2013 Proceeding- General Chair:
- Muthu Muthukrishnan,
- Program Chairs:
- Amr El Abbadi,
- Balachander Krishnamurthy
Welcome to the first ACM Conference on Online Social Networks - COSN! We are very excited that COSN is taking place in Boston MA, on October 7 and 8, 2013. We are proud to present its proceedings. The conference starts with a keynote by Jaron Lanier, a scientist, musician, visual artist and author of "Who owns the Future", followed by 22 technical paper presentations.
As mentioned in the Steering Committee Chair's welcome message, COSN was formed by merging six different workshops and the submissions reflected that. We received 138 submissions from over 20 countries, roughly as many submissions as the six workshops combined! We had solicited full papers (up to 12 pages) describing original research in detail and short papers (6 pages) conveying promising work and high-level vision. We received 103 long submissions and 35 short submissions. Both the high number of submissions and especially the number of long submissions clearly show that the community needs COSN and the time is ripe for COSN. The final program includes 4 short papers and 18 long papers. The acceptance rate is 16% (22 of 138 candidates) overall, 17.5% (18 of 103 candidates) for long papers and 11.5% (4 out of 35 candidates) for short papers. These rates reflect the high quality that we sought. The program reflects the broad coverage that was envisioned in merging the workshops: including papers in understanding social behavior, privacy, social graphs, trending topics, advertisements, applications, and crowdsourcing.
The PC consisted of 24 members (including the two of us). In addition, we sought and received additional reviews for some papers from over 20 external reviewers. The reviewing period was just four weeks, due to the exigencies of a first time conference with specific time constraints. Five papers were filtered out for being out of scope and a small handful was rejected based on two strongly negative reviews. Each of the remaining papers received at least three reviews with several receiving 4 or 5. In all, we had over 440 reviews within four weeks---showing the diligence of the PC and external reviewers. The reviewing process included extensive on-line discussions.
On July 29, we held a face-to-face day long program committee meeting at Columbia University. 50 papers with positive reviews and consensus after the on-line discussion were discussed extensively. The face to face PC meeting was beneficial as it brought various representatives of the OSN community together, some of whom were meeting others for the first time. The accepted papers cover a diversity of topics spanning the various research areas of the OSN community. The papers also reflect the globalization of the community, covering papers with author affiliations from 13 countries: Australia, Austria, Brazil, China, Germany, India, Italy, Japan, Korea, Spain, Switzerland, United Kingdom, and United States. Virtually all but one of the accepted papers were shepherded to ensure compliance with specific outcomes from the reviews and the discussions.
Proceeding Downloads
COSN'13 keynote speaker (Jaron Lanier biography)
A Renaissance Man for the 21st century, Jaron Lanier is a computer scientist, composer, artist, and author who writes on numerous topics, including high-technology business, the social impact of technology, the philosophy of consciousness and ...
We know how you live: exploring the spectrum of urban lifestyles
An incisive understanding of human lifestyles is not only essential to many scientific disciplines, but also has a profound business impact for targeted marketing. In this paper, we present LifeSpec, a computational framework for exploring and ...
Dynamics of personal social relationships in online social networks: a study on twitter
The growing popularity of Online Social Networks (OSN) is generating a large amount of communication records that can be easily accessed and analysed to study human social behaviour. This represents a unique opportunity to understand properties of ...
Comparing and combining sentiment analysis methods
Several messages express opinions about events, products, and services, political views or even their author's emotional state and mood. Sentiment analysis has been used in several applications including analysis of the repercussions of events in social ...
Social resilience in online communities: the autopsy of friendster
We empirically analyze five online communities: Friendster, Livejournal, Facebook, Orkut, and Myspace, to study how social networks decline. We define social resilience as the ability of a community to withstand changes. We do not argue about the cause ...
Social affinity filtering: recommendation through fine-grained analysis of user interactions and activities
Content recommendation in social networks poses the complex problem of learning user preferences from a rich and complex set of interactions (e.g., likes, comments and tags for posts, photos and videos) and activities (e.g., favourites, group ...
On the precision of social and information networks
The diffusion of information on online social and information networks has been a popular topic of study in recent years, but attention has typically focused on speed of dissemination and recall (i.e. the fraction of users getting a piece of information)...
Cryptagram: photo privacy for online social media
While Online Social Networks (OSNs) enable users to share photos easily, they also expose users to several privacy threats from both the OSNs and external entities. The current privacy controls on OSNs are far from adequate, resulting in inappropriate ...
Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo
In recent years, social media has risen to prominence in China, with sites like Sina Weibo and Renren each boasting hundreds of millions of users. Social media in China plays a profound role as a platform for breaking news and political commentary that ...
Call me maybe: understanding nature and risks of sharing mobile numbers on online social networks
Little research explores the activity of sharing mobile numbers on OSNs, in particular via public posts. In this work, we understand the characteristics and risks of mobile numbers shared on OSNs either via profile or public posts and focus on Indian ...
Hierarchical community decomposition via oblivious routing techniques
The detection of communities in real-world large-scale complex networks is a fundamental step in many applications, such as describing community structure and predicting the dissemination of information. Unfortunately, community detection is a ...
On the performance of percolation graph matching
Graph matching is a generalization of the classic graph isomorphism problem. By using only their structures a graph-matching algorithm finds a map between the vertex sets of two similar graphs. This has applications in the de-anonymization of social and ...
Scalable similarity estimation in social networks: closeness, node labels, and random edge lengths
Similarity estimation between nodes based on structural properties of graphs is a basic building block used in the analysis of massive networks for diverse purposes such as link prediction, product recommendations, advertisement, collaborative filtering,...
Appinspect: large-scale evaluation of social networking apps
Third-party apps for social networking sites have emerged as a popular feature for online social networks, and are used by millions of users every day. In exchange for additional features, users grant third parties access to their personal data. However,...
Ads by whom? ads about what?: exploring user influence and contents in social advertising
Despite the growing interest in using online social networking services (OSNS) for advertising, little is understood about what contributes to the social advertising performance. In this research, we pose following questions: How many clicks do social ...
Are trending topics useful for marketing?: visibility of trending topics vs traditional advertisement
Trending Topics seem to be a powerful tool to be used in marketing and advertisement contexts, however there is not any rigorous analysis that demonstrates this. In this paper we present a first effort in this direction. We use a dataset including more ...
Launch hard or go home!: predicting the success of kickstarter campaigns
Crowdfunding websites such as Kickstarter are becoming increasingly popular, allowing project creators to raise hundreds of millions of dollars every year. However, only one out of two Kickstarter campaigns reaches its funding goal and is successful. It ...
Crowd crawling: towards collaborative data collection for large-scale online social networks
The emerging research for online social networks (OSNs) requires a huge amount of data. However, OSN sites typically enforce restrictions for data crawling, such as request rate limiting on a per-IP basis. It becomes challenging for an individual ...
Building confederated web-based services with Priv.io
With the increasing popularity of Web-based services, users today have access to a broad range of free sites, including social networking, microblogging, and content sharing sites. In order to offer a service for free, service providers typically ...
Fit or unfit: analysis and prediction of 'closed questions' on stack overflow
Stack Overflow is widely regarded as the most popular Community driven Question Answering (CQA) website for programmers. Questions posted on Stack Overflow which are not related to programming topics, are marked as `closed' by experienced users and ...
Traveling trends: social butterflies or frequent fliers?
Trending topics are the online conversations that grab collective attention on social media. They are continually changing and often reflect exogenous events that happen in the real world. Trends are localized in space and time as they are driven by ...
Landmark-based user location inference in social media
Location profiles of user accounts in social media can be utilized for various applications, such as disaster warnings and location-aware recommendations. In this paper, we propose a scheme to infer users' home locations in social media. A large portion ...
Inferring user interests from tweet times
We propose and demonstrate the feasibility of a probabilistic framework for mining user interests from their tweet times alone, by exploiting the known timing of external events associated with these interests. This approach allows for making inferences ...