Mining Social Media: Challenges and Opportunities

The opportunities presented by social networking have led to millions of users flocking to sites like Facebook, Twitter, and Foursquare. Even sites like Amazon have added the ability for users to interact with one another, though it seems tangential to the site's stated purpose. These social networking sites and social networking features generate massive amounts of data that can be used to draw conclusions about social behavior that could previously only be studied using relatively small sample sizes. This unlocks the ability to validate existing social theories, generate new models for how individuals and groups interact, and leverage the power of the crowd, among others.

[1]  Huan Liu,et al.  Exploring Social-Historical Ties on Location-Based Social Networks , 2012, ICWSM.

[2]  Chao Liu,et al.  Recommender systems with social regularization , 2011, WSDM '11.

[3]  Matthew Richardson,et al.  Mining knowledge-sharing sites for viral marketing , 2002, KDD.

[4]  Huan Liu,et al.  Promoting Coordination for Disaster Relief - From Crowdsourcing to Coordination , 2011, SBP.

[5]  Yue Lu,et al.  Exploiting social context for review quality prediction , 2010, WWW '10.

[6]  Huiji Gao,et al.  Harnessing the Crowdsourcing Power of Social Media for Disaster Relief , 2011, IEEE Intelligent Systems.

[7]  Alessandro Acquisti,et al.  Information revelation and privacy in online social networks , 2005, WPES '05.

[8]  Bobby Bhattacharjee,et al.  Persona: an online social network with user-defined privacy , 2009, SIGCOMM '09.

[9]  Huan Liu,et al.  mTrust: discerning multi-faceted trust in a connected world , 2012, WSDM '12.

[10]  Christos Faloutsos,et al.  Spotting Culprits in Epidemics: How Many and Which Ones? , 2012, 2012 IEEE 12th International Conference on Data Mining.

[11]  Reza Zafarani,et al.  Connecting Corresponding Identities across Communities , 2009, ICWSM.

[12]  Huan Liu,et al.  Exploiting vulnerability to secure user privacy on a social networking site , 2011, KDD.

[13]  Kristen LeFevre,et al.  Privacy wizards for social networking sites , 2010, WWW '10.

[14]  Huan Liu,et al.  Exploiting homophily effect for trust prediction , 2013, WSDM.

[15]  Mohammad Ali Abbasi,et al.  TweetTracker: An Analysis Tool for Humanitarian and Disaster Relief , 2011, ICWSM.

[16]  Yihong Gong,et al.  Combining content and link for classification using matrix factorization , 2007, SIGIR.

[17]  Devavrat Shah,et al.  Rumors in a Network: Who's the Culprit? , 2009, IEEE Transactions on Information Theory.

[18]  Eric Sun,et al.  Location 3 : How Users Share and Respond to Location-Based Data on Social Networking Sites , 2011 .

[19]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[20]  Fei Wang,et al.  ET-LDA: Joint Topic Modeling for Aligning Events and their Twitter Feedback , 2012, AAAI.

[21]  Claire Cardie,et al.  Annotating Expressions of Opinions and Emotions in Language , 2005, Lang. Resour. Evaluation.

[22]  Ravi Kumar,et al.  Influence and correlation in social networks , 2008, KDD.

[23]  Peng Zhang,et al.  Identifying Information Spreaders in Twitter Follower Networks , 2012 .

[24]  Bernhard Schölkopf,et al.  Structure and dynamics of information pathways in online media , 2012, WSDM.

[25]  Kristina Lerman,et al.  Information Contagion: An Empirical Study of the Spread of News on Digg and Twitter Social Networks , 2010, ICWSM.

[26]  Balachander Krishnamurthy,et al.  On the leakage of personally identifiable information via online social networks , 2009, CCRV.

[27]  J. Pitman,et al.  The two-parameter Poisson-Dirichlet distribution derived from a stable subordinator , 1997 .

[28]  Long Jiang,et al.  User-level sentiment analysis incorporating social networks , 2011, KDD.

[29]  Ramanathan V. Guha,et al.  Propagation of trust and distrust , 2004, WWW '04.

[30]  Jennifer Golbeck,et al.  Generating Predictive Movie Recommendations from Trust in Social Networks , 2006, iTrust.

[31]  Dimitrios Gunopulos,et al.  Finding effectors in social networks , 2010, KDD.

[32]  Reza Zafarani,et al.  Understanding User Migration Patterns in Social Media , 2011, AAAI.

[33]  Scott Counts,et al.  Predicting the Speed, Scale, and Range of Information Diffusion in Twitter , 2010, ICWSM.

[34]  J. Pitman.  Combinatorial Stochastic Processes , 2006 .

[35]  Danah Boyd,et al.  Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter , 2010, 2010 43rd Hawaii International Conference on System Sciences.

[36]  Adam Wierzbicki,et al.  Enriching Trust Prediction Model in Social Network with User Rating Similarity , 2009, 2009 International Conference on Computational Aspects of Social Networks.

[37]  Patrick Barwise,et al.  Permission-based mobile advertising , 2002 .

[38]  Ee-Peng Lim,et al.  To Trust or Not to Trust? Predicting Online Trusts Using Trust Antecedent Framework , 2009, 2009 Ninth IEEE International Conference on Data Mining.

[39]  Jaideep Srivastava,et al.  Predicting trusts among users of online communities: an epinions case study , 2008, EC '08.

[40]  Christopher Krügel,et al.  A Practical Attack to De-anonymize Social Network Users , 2010, 2010 IEEE Symposium on Security and Privacy.

[41]  Hugo Liu.  InterestMap : Harvesting Social Network Profiles for Recommendations , 2004 .

[42]  Huan Liu,et al.  Exploiting social relations for sentiment analysis in microblogging , 2013, WSDM.

[43]  R. Abelson.  Whatever Became of Consistency Theory? , 1983 .

[44]  Giovanni Comarela,et al.  Analyzing the Dynamic Evolution of Hashtags on Twitter: a Language-Based Approach , 2011 .

[45]  Lise Getoor,et al.  To join or not to join: the illusion of privacy in social networks with mixed public and private user profiles , 2009, WWW '09.