2012 Proceeding- Conference Chairs:
- Xiaoming Fu,
- Peter Gloor,
- Jie Tang
With the blessing of information technology, we are living in an increasingly networked world. People, information and other entities are connected via World Wide Web, email networks, instant messaging networks, mobile communication networks, online social networks, etc. These online networks grow fast and possess huge amount of recorded information, which presents great opportunities in understanding the science of these networks, and in developing new applications from these networks and for these networks. The increasingly networked society has fundamentally changed our way of thinking, individual behaviors and social activities. It is foreseen that the public health relating to epidemic diseases is greatly impacted by this emerging connectivity as they are by nature mediated by direct or indirect human interactions and mobility. However, new challenges have to be met --- the networks are huge and information is noisy, and they demand new methodologies in accessing and analyzing these networks, and in developing theories and applications for the networks.
To meet with these challenges, researchers from a wide range of academic fields, including theory and algorithms, data mining and machine learning, computer systems and networks, statistical physics and complex systems, sociology, social psychology, economics and managerial science, etc. are all actively studying various aspects concerning social and information networks.
However, we lack the proper opportunities for people from these diverse backgrounds to directly interact with each other. The diversity of approaches and methodologies to study various social networks has raised the need for an interdisciplinary effort to create the required expertise to address the fundamental open questions in this field.
This workshop is intended to present such an opportunity and serve as a forum to bring together people from various fields to exchange their latest research results and to sparkle new ideas and directions to properly understand these networks. It will be held on August 12, 2012, in conjunction with ACM KDD 2012, August 12-16, Beijing, China.
On the bursty evolution of online social networks
The high level of dynamics in today's online social networks (OSNs) creates new challenges for their infrastructures and providers. In particular, dynamics involving edge creation has direct implications on strategies for resource allocation, data ...
Ego-net digger: a new way to study ego networks in online social networks
The vast proliferation of Online Social Networks (OSN) is generating many new ways to interact and create social relationships with others. While substantial results have been obtained in anthropology literature describing the properties of human social ...
Predicting offline behaviors from online features: an ego-centric dynamical network approach
Investigating online social behaviors may help us to better understand and predict offline high risk behaviors in gay communities. But how can offline behaviors be predicted from online social networks? This article selects data from 26 online social ...
Reconstruction and analysis of Twitter conversation graphs
User interactions over social networks has been an emergent theme over the last several years. In contrast to previous work we focus on characterizing user communications patterns around an initial post, or conversation root. Specifically, we focus on ...
Forecasting social movements by web buzz analysis
Widespread Internet usage has led to the availability of a cacophony of fact, fiction and opinion composed by all elements of society; events such as the recent panic in Veracruz, Mexico over Twitter chatter of a violent attack on a school demonstrates ...
Sampling online social networks by random walk
This paper proposes to use simple random walk, a sampling method supported by most online social networks (OSN), to estimate a variety of properties of large OSNs. We show that due to the scale-free nature of OSNs the estimators derived from random walk ...
A case for automatic sharing over social networks
The proliferation of sharing on social networks, such as Facebook, Pinterest, Linkedin, and Foursquare, has closely connected people more than ever before. Our hypothesis is that, modulo privacy concerns, people are willing to share a lot more useful ...
Exploring decentralization dimensions of social networking services: adversaries and availability
Current online Social Networking Services (SNS) are organized around a single provider and while storage and functionality can be distributed, the control over the service belongs to one central entity. This structure raises privacy concerns over the ...
Strategies for spreading information from local to global in social complex networks, cases from a village in China
In this paper, we discuss the strategies adopted for spreading information from local to global areas in social complex networks by studying cases from a Village named Wukan in China. After identifying the most efficient spreaders [1], the structures ...
Complex network perspective on network dynamics: a study on investment network in VC industry in China
From the complex network perspective, using social network analysis methods, we aim to systematically conduct in-deep research on the emergence and evolution of the investment network in the venture capital industry in China to show the network dynamics ...
On the self-similarity of intertextual structures in Wikipedia
In recent years, Wikipedia and other wikis (e.g., Wiktionary) have been explored as knowledge resources in natural language processing (NLP) and related disciplines to overcome the bottleneck problem of knowledge acquisition (see [10] for an overview). ...
Correlating S&P 500 stocks with Twitter data
Twitter is a widely used online social media. One important characteristic of Twitter is its real-time nature. In this paper, we investigate whether the daily number of tweets that mention Standard & Poor 500 (S&P 500) stocks is correlated with S&P 500 ...
Topic evolution prediction of user generated contents considering enterprise generated contents
A large number of people use social media to generate content in a vast network of friends or strangers, and often with an unspecified number of users generating long lasting topic information which affects the normal operation of enterprises. The ...
Towards a socially aware home router
Effective security on home wireless networks remains an elusive goal. The most prevalent method uses a single pre-shared key to enforce access control, but the requirement for convenience often results in poorly chosen keys which rarely change over ...
