Modeling Topics and Behavior of Microbloggers
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[1] Hong Cheng,et al. The dual-sparse topic model: mining focused topics and focused terms in short text , 2014, WWW.
[2] William W. Cohen,et al. From Topic Models to Semi-supervised Learning: Biasing Mixed-Membership Models to Exploit Topic-Indicative Features in Entity Clustering , 2013, ECML/PKDD.
[3] LimEe-Peng,et al. Modeling Topics and Behavior of Microbloggers , 2017 .
[4] Pengtao Xie,et al. Integrating Document Clustering and Topic Modeling , 2013, UAI.
[5] Hua Lu,et al. A unified model for stable and temporal topic detection from social media data , 2013, 2013 IEEE 29th International Conference on Data Engineering (ICDE).
[6] Mirella Lapata,et al. Tweet Recommendation with Graph Co-Ranking , 2012, ACL.
[7] Ramesh Nallapati,et al. Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora , 2009, EMNLP.
[8] Jacob Ratkiewicz,et al. Political Polarization on Twitter , 2011, ICWSM.
[9] William W. Cohen,et al. Regularization of Latent Variable Models to Obtain Sparsity , 2013, SDM.
[10] Nicola Barbieri,et al. Who to follow and why: link prediction with explanations , 2014, KDD.
[11] Aristides Gionis,et al. From chatter to headlines: harnessing the real-time web for personalized news recommendation , 2012, WSDM '12.
[12] Xiaoming Li,et al. Infer User Interests via Link Structure Regularization , 2014, TIST.
[13] Di Jiang,et al. Integrating Social and Auxiliary Semantics for Multifaceted Topic Modeling in Twitter , 2014, TOIT.
[14] Jun S. Liu,et al. The Collapsed Gibbs Sampler in Bayesian Computations with Applications to a Gene Regulation Problem , 1994 .
[15] Ting Wang,et al. Who will retweet me?: finding retweeters in twitter , 2013, SIGIR.
[16] Haewoon Kwak,et al. Fragile online relationship: a first look at unfollow dynamics in twitter , 2011, CHI.
[17] Zhiqiang Ma,et al. Tag-Latent Dirichlet Allocation: Understanding Hashtags and Their Relationships , 2013, 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).
[18] Duncan J. Watts,et al. Who says what to whom on twitter , 2011, WWW.
[19] Yutaka Matsuo,et al. Earthquake shakes Twitter users: real-time event detection by social sensors , 2010, WWW '10.
[20] Yong Yu,et al. Collaborative personalized tweet recommendation , 2012, SIGIR '12.
[21] Onkar Dabeer,et al. Timing Tweets to Increase Effectiveness of Information Campaigns , 2021, ICWSM.
[22] John Hannon,et al. Recommending twitter users to follow using content and collaborative filtering approaches , 2010, RecSys '10.
[23] Timothy W. Finin,et al. Why We Twitter: An Analysis of a Microblogging Community , 2009, WebKDD/SNA-KDD.
[24] Bo Pang,et al. The effect of wording on message propagation: Topic- and author-controlled natural experiments on Twitter , 2014, ACL.
[25] Noah A. Smith,et al. Predicting Response to Political Blog Posts with Topic Models , 2009, NAACL.
[26] Brian D. Davison,et al. Empirical study of topic modeling in Twitter , 2010, SOMA '10.
[27] Gregor Heinrich. Parameter estimation for text analysis , 2009 .
[28] Hongyuan Zha,et al. Probabilistic models for discovering e-communities , 2006, WWW '06.
[29] Jacob Ratkiewicz,et al. Predicting the Political Alignment of Twitter Users , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.
[30] Ee-Peng Lim,et al. On Modeling Community Behaviors and Sentiments in Microblogging , 2014, SDM.
[31] Bing He,et al. Community-based topic modeling for social tagging , 2010, CIKM.
[32] Junghoo Cho,et al. Topical semantics of twitter links , 2011, WSDM '11.
[33] Michael I. Jordan,et al. Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..
[34] Shuang-Hong Yang,et al. Large-scale high-precision topic modeling on twitter , 2014, KDD.
[35] Thomas L. Griffiths,et al. The Author-Topic Model for Authors and Documents , 2004, UAI.
[36] Isabell M. Welpe,et al. Divided They Tweet: The Network Structure of Political Microbloggers and Discussion Topics , 2011, ICWSM.
[37] Deborah A. Prentice,et al. Asymmetries in Attachments to Groups and to their Members: Distinguishing between Common-Identity and Common-Bond Groups , 1994 .
[38] Susan T. Dumais,et al. Characterizing Microblogs with Topic Models , 2010, ICWSM.
[39] Yan Liu,et al. Topic-link LDA: joint models of topic and author community , 2009, ICML '09.
[40] Brian D. Davison,et al. Structural link analysis and prediction in microblogs , 2011, CIKM '11.
[41] Jure Leskovec,et al. Community-Affiliation Graph Model for Overlapping Network Community Detection , 2012, 2012 IEEE 12th International Conference on Data Mining.
[42] Ying Ding,et al. Community detection: Topological vs. topical , 2011, J. Informetrics.
[43] Jiafeng Guo,et al. BTM: Topic Modeling over Short Texts , 2014, IEEE Transactions on Knowledge and Data Engineering.
[44] Ana-Maria Popescu,et al. Democrats, republicans and starbucks afficionados: user classification in twitter , 2011, KDD.
[45] Fei Wang,et al. ET-LDA: Joint Topic Modeling For Aligning, Analyzing and Sensemaking of Public Events and Their Twitter Feeds , 2012, ArXiv.
[46] Hai Yang,et al. ACM Transactions on Intelligent Systems and Technology - Special Section on Urban Computing , 2014 .
[47] Feida Zhu,et al. It Is Not Just What We Say, But How We Say Them: LDA-based Behavior-Topic Model , 2013, SDM.
[48] Scott Counts,et al. Predicting the Speed, Scale, and Range of Information Diffusion in Twitter , 2010, ICWSM.
[49] Andrew McCallum,et al. Topic and Role Discovery in Social Networks , 2005, IJCAI.
[50] J. Lafferty,et al. Mixed-membership models of scientific publications , 2004, Proceedings of the National Academy of Sciences of the United States of America.
[51] Xiaohui Yan,et al. A biterm topic model for short texts , 2013, WWW.
[52] Ramesh Nallapati,et al. Joint latent topic models for text and citations , 2008, KDD.
[53] Hongfei Yan,et al. Comparing Twitter and Traditional Media Using Topic Models , 2011, ECIR.
[54] Eric P. Xing,et al. Spatial compactness meets topical consistency: jointly modeling links and content for community detection , 2014, WSDM.
[55] Michele Zappavigna,et al. Ambient affiliation: A linguistic perspective on Twitter , 2011, New Media Soc..
[56] Yong Yu,et al. Diffusion-aware personalized social update recommendation , 2013, RecSys.
[57] Jure Leskovec,et al. Detecting cohesive and 2-mode communities indirected and undirected networks , 2014, WSDM.
[58] Timothy W. Finin,et al. Why we twitter: understanding microblogging usage and communities , 2007, WebKDD/SNA-KDD '07.
[59] Víctor M. Eguíluz,et al. Distinguishing topical and social groups based on common identity and bond theory , 2013, WSDM.
[60] Scott Sanner,et al. Improving LDA topic models for microblogs via tweet pooling and automatic labeling , 2013, SIGIR.
[61] Max Welling,et al. Distributed Algorithms for Topic Models , 2009, J. Mach. Learn. Res..
[62] M E J Newman,et al. Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.
[63] Yang Li,et al. Interpreting the Public Sentiment Variations on Twitter , 2014, IEEE Transactions on Knowledge and Data Engineering.
[64] Seunghak Lee,et al. More Effective Distributed ML via a Stale Synchronous Parallel Parameter Server , 2013, NIPS.
[65] Wray L. Buntine,et al. Topic Model : Extracting Product Opinions from Tweets by Leveraging Hashtags and Sentiment Lexicon , 2014 .
[66] Peng Li,et al. Joint topic modeling for event summarization across news and social media streams , 2012, CIKM.
[67] Lifeng Sun,et al. Who should share what?: item-level social influence prediction for users and posts ranking , 2011, SIGIR.
[68] Lei Yang,et al. We know what @you #tag: does the dual role affect hashtag adoption? , 2012, WWW.
[69] Edoardo M. Airoldi,et al. Mixed Membership Stochastic Blockmodels , 2007, NIPS.
[70] Krishna P. Gummadi,et al. The Emergence of Conventions in Online Social Networks , 2012, ICWSM.
[71] Jiawei Han,et al. Latent Community Topic Analysis: Integration of Community Discovery with Topic Modeling , 2012, TIST.
[72] Jing Jiang,et al. A Unified Model for Topics, Events and Users on Twitter , 2013, EMNLP.
[73] L. Venkata Subramaniam,et al. Using content and interactions for discovering communities in social networks , 2012, WWW.
[74] Jure Leskovec,et al. Community Detection in Networks with Node Attributes , 2013, 2013 IEEE 13th International Conference on Data Mining.
[75] Hosung Park,et al. What is Twitter, a social network or a news media? , 2010, WWW '10.
[76] Ed H. Chi,et al. Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network , 2010, 2010 IEEE Second International Conference on Social Computing.
[77] Kwan Hui Lim,et al. Following the follower: detecting communities with common interests on twitter , 2012, HT '12.
[78] Ee-Peng Lim,et al. Finding Bursty Topics from Microblogs , 2012, ACL.
[79] Mary Beth Rosson,et al. How and why people Twitter: the role that micro-blogging plays in informal communication at work , 2009, GROUP.
[80] Krishna P. Gummadi,et al. Predicting emerging social conventions in online social networks , 2012, CIKM.
[81] Antoine Boutet,et al. What's in Your Tweets? I Know Who You Supported in the UK 2010 General Election , 2012, ICWSM.
[82] Gao Cong,et al. A Tri-Role Topic Model for Domain-Specific Question Answering , 2015, AAAI.
[83] Matthew Michelson,et al. Tweet Disambiguate Entities Retrieve Folksonomy SubTree Step 1 : Discover Categories Generate Topic Profile from SubTrees Step 2 : Discover Profile Topic Profile : “ English Football ” “ World Cup ” , 2010 .
[84] Liangjie Hong,et al. A time-dependent topic model for multiple text streams , 2011, KDD.