Title:
Human Atlas: A Tool for Mapping Social Networks

CCS:
Social networks

Keywords:
mapping social networks
social network analysis

Abstract:
<p>Most social network analyses focus on online social networks. . While these networks encode important aspects of our lives ... many simple and independent subtasks. Due to the nature of social networks- -presence of highly connected nodes and tightly knit groups-if we ... we built the Human Atlas, a web-based tool for mapping social networks. . To test it, we partially mapped the social network of the MIT Media Lab. We ran a user study ...

Primary CCS:
Social networks

References:
G. Carullo, A. Castiglione, A. De Santis, and F. Palmieri. A triadic closure and homophily-based recommendation system for online social networks. World Wide Web Conference, 2015.

Full Text:
... Labmsaveski@mit.eduEric ChuMIT Media Labechu@mit.eduSoroush VosoughiMIT Media Labsoroush@mit.eduDeb RoyMIT Media Labdkroy@media.mit.eduABSTRACTMost social network analyses focus on online social networks.While these networks encode important ... end, we built the Human Atlas, a web-based tool formapping social networks. . To test it, we partially mappedthe social network of the MIT Media Lab. We ran a userstudy and ... connectionswithin the lab, demonstrating the potential of the tool.1. INTRODUCTIONMost social network analyses focus on online social net-works, such as Facebook, Twitter, ... ties.Moreover, most of these data are proprietary and the com-plete social networks are not available to the members of thecommunity themselves.However, most ... distribute it: we can ask every participant to map theirimmediate social network (i.e. ego network) and combineCopyright is held by the author/owner(s).WWW?16 ... 2016, Montr al, Qu bec, Canada.ACM 978-1-4503-4144-8/16/04.http://dx.doi.org/10.1145/2872518.2890552.the individual networks to assemble the social network ofthe entire community. Moreover, the task of building anego network ...
online social networks, , such asthose captured by Twitter or Facebook.8. REFERENCES[1] A.-L. ...

CCS:
Social network security and privacy

Keywords:
social network

Abstract:
<p>Online social networks (OSNs) are gaining in popularity and are used by a ...

Primary CCS:
Social network security and privacy

References:
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B. Carminati, E. Ferrari, and A. Perego, "Rule-Based Access Control for Social Networks," in On the Move to Meaningful Internet Systems 2006: OTM 2006 Workshops, OTM Confederated International Workshops and Posters, AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET, OnToContent, ORM, PerSys, OTM Academy Doctoral Consortium, RDDS, SWWS, and SeBGIS 2006, Montpellier, France, October 29 - November 3, 2006. Proceedings, Part II, 2006, vol. 4278, pp. 1734--1744.

Title:
Specification and Enforcement of Location-Aware Attribute-Based Access Control for Online Social Networks

CCS:
Social networks

Keywords:
social networks

Primary CCS:
Social networks

Full Text:
... and the results arepromising and encouraging.CCS Concepts?Information systems? Content ranking; Social networks; ... ;KeywordsSocial Networks; Clustering; Twitter1. INTRODUCTIONIt is very common in todays? social networks that several discussionthreads around similar topics are opened at the ... and (iii) temporal dimensions to generateconnections between short messages in social networks (i.e. in ourwork on Twitter), as we did in [11]. ...
... these messages should then increase.3.3 Temporal Similarity (TS)The nature of social networks is that of a quickly and dynamicallychanging and evolving system ...
... it is jus-tified because of the wide dynamics related to social networks. . Forleveraging the dynamics of social networks in the creation group-ing messages, we exploit the reactivity of ...
... information overload. We have usedTwitter as an example of a social network. . We have proposed anapproach considering several steps and using ... We have proposed anapproach considering several steps and using the social network in-formation: (i) content, (ii) users, (iii) time. The innovation in ...

Title:
Data Management for Social Networking

CCS:
Social networks

Keywords:
social networks

Abstract:
<p>Social networks are fascinating and valuable datasets, which can be leveraged to ... both the textual content and the graph structure of a social network, , e.g., social search and querying, and team formation. Finally, ... team formation. Finally, we consider critical aspects of implementing a social network database management system, and discuss existing systems. In this tutorial, ... state-of-the-art and desired features of a data management system for social networking,

Primary CCS:
Social networks

References:
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S. P. Borgatti, M. G. Everett, and L. C. Freeman. UCINET. In Encyclopedia of Social Network Analysis and Mining, pages 2261--2267. 2014.
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S. Cohen and N. Cohen-Tzemach. Implementing link-prediction for social networks in a database system. In Proceedings of the 3rd ACM SIGMOD Workshop on Databases and Social Networks, DBSocial 2013, New York, NY, USA, June, 23, 2013, pages 37--42, 2013.
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A. Guille, H. Hacid, C. Favre, and D. A. Zighed. Information diffusion in online social networks: A survey. SIGMOD Rec., 42(2):17--28, July 2013.
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D. Liben-Nowell and J. Kleinberg. The link-prediction problem for social networks. J. Am. Soc. Inf. Sci. Technol., 58(7):1019--1031, May 2007.
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Wikipedia. Social network analysis software -- Wikipedia, the free encyclopedia, 2012. {Online; Accessed Feb 2016}.

Full Text:
... thatleverage both the textual content and the graph structureof a social network, , e.g., social search and querying, andteam formation. Finally, we ... andteam formation. Finally, we consider critical aspects of im-plementing a social network database management system,and discuss existing systems. In this tutorial, we ... the state-of-the-art and desired featuresof a data management system for social networking, , anddiscuss open research challenges.1. INTRODUCTIONOur lives are deeply affected ... arise when storing and querying social data.The notion of a social network is commonly used narrowly,to refer to networks of friends or ... to networks of friends or followers in online applica-tions. However, social networks are in fact a broader con-cept, including a variety of ... USAc 2016 ACM. ISBN 978-1-4503-4191-2/16/06. . . $15.00DOI: http://dx.doi.org/10.1145/2902251.2902306broad sense, social networks are an interesting data source,whose importance has been recognized for ... early example of the community detectionproblem. Thus, key problems in social networks have beenstudied for almost a century, and yet take on ... both the tex-tual content and the graph structure of a social network, , e.g.,social search and querying, and team formation. Finally, weconsider ... the state-of-the-art and desired features of a data management systemfor social networking, , and discuss open research challenges.We note that social network database management is aresearch area that is huge in both ...
... weighted. Figure 1 contains a toy example of a smallundirected social network. .2.1 CentralityOne important task over a social network, , is finding nodes(i.e., people) who are important. The prominence ... central nodes.Given an adjacency matrix A representing the relationshipsin a social network, , the eigenvector centrality score for thenodes of a graph ... v4 v5 v8v3 v10 v9Figure 1: Toy example of a social network G.with v are likely to become friends with v in ...
... functions to measure effi-ciency of different types of data-stores for social networks. .)As is the case for centrality measures, there is no ...
... be considered is whatis the appropriate data model for a social network. . So far,we have viewed a social network simply as a directed orundirected graph. However, in practice, even ... is a directed hyper-edge.2An orthogonal issue is that people in social networks tendto be associated with large amounts of textual, temporal andspatial ... AND STRUCTUREIn the previous section, we adopted the simplification thata social network is simply a graph. However, the textualcontent attached to the ...
... been developed to estimate thecommunication cost between nodes in a social network. . In [54],the goal is to form a team with ... most general sense, social search is the problem ofleveraging a social network, , to improve the results of search-ing a corpus. Thus, ... personrecommendation [31]) is the problem of recommending peo-ple in a social network, , when given a set of keywords k, bya member ... given a set of keywords k, bya member of the social network u. The goal is to return ahigh-quality ranked list of ... overarbitrary graphs, they are not necessarily a best choice forquerying social networks. . In particular, graph query lan-guages focus mostly on precise ...
... recommendation or recognizing communities,that are more in the spirit of social- -network analysis.Several papers have studied the problem of querying specif-ically social networks. . Datalog [67] and RDF/SPARQL [68]have both been extended to ... as query languages forsocial networks. In addition, specialized query languagesfor social networks have also been developed. These are sur-veyed, next.SoQL [67], is ... also been developed. These are sur-veyed, next.SoQL [67], is a social- -network query language that is basedon SQL. In SoQL, a social network is a four-tuple(N,F, TN , TF ) ,containing a set ... SNQL is the ability to constructarbitrary new portions of a social network, , using a construc-tion query. This is lacking in SoQL.Finally, ... a construc-tion query. This is lacking in SoQL.Finally, [34] combines social- -network querying, data min-ing and clustering capabilities. This is achieved by ... structure and content are chal-lenging due to the volume of social networks and to thevelocity in which the data changes. In addition, ...
... used as building blocks for ex-pressing interesting queries over the social network. . (Wenote that a similar approach was taken to integrate ... methodologiesfor managing this data. In particular, we consider bench-marks for social network data management, the problem ofstoring and compressing social networks, , graph databases,social network analysis tools and the systems of big playersin the industry.4.1 ... of the network, or the behavior of the users.Benchmarks for social network analysis data managementinclude some of these tasks. However, there are ... throughput.1704.2 Storing and Compressing Social NetworksDefining methods to store a social network, , while allow-ing efficient access for query processing, is key ...
... appearing, nodes, and by using gapencoding [20].The nodes in a social networks do not have extrinsic in-formation that can be leveraged for ... be used to achieveeffective sorting of the nodes of a social network, , so thatnodes close to one another are also similar ... opposed to previous work that consid-ered vertex-balanced partitions).4.3 Graph DatabasesAbstractly, social networks are often viewed simply asgraphs. There has been significant work ... of the work on graph databases is highly relevant tomanaging social network data. However, much of the workis not directly applicable (or ... a graph as a data modelmay be overly simplistic. A social network may come inconjunction with a standard relational database that storesmission ... storesmission critical information, e.g., a university database, to-gether with a social network of students. In addition, muchinteresting information in a social network is in rich textualand spatial data associated with the users. ... people). Furthermore, even when tak-ing a simplistic view of a social network as simply beinga directed graph, tools for graph databases usually ... graph databases usually do notprovide built-in methods to perform key social network tasks(e.g., link prediction, social search, community detection).4.4 Social Network ... Analysis ToolsMany software tools are available for analysis of arbi-trary social networks. . In fact, Wikipedia [78] lists close to80 social- -network analysis tools. Roughly speaking, thesetools usually focus on one or ... aspects:visualization, analysis, mining, filtering and manipulation.Some of the better known social network analysis tools in-clude UCINET, Gephi and Pajek. The main capabilitiesof ... and hypothesis testing.Gephi [15] allows for filtering, navigating, manipulating andclustering social network
... of thousands to millionsof vertices.While these tools are useful for social network analysis,4http://neo4j.com/5http://orientdb.com/orientdb/6http://thinkaurelius.com/171i.e., for accomplishing the tasks of Section 2, they lack ... structures,such as groups of nodes, or associated tables of attributes.Finally, social network analysis systems cannot easily inte-grate powerful tools for geospatial analysis ... back and forth between a databasesystem and a system for social network analysis. Clearlysuch a solution has severe limitations. It does not ... data. However, they cannot be a solutionfor data management of social networks. .4.5 The Big PlayersThere are currently several social networks of mammothsize, used by a large percentage of the world?s ... namely LinkedIn, Facebook and Twitter. Thereare, of course, other huge social networks. . We focus onthese three because of the wealth of ... are reportedly 400 million user accounts atLinkedIn [3]. Facebook8, a social networking system launchedin 2004, was originally geared towards college students. Since2006, ... monthly users at Twitter [4].The enormous user base of these social network systemscreates significant challenges in data management. Users ofthe systems expect ... (page views, click-throughs). This data must be made immediately accessibleto social network users. In fact, often the most recent datais also the ... we touch upon two aspects of data man-agement within huge social networks. . Obviously, it is notpossible to provide all details within ...
... these companies are rather limited andcannot directly express many key social network tasks. Thisis perhaps not surprising, as the focus here is ...
... to be possible to formulate richer queries, which lever-age the social network graph (e.g., to return a tweet from auser who follows ... ChallengesWhile the industry giants have their own systems for man-aging social network data, smaller-sized companies do notcurrently have a ready-to-use solution for ... simple network analysis operationsquite expensive.In practice, it seems that for social network queries, it issufficient to return the most highly ranked results. ... old query results.Another important issue is effective privacy management.Standard online social networks provide a very limited ar-ray of privacy controls for their ... As a simple example, a den-tist who participates in a social network may desire to bea possible result for queries relating to ... controls is a challenge, as is determininghow to evaluate built-in social network functions withoutinadvertently exposing private information.Evaluating queries in a privacy-aware manner ... advanced features that wouldbe invaluable within the context of a social- -network database.One such feature is the ability to ask hypothetical questions(e.g., ... a network. Thus, such a querymay be issued over the social network of some company, be-fore determining whether an employee can be ...
... L. Adamic and E. Adar. Friends and neighbors on theweb. Social Networks, , 25:211?230, 2001.[7] A. S. Aiyer, M. Bautin, G. J. ... and S. Vigna. Layeredlabel propagation: A multiresolution coordinate-freeordering for compressing social networks. . InProceedings of the 20th International Conference onWorld Wide Web, ... M. G. Everett, and L. C. Freeman.UCINET. In Encyclopedia of Social Network Analysisand Mining, pages 2261?2267. 2014.[22] F. Bourse, M. Lelarge, and ...
... Kumar, S. Lattanzi,M. Mitzenmacher, A. Panconesi, and P. Raghavan. Oncompressing social networks. . In Proceedings of the15th ACM SIGKDD International Conference onKnowledge ... USA, 2009. ACM.[28] S. Cohen and N. Cohen-Tzemach. Implementinglink-prediction for social networks in a databasesystem. In Proceedings of the 3rd ACM SIGMODWorkshop ... In Proceedings of the 3rd ACM SIGMODWorkshop on Databases and Social Networks, ,DBSocial 2013, New York, NY, USA, June, 23, 2013,pages 37?42, ... Chafi,A. Gubichev, A. Prat, M.-D. Pham, and P. Boncz.The ldbc social network benchmark: Interactiveworkload. In Proceedings of the 2015 ACM SIGMODInternational Conference ... Hacid, C. Favre, and D. A. Zighed.Information diffusion in online social networks: : Asurvey. SIGMOD Rec., 42(2):17?28, July 2013.[40] P. Gupta, A. ... A. An. Discovering top-k teams ofexperts with/without a leader in social networks. . InProceedings of the 20th ACM International Conferenceon Information and ... Kleinberg, and E. Tardos. Maximizingthe spread of influence through a social network. . InProceedings of the Ninth ACM SIGKDD InternationalConference on Knowledge ...
... K. Liu, and E. Terzi. Finding a team ofexperts in social networks. . In Proceedings of the 15thACM SIGKDD international conference on ... Li, M.-K. Shan, and S.-D. Lin. Context-basedpeople search in labeled social networks. . InProceedings of the 20th ACM International Conferenceon Information and ... USA, 2011.ACM.[57] D. Liben-Nowell and J. Kleinberg. The link-predictionproblem for social networks. . J. Am. Soc. Inf. Sci.Technol., 58(7):1019?1031, May 2007.[58] G. ... M. S. Mart ?n, C. Gutierrez, and P. T. Wood. SNQL:A social networks query and transformation language.In Proceedings of the 5th Alberto MendelzonInternational ... Rangapuram, T. Bu hler, and M. Hein. Towardsrealistic team formation in social networks based ondensest subgraphs. In Proceedings of the 22NdInternational Conference on ... R. Ronen and O. Shmueli. Evaluating very largedatalog queries on social networks. . In EDBT 2009,12th International Conference on Extending DatabaseTechnology, Saint ...
... D. d. C. Reis, and B. Ribeiro-Neto. Efficientsearch ranking in social networks. . In Proceedings ofthe Sixteenth ACM Conference on Conference onInformation ... WSDM?10, pages 261?270, New York, NY, USA, 2010. ACM.[78] Wikipedia. Social network analysis software ?Wikipedia, the free encyclopedia, 2012. [Online;Accessed Feb 2016].[79] ...

CCS:
Social networking sites

Keywords:
social networks

Abstract:
... has addressed this important aspect, primarily because large-scale studies of social networks are impractical using traditional methods such as surveys. In this ... provide the first comprehensive view into the composition of immigrants' social networks in the United States using data from the social networking site Facebook. We measure the integration of immigrant populations through ...

Primary CCS:
Social networking sites

References:
J. S. MacDonald and L. D. MacDonald. Chain migration ethnic neighborhood formation and social networks. The Milbank Memorial Fund Quarterly, pages 82--97, 1964.

Full Text:
... has addressed this important aspect, primarily be-cause large-scale studies of social networks are impractical usingtraditional methods such as surveys. In this study ... groups, deriving a map of cultural friendship affinities.CCS Concepts?Human-centered computing! Social networking sites; ?Appliedcomputing! Sociology;Keywordsmigration, social networks, , integrationINTRODUCTIONImmigrants comprise more than 13% of the United States ... rights licensed to ACM.ISBN 978-1-4503-4208-7/16/05. . . $15.00DOI: http://dx.doi.org/10.1145/2908131.2908163migration scholars. Social networks are one of the main pathwaysthrough which the individual migration ... broaden this scope by providing the first view ofmigration and social networks in the United States. We do so by an-alyzing, in ... States. We do so by an-alyzing, in aggregate, de-identified Facebook social network data.We begin by quantifying the extent to which migrants seek ...
... goal is to produce sim-ilar measures of integration, using the social network structure ofimmigrants who have moved from one country to the ... from one country to the US.Our focus is on the social networks
... tieswe contend that, in aggregate, the composition of immigrants? on-line social networks can offer a window into offline friendships notpossible by other ... TERMINOLOGYWe limited our analyses to aggregate measures based on de-identified social network data for people from the U.S. who usedFacebook at least ... observe that while immigrant groups vary in how in-tegrated their social networks
... Canada, Australia, or South Africahave upwards of 90% of their social networks composed of Amer-icans. People from Mexico have about 60% of ... India, 29%. Immigrants from Cuba have the lowest exposurein their social networks to Americans, consistent with their settlingpredominantly in a few geographical ... availability atlocal levels in more detail.ValidationWhile ?ground-truth? data on migrants? social networks is scarce,we can compare our measurements against established metrics ofimmigrant ...
... alone (ANOVA p-value = 0.003).Co-immigrant affinityThe evolution of an immigrant?s social network depends not onlyon cultural affinity, but also a variety of ...
... therelationship between the proportion of immigrant compatriots andthe proportion of social networks composed of compatriots.The general trend, seen in Figure 8, is ... than 0.1% of the city?spopulation), the proportions of compatriots in social networks jump82AEAFALAMARASAUBABBBDBEBGBOBRBSBYBZCACDCHCICLCMCNCOCRCUCVCZDEDKDOECEGERESETFJFMFRUKGHGRGTGUGYHKHNHTHUIDIEILINIQIRITJMJOJPKEKHKRLALBLKLRLTMAMDMKMMMPMXMYNGNINLNONPNZPAPEPHPKPLPRPSPTRORSRUSASESGSLSNSOSVSYTHTRTTTWUAUYVEVIVNZA40608040 60Index of dissimilarityExposure (%)Population size100001000001000000ContinentAfricaAmericasAsiaEuropeOceaniaFigure 7: Comparison of index ... compatriots in the city, the proportion of compa-triots in the social networks stops growing, and is complementedby locals and other immigrant groups.While ... is the case with people whohave moved from India. Their social networks in the US can havemore than 50% compatriot ties on ... from Mexico will typi-cally have fewer than 50% of their social networks composed ofcompatriots even as the proportion of compatriots in the ... this paper we presented the first large-scale analysis of immi-grants? social networks in the United States. We found several inter-esting correspondences, for ...
... type appear to play arole in the structure of immigrants? social networks. . Our findingslikewise suggest that migrant populations that are from ... paper presents thefirst glimpse into the potential of using online social network datato understand the integration of immigrant communities.REFERENCES[1] R. Alba and ... MacDonald and L. D. MacDonald. Chain migrationethnic neighborhood formation and social networks. . TheMilbank Memorial Fund Quarterly, pages 82?97, 1964.[13] D. S. ...

CCS:
Social networks

Keywords:
social networks

Primary CCS:
Social networks

References:
Augusto Q. Macedo, Leandro B. Marinho, and Rodrygo L.T. Santos. 2015. Context-Aware Event Recommendation in Event-based Social Networks. In RecSys. Vienna, Autria, 123--130.
Yu Zheng. 2012. Tutorial on Location-Based Social Networks. In WWW. Lyon, France, 679--688.

Full Text:
... solution is very close to the ideal ranking.CCS CONCEPTS?Information systems! Social networks; ; ?Human-centeredcomputing! Social recommendation;KEYWORDSReview Recommendation, Social Networks1 INTRODUCTIONOnline reviews have ... when the items being reviewed are loca-tions. Specially, location based social networks, , such as TripAdvi-sor1 and FourSquare2, are important tools for ...
... and then state the problem.2.1 Location Based Social NetworksLocation based social networks (LBSN) are web platforms that re-flect the social networking structures of real world [35]. In recentyears, the study of ...
... an efficient way toanalyze opinions about topics and entities on social networks likeTwitter. However, changes in opinions are not necessarily usefulby themselves, ...
... problem of automatically determining the quality of contentgenerated by online social networking users has attracted much at-tention [10, 26, 31]. For instance, ...
... Pre-processingEvaluating the helpfulness of reviews requires a dataset built froma social network that allows (i) users to write reviews for POIs,and (ii) ... reviews. The first restric-tion is easily satisfied by most POI-related social networks (e.g.FourSquare and TripAdvisor), but the second is not a common ...
... Marinho, and Rodrygo L.T. Santos. 2015.Context-Aware Event Recommendation in Event-based Social Networks. . In Rec-Sys. Vienna, Autria, 123?130.[21] Luciana B. Maroun, Mirella ... Arlington, Virginia, USA, 51?57.[35] Yu Zheng. 2012. Tutorial on Location-Based Social Networks. . In WWW. Lyon,France, 679?688.[36] Yu Zheng, Lizhu Zhang, Zhengxin ...

CCS:
Social networking sites

Keywords:
social networking

Abstract:
... In a separate line of research, we explored how online social networking tools might be leveraged for pedagogical purposes. Rather than treating ... and vice versa. In particular: <ol><li>After receiving help on a social network, , what changes are made to code? Are these changes ...

CCS:
Online social networks

Keywords:
social networks

Primary CCS:
Online social networks

References:
W. Chen, Y. Wang, and S. Yang. Efficient influence maximization in social networks. In 15th ACM SIGKDD, pages 199--208. ACM, 2009.
C. Zang, P. Cui, and C. Faloutsos. Beyond sigmoids: The nettide model for social network growth, and its applications. In 22nd ACM SIGKDD, pages 2015--2024. ACM, 2016.

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... imposegood control over information cascades in real applications.CCS Concepts?Networks? Online social networks; ;Keywords: Social networks; ; Information cascades; Structures1. INTRODUCTIONInformation cascades are ubiquitous phenomena in ...

CCS:
Social networking sites

Keywords:
Social networking sites
Social network addiction

Abstract:
<p> The worldwide use of social networking sites (SNSs) continues to dramatically increase. People are spending unexpected ...

References:
Kuss, D. J. and Griffiths, M. D. 2011. Online social networking and addiction-A review of the psychological literature. International Journal of Environmental Research and Public Health. 8, 9: 3528-3552.
Poh, A., Cheak, C., Guan, G. and Goh, G. 2012. Online social networking addiction: exploring its relationship with social networking dependency and mood modification among undergraduates in Malaysia. In International Conference on Management, Economics and Finance (Sarawak, Malaysia), 247–262.
Abdesslem, F., Parris, I. and Henderson, T. 2012. Reliable online social network data collection. Computational Social Networks, Springer London. 183–210.
Burke, M., Marlow, C. and Lento, T. 2010. Social network activity and social well-being. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, ACM.
Geisel, O., Panneck, P., Stickel, A., Schneider, M. and Christian A. Müller. 2015. Characteristics of social network gamers: Results of an online survey. Frontiers in Psychiatry. 6: 1–5.
Alfantoukh, L. and Durresi, A. 2014. Techniques for collecting data in social networks. In Network-based Information Systems (NBis), 2014 17th International Conference on. IEEE. 336–341.
Petrillo, U. F. and Consolo, S. 2014. A framework for the efficient collection of big Data from online social networks. Intelligent Networking and Collaborative Systems (INCos), 2014 International Conference on. IEEE. 34–41.
Benevenuto, F., Rodrigues, T., Cha, M and Almeida, V. 2009. Characterizing user behavior in online social networks. In Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference. 49–62.
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Schneider, F., Feldmann, A., Krishnamurthy, B. and Willinger, W. 2009. Understanding online social network usage from a network perspective. In Proceedings of the 9th ACM SIGCOMM Conference on Internet Measurement Conference, ACM. 35-48.

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... Khru, Bangkok, Thailand +66-2-470-9380 tiranee.ach@mail.kmutt.ac.th ABSTRACT The worldwide use of social networking sites (SNSs) continues to dramatically increase. People are spending unexpected ... of the risks of excessive SNS usage. CCS Concepts ?Information systems~Social networking sites Keywords Social networking sites, SNS, User behavior, Social network addiction. 1. INTRODUCTION Digital technology plays an important role in ... WORK 2.1 Negative Consequences of Excessive SNS Usage SNSs, online social networks (OSNs), or simply social networks are virtual communities where groups of people with similar interests ...
... HTTP request/response [16]. Similarly, some researchers collect data through a social network aggregator [17]. Others collect data by tracing network traffic from ...
... [1] Kuss, D. J. and Griffiths, M. D. 2011. Online social networking and addiction-A review of the psychological literature. International Journal of ... A., Cheak, C., Guan, G. and Goh, G. 2012. Online social networking addiction: exploring its relationship with social networking dependency and mood modification among undergraduates in Malaysia. In International ... Abdesslem, F., Parris, I. and Henderson, T. 2012. Reliable online social network data collection. Computational Social Networks, , Springer London. 183?210. [8] Burke, M., Marlow, C. and ... 183?210. [8] Burke, M., Marlow, C. and Lento, T. 2010. Social network activity and social well-being. In Proceedings of the SIGCHI Conference ... A., Schneider, M. and Christian A. M ller. 2015. Characteristics of social network gamers: Results of an online survey. Frontiers in Psychiatry. 6: ... L. and Durresi, A. 2014. Techniques for collecting data in social networks. . In Network-based Information Systems (NBis), 2014 17th International Conference ... framework for the efficient collection of big Data from online social networks. . Intelligent Networking and Collaborative Systems (INCos), 2014 International Conference ...
... M and Almeida, V. 2009. Characterizing user behavior in online social networks. . In Proceedings of the 9th ACM SIGCOMM Conference on ... Pillai, A. and Juneja, D. 2014. Study and analysis of social network aggregator. Optimization, Reliability, and Information Technology (ICROIT), 2014 International Conference ... Feldmann, A., Krishnamurthy, B. and Willinger, W. 2009. Understanding online social network usage from a network perspective. In Proceedings of the 9th ...

CCS:
Social networks

Keywords:
social networks
social network
social networking

Abstract:
... based on a simple observation: each person has a distinctive social network, , and thus the set of links appearing in one's ...

Title:
De-anonymizing Web Browsing Data with Social Networks

References:
B. Krishnamurthy and C. E. Wills. On the leakage of personally identifiable information via online social networks. In Proceedings of the 2nd ACM workshop on Online social networks, pages 7--12. ACM, 2009.
A. Ramachandran, Y. Kim, and A. Chaintreau. "I knew they clicked when I saw them with their friends". In Proceedings of the 2nd Conference on Online Social Networks, 2014.
G. Wondracek, T. Holz, E. Kirda, and C. Kruegel. A practical attack to de-anonymize social network users. In IEEE Symposium on Security and Privacy, 2010.

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... we outline a system that addresses thesehurdles for the Twitter social network and enables real-timelinking of web browsing histories to user profiles.4.1 ...
... online socialnetworks. In Proceedings of the 2nd ACM workshop onOnline social networks, , pages 7?12. ACM, 2009.[19] P. Laperdrix, W. Rudametkin, and ...
... them with theirfriends?. In Proceedings of the 2nd Conference onOnline Social Networks, , 2014.[34] F. Roesner, T. Kohno, and D. Wetherall. Detectingand ... Holz, E. Kirda, and C. Kruegel. Apractical attack to de-anonymize social network

Title:
Hybrid de-anonymization across real-world heterogeneous social networks

CCS:
Online social networks

Keywords:
social networks privacy
heterogeneous social networks

Abstract:
... enjoy various utility and services, people are active in multiple social networks nowadays. With tons of data generated on platforms, multiple accounts ... on platforms, multiple accounts of the same user in different social networks can be used to de-anonymize the user in a large ... few works throw light on the deanonymization between real-world heterogeneous social networks. . In this paper, we propose a Hybrid De-anonymization Scheme ... propose a Hybrid De-anonymization Scheme (HDS) aiming at de-anonymizing heterogeneous social networks. . HDS firstly leverages the network graph structure to significantly ... mapping users with a high confidence. Performance evaluation on real-world social network datasets shows that HDS has considerable accuracy on de-anonymization and ...

Primary CCS:
Online social networks

References:
H. Li, H. Zhu, S. Du, X. Liang, and X. Shen, "Privacy leakage of location sharing in mobile social networks: Attacks and defense", In IEEE Transactions on Dependable and Secure Computing vol: PP, Issue: 99, pp: 1--1, 2016.
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L. Backstrom, C. Dwork and J. Kleinberg, "Wherefore art thou r3579x?: anonymized social networks, hidden patterns, and structural steganography", ACM WWW'07, 181--190, 2007.
Narayanan A, Shmatikov V, "De-anonymizing social networks", In 30th IEEE Symposium on Security and Privacy, (pp. 173--187), 2009.
Nilizadeh S, Kapadia A, Ahn Y Y. "Community-enhanced de-anonymization of online social networks", In Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security, (pp. 537--548), 2014.
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S. Ji, W. Li, M. Srivatsa, J. He and R. Beyah, "Structure based Data De-anonymization of Social Networks and Mobility Traces", Springer Information Security, 237--254, 2014.
M. Srivatsa and M. Hicks. "Deanonymizing mobility traces: Using social networks as a side-channel", In Proceedings of the 2012 ACM conference on Computer and communications security, (pp. 628--637), 2012.
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Y. Zhang, J. Tang, Z. Yang, J. Pei, and S. Yu, "COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency", Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, (pp. 1485--1494), 2015.
M. Li, N. Cao, S. Yu, and W. Lou, "FindU: Privacy-Preserving Personal Profile Matching in Mobile Social Network", In Proceedings of IEEE INFOCOM, (pp. 2435--2443), 2011.
M. Li, S. Yu, N. Cao, and W. Lou, "Privacy-Preserving Distributed Profile Matching in Proximity-based Mobile Social Networks", IEEE TWC, vol. 12, no.5, 2013.
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R. Zhang, Y. Zhang, J. Sun, G. Yan, "Privacy-Preserving Profile Matching for Proximity-Based Mobile Social Networking", IEEE JSAC, vol. 31, no. 9, pp. 656--668, 2013.
L. Yartseva and M. Grossglauser. "On the performance of percolation graph matching", In Proceedings of the first ACM conference on Online social networks, (pp. 119--130), 2013.

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... propose a Hybrid De-anonymization Scheme (HD-S) aiming at de-anonymizing heterogeneous social networks. . HDSfirstly leverages the network graph structure to significantly reducethe ... mapping users with a high confidence. Perfor-mance evaluation on real-world social network datasets shows thatHDS has considerable accuracy on de-anonymization and signifi-cantly ... Networks Privacy, De-anonymizaion, Heterogeneous SocialNetworks1 INTRODUCTIONAlong with overwhelming popularity of social networks, , peopleenjoy abundant functionalities and services of a variety of ... and making friends. Due to the differen-t functionalities of different social networks, , a user tends to signin multiple social networks for different purposes. According tothe report conducted by Pew Research ... such as Facebook,Twitter, MySpace, or LinkedIn[1]. Aggregating user profiles fromdifferent social networks reveals various aspects of users. It is in-teresting that cross-network ... the one hand, once the user?s multiple accounts of differ-ent social networks are identified or mapped, these accounts? pro-files, preferences, and activities ... increasing privacy con-cerns. The process of identifying user from a social network (e.g.,anonymized network) based on another social network (e.g., aux-iliary network) is called ?de-anonymization?. Recently, there is anincreasing ... anincreasing interest to study how to ?de-anonymize? or ?re-identify?users across social networks, , which mainly falls to the following t-wo categories: profile ... basedde-anonymization, which either suffer from high false positive orassuming the social networks are aligned.Profile based de-anonymization (or profile matching) exploitsthe similarities of ... signatures, and tags to map theusers multiple accounts on different social networks [7?9]. Profilematching has the advantages of identifying a specific node ...
... to the common per-sons. However, since it takes the whole social network users setas the candidate set, the false positive of profile ... leverages the similarity of social networks?graph structures. In particular, any social network can be modelledas a graph and each user is represented ... similar users whom are interestedin or acquainted with in different social networks. . In other word-s, these kind of approaches are based ... kind of approaches are based on the assumption that thedifferent social networks of the same group users should show thesimilar network topology, ... the case that two networks are aligned. How-ever, in heterogeneous social networks, , this assumption may not al-ways hold due to the ... be always overlapping. The diversity of usage pattern on d-ifferent social networks will further render the inconsistency of thenetwork structures of the ... further render the inconsistency of thenetwork structures of the different social networks. . Therefore, instructure based de-anonymization, how to obtain the anchor ... based de-anonymization, how to obtain the anchor pointsand align heterogeneous social networks represents a key challenge.In this study, we present a Hybrid ... challenge.In this study, we present a Hybrid De-anonymization Scheme forheterogeneous social networks, , which is coined as HDS. Differentfrom any previous works ... We propose Hybrid De-anonymization Scheme (HDS) tode-anonymize users across heterogeneous social network- -s. The proposed scheme jointly exploits publicly avail-able network graph ... profile information,which is expected to be feasible across real-world hetero-geneous social networks and significantly increase the de-anonymization accuracy.? We conduct extensive experiments ... the de-anonymization accuracy.? We conduct extensive experiments on real-world hetero-geneous social network datasets to demonstrate the effec-tiveness of our proposed scheme. The ... po-tential risks to the community of launching de-anonymizationattack across real-world social networks, , and calls for thefollowing research efforts on privacy-preserving personalrecommendation.The ... III. Then, Section IV evaluates theresults based on three real-world social networks. . Section V dis-cusses related research works, and VI concludes ... works, and VI concludes this paper.2 ATTACKMODELWe assume two heterogenous social networks GA and GU . GA isdenoted as anonymous network and ... in large scaleand with a high confidence from two different social networks. . Thisproblem can be formally defined as follows.PROBLEM 1. Given ... be formally defined as follows.PROBLEM 1. Given (1) two different social network graphsGA =(VA; EA) and GU = (VU ; EU ), ...
... formally defined as follows:DEFINITION 1. A community C in a social network graph is adisjoint partition, which corresponds to a social circle ... to beavailable to public. To exploit profile information across heteroge-neous social networks, , we firstly give a uniform definition:DEFINITION 2. Let Xi ... If a uservi?s jth attribute is not available on the social network (e.g., Tomchooses not to show his hometown on Twitter), then ... show his hometown on Twitter), then xij = null.Since heterogeneous social network platforms contain differentkinds of profile information, and some of which ... two users? accounts from two2Figure 1: Overview of our schemeheterogeneous social networks is similar to an ontology matchingproblem. In general, ontology matching ... Detection and AlignmentThe goal of first step is to partition social network graphs GA andGU into two sets of communities CA = ...
... strings (e.g. username and person name). These at-tributes on different social networks often have editing differences,such as difference among ?Jones, David?, ?David ... HDS scheme by conduct-ing experiments on a set of real-world social networks data.4.1 DatasetsThe datasets of three real-world heterogeneous online social net-works, ... these social networks.We evaluate our proposed scheme on the three social networks pair-wise.? Last.fm is the world?s largest online music catalogue andhas ... largest online music catalogue andhas been recognized as a popular social network for musicenthusiasts. Last.fm builds detailed profiles of users musi-cal tastes ... consists of 136,420users and 1,685,524 friend relationship.? LiveJournal is a social networking site and blogging plat-form that allows users to find each ... consistsof 3,017,286 users and 19,360,690 friend relationship.? MySpace is a social networking website offering an in-teractive, user-submitted network of friends, personal pro-files, ... datasetconsists of 854,498 individuals and 6,489,736 friend rela-tionship.We build undirected social network graphs according to ?friend?or ?follow? relationship in these social networks. . The statistics ofthe graphs are shown in Table 1. ... from [23, 31], which contain pair-wisematched user id of two social networks. . The data were originallycollected by Perito el. al [31] ... [31] through Google Profiles service byallowing users to integrate different social network services.Table 1: Statistics of social networksNetwork Nodes Edges Av. DegreeLast.fm ...
... However, only a few of themare suitable to real-world heterogeneous social networks for vari-ous reasons. Some techniques are constrained by their restrictedrequirements ... are constrained by their restrictedrequirements of the same size of social networks (or same numberof nodes) [10, 11], sybil users [12] or ... usually difficult to obtain datasets with idealoverlaps from two heterogenous social networks, , which limit theperformance of graph-based approaches in practice. According ... previous studies exploit various user profileinformation to connect individuals between social networks, , includ-ing usernames [8, 22], tags [7], activities [21], and ... user in one social networkand all users in the other social network and find the most similarone, is used as the baseline.Figure ... outincorrect matchings, thus increasing the accuracy.5 RELATEDWORK5.1 Structure based de-anonymizationDe-anonymizing social networks is a hot research topic in recentyears. Structure based de-anonymization ... de-anonymization works are based on the as-sumption that the different social networks of the same group usersshould show the similar network topology, ... data [12]. Narayanan andShmatikov performed the de-anonymization attack to large-scaledirected social networks.
... Narayananand Shmatikov?s attack by proposing a community-enhanced de-anonymizing scheme of social networks. . Then, Lai [15] proposedto detect communities in social networks via user?s interests andde-anonymize users in communities. Ji et al. ... using online social networksas side channel [17]. However, in heterogeneous social networks, ,this assumption may not always hold due to the fact ... always hold due to the fact that the usersof different social networks may not always be overlapping. Thediversity of usage pattern on ... not always be overlapping. Thediversity of usage pattern on different social networks will furtherrender the inconsistency of the network structures of the ... some private attributes. In our work, wetry to de-anonymize heterogeneous social networks by consideringboth semantic information and structure information.5.2 Profile based user ... techniques to find correct mapping [9]. Zhanget al. [23] connected social networks users by considering both lo-cal and global consistency among multiple ... and [25], the first privacy-preserving personalprofile matching schemes for mobile social networks was proposedby Li et al. In this scheme, an initiating ... propose a practical Hybrid De-anonymization Scheme(HDS) for de-anonymizing real-world heterogeneous social network- -s. HDS is a de-anonymizing scheme that exploits the network ... of our proposed scheme based on adataset of three real-world social networks show that it achieveshigh accuracy with a slight sacrifice of ...
... that our proposed scheme is ef-fective to de-anonymize real-world heterogeneous social network- -s. Nodes anonymization and privacy preserving in social networksshould become ... and X. Shen, ?Privacy leakage of location shar-ing in mobile social networks: : Attacks and defense?, In IEEE Transactions onDependable and Secure ... Backstrom, C. Dwork and J. Kleinberg, ?Wherefore art thou r3579x?:anonymized social networks, , hidden patterns, and structural steganography?,ACMWWW?07, 181?190, 2007.[13] Narayanan A, ... and structural steganography?,ACMWWW?07, 181?190, 2007.[13] Narayanan A, Shmatikov V, ?De-anonymizing social networks? ?, In 30th IEEESymposium on Security and Privacy, (pp. 173-187), ... Nilizadeh S, Kapadia A, Ahn Y Y. ?Community-enhanced de-anonymization ofonline social networks? ?, In Proceedings of the 2014 ACM SIGSAC Conference onComputer ... 2014.[15] S. Lai, H. Li, H. Zhu, N. Ruan, ?De-anonymizing Social Networks: : Using UserInterest as a side-channel?, In 2015 IEEE/CIC International ... J. He and R. Beyah, ?Structure based Data De-anonymization of Social Networks and Mobility Traces?, Springer InformationSecurity, 237?254, 2014.[17] M. Srivatsa and ... J. Qian, X.-Y. Li, C. Zhang, and L. Chen, ?De-anonymizing Social Networks andInferring Private Attributes Using Knowledge Graphs?, In The 35th Annual ... Z. Yang, J. Pei, and S. Yu, ?COSNET: Connecting Heteroge-neous Social Networks with Local and Global Consistency?, Proceedings of the21th ACM SIGKDD ... Yu, and W. Lou, ?FindU: Privacy-Preserving Personal ProfileMatching in Mobile Social Network? ?, In Proceedings of IEEE INFOCOM, (pp.2435-2443), 2011.[25] M. Li, ... Cao, andW. Lou, ?Privacy-Preserving Distributed Profile Match-ing in Proximity-based Mobile Social Networks? ?, IEEE TWC, vol.12, no.5, 2013.[26] R. Zhang, Y. Zhang, ... Zhang, J. Sun, G. Yan, ?Fine-grained private matching forproximity-based mobile social networking? ?, In Proceedings of IEEE INFOCOM,(pp. 1969-1977), 2012.[27] R. Zhang, ...
Sun, G. Yan, ?Privacy-Preserving Profile Matching forProximity-Based Mobile Social Networking? ?, IEEE JSAC, vol. 31, no. 9, pp. 656-668, 2013.[28] ... graphmatching?, In Proceedings of the first ACM conference on Online social networks, ,(pp. 119-130), 2013.7Abstract1 Introduction2 Attack Model2.1 Graph Structure Model2.2 Profile ...

CCS:
Social network security and privacy

Keywords:
online social networks

Title:
Argumentation for Resolving Privacy Disputes in Online Social Networks: (Extended Abstract)

Primary CCS:
Social network security and privacy

References:
Y. Mester, N. Kökciyan, and P. Yolum. Negotiating privacy constraints in online social networks. In F. Koch, C. Guttmann, and D. Busquets, editors, Advances in Social Computing and Multiagent Systems, volume 541 of Communications in Computer and Information Science, pages 112--129. Springer, 2015.
R. Wishart, D. Corapi, S. Marinovic, and M. Sloman. Collaborative privacy policy authoring in a social networking context. In Proceedings of the IEEE International Symposium on Policies for Distributed Systems and Networks (POLICY), pages 1--8, 2010.

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... [Artificial Intelligence]: Distributed Artificial Intel-ligence Multiagent systemsGeneral TermsAlgorithms, DesignKeywordsPrivacy; Online Social Networks; ; Argumentation1. INTRODUCTIONPreserving privacy of users in online social networks ... is im-portant. Usually, users specify their privacy constraints andthe online social network is expected to enforce them. How-ever, many times a piece ... work, we advocate an agent-based approach where eachuser in the social network is represented by an agent thatmanages its user?s privacy constraints. ... content should be shared or not.2. TECHNICAL DETAILSWe represent a social network user with an agent. Themain goal of an agent is ... this, an agent is equipped with an ontologyto represent the social network domain, the content beingshared, the relationships of its user, and ... in that: (i)Agents are equipped with ontologies to represent knowledge(the social network domain and the privacy constraints). (ii)Agents generate arguments by using ...
... use their own on-tologies or consult other agents in their social network tocollect information. This is similar to real life where peopleconsult ... a winning argument. Thus, :bob shares the photoin the online social network. . In this scenario, :bob has con-vinced :alice to share ...
... Mester, N. Ko kciyan, and P. Yolum. Negotiatingprivacy constraints in online social networks. . InF. Koch, C. Guttmann, and D. Busquets, editors,Advances in ...

CCS:
Online social networks

Keywords:
social network

Abstract:
<p>Betweenness centrality (BWC) is a fundamental centrality measure in social network analysis. Given a large-scale network, how can we find the ...

References:
T. Alahakoon et al. K-path centrality: A new centrality measure in social networks. In Proceedings of the 4th Workshop on Social Network Systems, page 1. ACM, 2011.
D. Kempe, J. Kleinberg, and É. Tardos. Maximizing the spread of influence through a social network. KDD, 2003.
M. E. Newman. A measure of betweenness centrality based on random walks. Social networks, 27(1):39--54, 2005.

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... RI 02912eli@cs.brown.eduABSTRACTBetweenness centrality (BWC) is a fundamental centrality mea-sure in social network analysis. Given a large-scale network,how can we find the most ...
... T. Alahakoon et al. K-path centrality: A new centralitymeasure in social networks. . In Proceedings of the 4thWorkshop on Social Network Systems, page 1. ACM, 2011.[3] R. Albert, H. Jeong, and ...
... Kleinberg, and . Tardos. Maximizing thespread of influence through a social network. . KDD,2003.[26] J. M. Kleinberg. Authoritative sources in a hyperlinkedenvironment. ... E. Newman. A measure of betweenness centralitybased on random walks. Social networks, , 27(1):39?54,2005.[33] L. Page, S. Brin, R. Motwani, and T. ...

CCS:
Social network analysis

Keywords:
social network analysis

Abstract:
... role in the revolution of our daily life. The location-based social networks (LBSN) have emerged and facilitated the users to share the ...

Primary CCS:
Social network analysis

References:
Z. Jin, D. Shi, Q. Wu, H. Yan, and H. Fan. Lbsnrank: personalized pagerank on location-based social networks. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing, pages 980--987. ACM, 2012.
H. Wang, M. Terrovitis, and N. Mamoulis. Location recommendation in location-based social networks using user check-in data. In Proceedings of the 21st ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pages 374--383. ACM, 2013.
M. Ye, P. Yin, and W. C. Lee. Location recommendation for location-based social networks. In Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, pages 458--461. ACM, 2010.

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... role in the rev-olution of our daily life. The location-based social networks( (LBSN) have emerged and facilitated the users to share thecheck-in ... it extensively evaluates the model with tworeal-world data sets.KeywordsPOI Recommendation, Social network analysis1. INTRODUCTIONThe LBSNs, such as, the Facebook1, the Foursquare2, theGowalla3, ...
... Ye, P. Yin, and W. C. Lee. Locationrecommendation for location-based social networks. . InProceedings of the 18th SIGSPATIAL InternationalConference on Advances in ...

Title:
Sampling from Social Networks with Attributes

CCS:
Social networks

Keywords:
social networks

Abstract:
<p>Sampling from large networks represents a fundamental challenge for social network research. In this paper, we explore the sensitivity of different ... sampling, edge sampling, random walk sampling, and snowball sampling) on social networks with attributes. We consider the special case of networks (i) ... such networks. Experiments are conducted both on synthetic and empirical social networks. . Our results provide evidence that different network sampling techniques ... observed in the network. We conclude that uninformed sampling from social networks with attributes thus can significantly impair the ability of researchers ... of nodes and the visibility or invisibility of groups in social networks.

Primary CCS:
Social networks

References:
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Sampling from Social Networks with AttributesClaudia Wagner?GESIS & U. of Koblenz-Landauclaudia.wagner@gesis.orgPhilipp Singer?GESIS & U. ... of Koblenz-Landaumarkus.strohmaier@gesis.orgABSTRACTSampling from large networks represents a fundamental chal-lenge for social network research. In this paper, we explorethe sensitivity of different sampling ... (node sam-pling, edge sampling, random walk sampling, and snowballsampling) on social networks with attributes. We considerthe special case of networks (i) where ... groups in suchnetworks. Experiments are conducted both on synthetic andempirical social networks. . Our results provide evidence thatdifferent network sampling techniques are ... nodes and the visibility or invisibility of groupsin social networks.Keywords: social networks; ; sampling methods; samplingbias; homophily1. INTRODUCTIONSampling from large networks represents ... samplingbias; homophily1. INTRODUCTIONSampling from large networks represents a fundamentalproblem for social network research. In order to draw validconclusions from network samples, understanding ... of nodes and the visibility of groupsin synthetic and empirical social networks with (i) differentminority and majority group proportions, and (ii) variouslevels ...
... when ranking sampled nodes by their degree centrality.We construct synthetic social networks and vary the struc-tural mechanisms guiding the growth of the ... measures with respect to miss-ing data in two large online social networks and one randomgraph. They defined six different types of measurement ...
... linksbetween them. This technique of sampling is usually usedin online social networks such as Facebook or Twitter, inwhich retrieving information about the ...
... similar nodes) [21, 27] have been extensivelyobserved in many real-world social networks [7, 9, 23, 31]and information networks [22, 24]. Homophily implies ...
... We study publicly available data1 obtained fromthe most popular Slovakian social network ?Pokec? [29]. Weadded all friendship relations as undirected edges. The ... totally at random. From that we can assertthat the Pokec social network is moderately homophilic withrespect to the defined age groups. Figure ...
... of empirical social net-works (Pokec and Sexworker). In the homophilicPokec social network, , nodes with the highest degreetend to belong to the ... heterophily) is the driving force behindthe formation of edges in social networks with unbalancedattribute distributions, then the attribute and the degree ofnodes ...
... equally active and behave equally homophilic orheterophilic. In real world social networks,
... that the combination oftwo factors leads to sampling error in social networks withattributes: (i) group size differences and (ii) homophily.If unequal sized ... which groups will be over- or underestimated insamples drawn from social networks with unequally sizedgroups and various level of homophily. It is ... research presented in this paper motivates more researchinto sampling from social networks with attributes.Acknowledgements. We want to thank Robert West forvaluable discussions ... ACM, 2005.[10] L. C. Freeman. Centrality in social networks:Conceptual clarification. Social Networks, , 1(3):215?239,1979.[11] J. Galaskiewicz. Estimating point centrality usingdifferent network sampling ... 1(3):215?239,1979.[11] J. Galaskiewicz. Estimating point centrality usingdifferent network sampling techniques. Social Networks, ,13(4):347?386, Dec. 1991.[12] C. A. Hidalgo and C. Rodriguez-Sickert. The ...
... J.-Y. Li and M.-Y. Yeh. On sampling type distributionfrom heterogeneous social networks. . In Proceedings ofthe 15th Pacific-Asia Conference on Advances inKnowledge ... Smith-Lovin, and J. M. Cook. Birdsof a feather: Homophily in social networks. . AnnualReview of Sociology, 27(1):415?444, 2001.[22] F. Menczer. Growing and ... Druschel. You are who you know: inferring userprofiles in online social networks. . In Proceedings of thethird ACM international conference on Web ... S. Dodds, and M. E. J. Newman.Identity and search in social networks. . Science,296:1302?1305, 2002.[32] W. Webber, A. Moffat, and J. Zobel. ...

CCS:
Online social networks

Keywords:
social networks

Primary CCS:
Online social networks

References:
M. Gabielkov, A. Rao, and A. Legout. Studying social networks at scale: macroscopic anatomy of the Twitter social graph. In Proc. of ACM SIGMETRICS'14, Austin, TX, USA, Jun. 2014.
N. Hegde, L. Massoulié, and L. Viennot. Self-organizing flows in social networks. In Proc. of SIROCCO'13, pages 116--128, Ischia, Italy, Jul. 2013.
D. Kempe, J. M. Kleinberg, and É. Tardos. Maximizing the spread of influence through a social network. In Proc. of ACM SIGKDD KDD'03, Washington, DC, USA, Aug. 2003.
J. Ok, Y. Jin, J. Shin, and Y. Yi. On maximizing diffusion speed in social networks. In Proc. of ACM SIGMETRICS'14, Austin, TX, USA, Jun. 2014.

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... simple hypothesis in which thechannel, or in this case the social network, , that is used toshare information governs how its users ...
... 2012.[11] N. Hegde, L. Massoulie , and L. Viennot.Self-organizing flows in social networks. . In Proc. ofSIROCCO?13, pages 116?128, Ischia, Italy, Jul. 2013.[12] ...
... Jin, J. Shin, and Y. Yi. On maximizingdiffusion speed in social networks. . In Proc. of ACMSIGMETRICS?14, Austin, TX, USA, Jun. 2014.[24] ...

CCS:
Online social networks
Social networks

Keywords:
social network anlaysis

Abstract:
... this study. We model the evolution of friendship in the social network of MobiClique using observations of interactions among users. MobiClique is ...

Primary CCS:
Online social networks
Social networks

References:
Mujtaba Jawed, Mehmet Kaya, and Reda Alhajj. 2015. Time Frame Based Link Prediction in Directed Citation Networks. In Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2015 (ASONAM '15). ACM, New York, NY, USA, 1162--1168. DOI:https://doi.org/10.1145/2808797.2809323
A-K Pietil"ainen, E. Oliver, J. LeBrun, G. Varghese, and C. Diot. 2009. MobiClique: Middleware for Mobile Social Networking. In WOSN'09: Proceedings of ACM SIGCOMM Workshop on Online Social Networks.
Anna-Kaisa Pietiläinen, Earl Oliver, Jason LeBrun, George Varghese, and Christophe Diot. 2009. MobiClique: Middleware for Mobile Social Networking. In Proceedings of the 2Nd ACM Workshop on Online Social Networks (WOSN '09). ACM, New York, NY, USA, 49--54. DOI:https://doi.org/10.1145/1592665.1592678
Peng Wang, Baowen Xu, Yurong Wu, and Xiaoyu Zhou. 2015. Link prediction in social networks: the state-of-the-art. SCIENCE CHINA Information Sciences 58, 1 (2015), 1--38. http://dblp.uni-trier.de/db/journals/chinaf/chinaf58.html#WangXWZ15

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... to this study. We modelthe evolution of friendship in the social network of MobiClique usingobservations of interactions among users. MobiClique is a ... is necessary to utilise some interaction information.CCS CONCEPTS?Networks ! Online social networks; ; Online social networks; ;?Information systems! Social networks; ;KEYWORDSsocial network anlaysis, community detection, link predictionACM Reference format:JooYoung Lee, ... an observed network. Link prediction helps to understandthe evolution of social networks and has a power to complete thecurrent observed graphs. As ... observed graphs. As it involves many other areas of studyin social network analysis, such as ranking, link prediction hasmany important applications. Recommender ... such as common neighbours and preferentialattachment [7].Despite the fact that social networks are highly dynamic andvolatile, link prediction metrics have not paid ...
... link appearing then it become a problem of temporallink prediction. Social network with time can be organised as athird-order tensor or multidimensional ...
... In Proceedings of the 2015 IEEE/ACMInternational Conference on Advances in Social Networks Analysis and Mining2015 (ASONAM ?15). ACM, New York, NY, USA, ...
... G. Varghese, and C. Diot. 2009. Mobi-Clique: Middleware for Mobile Social Networking. . In WOSN?09: Proceedings ofACM SIGCOMM Workshop on Online Social Networks. .[4] Anna-Kaisa Pietila inen, Earl Oliver, Jason LeBrun, George Varghese, andChristophe ... Social Networking.In Proceedings of the 2Nd ACM Workshop on Online Social Networks (WOSN?09). ACM, New York, NY, USA, 49?54. DOI:https://doi.org/10.1145/1592665.1592678[5] Ben Taskar, ... Baowen Xu, Yurong Wu, and Xiaoyu Zhou. 2015. Link predictionin social networks: : the state-of-the-art. SCIENCE CHINA Information Sciences58, 1 (2015), 1?38. ...

Title:
What's Inside a Bow-Tie: Analyzing the Core of the Web and of Social Networks

CCS:
Social networks

Keywords:
social networks

Abstract:
<p>The explosive growth of the Web and of social networks motivates the need for analyzing the macroscopic structure of their ...

Primary CCS:
Social networks

References:
L. Backstrom, D. Huttenlocher, J. Kleinberg, and X. Lan. Group formation in large social networks: membership, growth, and evolution. In ACM SIGKDD, pages 44--54, 2006.
M. Fire, L. Tenenboim-Chekina, R. Puzis, O. Lesser, L. Rokach, and Y. Elovici. Computationally efficient link prediction in a variety of social networks. ACM Trans. on Intelligent Systems and Technology, 5(1):10, 2013.
M. Gabielkov, A. Rao, and A. Legout. Sampling online social networks: an experimental study of twitter. volume 44, pages 127--128, 2014.
M. Gabielkov, A. Rao, and A. Legout. Studying social networks at scale: macroscopic anatomy of the twitter social graph. ACM SIGMETRICS Performance Evaluation Review, 42(1):277--288, 2014.
H. Kwak, C. Lee, H. Park, and S. Moon. What is Twitter, a social network or a news media? In WWW, pages 591--600, 2010.
A. Mislove, H. S. Koppula, K. P. Gummadi, P. Druschel, and B. Bhattacharjee. Growth of the flickr social network. In WOSN, pages 25--30, 2008.

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... sizes andcharacteristics.CCS Concepts?Information systems ? Web mining; Social net-works;KeywordsWeb graphs; social networks; ; data mining.1. INTRODUCTIONThe explosive growth of the World Wide ... growth of the World Wide Web, in the pastdecade several social networks emerged and were adoptedquickly by a large portion of the ...
... [14] representthe friendships among the registered users of the homony-mous social networks. . Finally, Twitter-2009 [17] is the net-work of Twitter in ...
... the L2ECC set(which is the most connected part of each social network) ) isthe most ?fragile?, i.e., all their paths to vertices ...
... and Y. Elovici. Computationally efficientlink prediction in a variety of social networks. . ACMTrans. on Intelligent Systems and Technology, 5(1):10,2013.[8] M. Gabielkov, ... Technology, 5(1):10,2013.[8] M. Gabielkov, A. Rao, and A. Legout. Samplingonline social networks: : an experimental study oftwitter. volume 44, pages 127?128, 2014.[9] ... C. Lee, H. Park, and S. Moon. What isTwitter, a social network or a news media? In WWW,pages 591?600, 2010.[18] J. Leskovec ... K. P. Gummadi,P. Druschel, and B. Bhattacharjee. Growth of theflickr social network. . In WOSN, pages 25?30, 2008.[21] M. Najork and J. ...

CCS:
Social network security and privacy

Keywords:
Social networks

Abstract:
... now constantly sharing their images in various social media, from social networking sites to online communities, blogs, and content sharing sites. In ...

Primary CCS:
Social network security and privacy

References:
Joseph Bonneau, Jonathan Anderson, and Luke Church. 2009a. Privacy suites: Shared privacy for social networks. In Proceedings of the Symposium on Usable Privacy and Security.
Joseph Bonneau, Jonathan Anderson, and George Danezis. 2009b. Prying data out of a social network. In ASONAM: Proceedings of the International Conference on Advances in Social Network Analysis and Mining. 249--254.
Gorrell P. Cheek and Mohamed Shehab. 2012. Policy-by-example for online social networks. In 17th ACM Symposium on Access Control Models and Technologies (SACMAT’12). ACM, New York, NY, 23--32.
Lujun Fang and Kristen LeFevre. 2010. Privacy wizards for social networking sites. In Proceedings of the 19th International Conference on World Wide Web (WWW’10). ACM, New York, NY, 351--360.
J. He, W. W. Chu, and Z. Liu. 2006. Inferring privacy information from social networks. In Proceedings of the IEEE International Conference on Intelligence and Security Informatics.
Kelly Jackson Higgins. 2010. Social Networks For Patients Stir Privacy, Security Worries. Retrieved from http://www.darkreading.com/authentication/167901072/security/privacy/227500908/social-networks-for-patients-stir-privacy-security-worries.html.
Kun Liu and Evimaria Terzi. 2010. A framework for computing the privacy scores of users in online social networks. ACM Trans. Knowl. Discov. Data 5, Article 6 (Dec. 2010), 30 pages. Issue 1.
Michelle Madejski, Maritza Johnson, and Steven M. Bellovin. 2012. A study of privacy settings errors in an online social network. In Proceedings of the 2012 IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM Workshops). IEEE, 340--345.

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... are nowconstantly sharing their images in various social media, from social networking sites to online communities,blogs, and content sharing sites. In this ... tagsare available.CCS Concepts: ? Security and privacy?Software and application security; Social network se-curity and privacyAdditional Key Words and Phrases: Social networks, , image analysis, privacy, machine learningACM Reference Format:Anna Squicciarini, Cornelia ...
... features. We focus on image-specificfeatures only, rather than broader contextual social network dimensions or personalinformation about the image poster or his/her audience. ...
... of thisstudy. For instance, we do not consider any additional social networking or personalinformation about the photo owners and the site where ... information about a photo poster and his or her online social network activitiesmay not be available or easily accessible.Our learning models try ... complex case of an image to beplaced in an online social networking site, where users may choose from a fine-grainedset of options ...
... preferences, assuming such an image were tobe displayed on a social networking site. The question wording was as follows: ?Assumeyou have taken ...
... Anderson, and George Danezis. 2009b. Prying data out of a social network. ... . InASONAM: Proceedings of the International Conference on Advances in Social Network
... 151?153.Gorrell P. Cheek and Mohamed Shehab. 2012. Policy-by-example for online social networks. . In 17th ACMSymposium on Access Control Models and Technologies ... from http://portal.acm.org/citation.cfm?id=1888150.1888157Lujun Fang and Kristen LeFevre. 2010. Privacy wizards for social networking sites. In Proceedings of the19th International Conference on World Wide ... W. Chu, and Z. Liu. 2006. Inferring privacy information from social networks. . In Proceedings of theIEEE International Conference on Intelligence and ... in Wireless and Mobile Networks. ACM, 95?106.Kelly Jackson Higgins. 2010. Social Networks For Patients Stir Privacy, Security Worries. Retrieved fromhttp://www.darkreading.com/authentication/167901072/security/privacy/227500908/social-networks-for-patients-stir-privacy-security-worries.html.Simon Jones and ... Bellovin. 2012. A study of privacy settings errors in anonline social network. . In Proceedings of the 2012 IEEE International Conference on ...

CCS:
Social networking sites
Social networks

Keywords:
social networks

Abstract:
... and fourteen labeled datasets from many domains, including messages from social networks, , movie and product reviews, opinions and comments in news ...

Primary CCS:
Social networking sites
Social networks

Full Text:
... and fourteen labeled datasets from many domains, includ-ing messages from social networks, , movie and product reviews,opinions and comments in news articles. ... impact in thearea of sentiment classification research.CCS Concepts?Information systems ! Social networking sites; Social net-works;Permission to make digital or hard copies of ... machine learning; social networks1. INTRODUCTIONGiven the recent popularity of Online Social Networks (OSNs) andother Web 2.0 applications (e.g., micro-blogs), sentiment analysishas become ...
... labeled as positive or negative from many domains, includingmessages from social networks, , movie and product reviews, opin-9http://www.csie.ntu.edu.tw/~cjlin/libsvm/10http://www.cs.waikato.ac.nz/ml/weka/1160ions and comments in news ...
... methods and fourteen labeled datasets from many domains,including messages from social networks, , movie and product re-views, opinions and comments in news ...