Twitter as Data
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[1] C. B. Colby. The weirdest people in the world , 1973 .
[2] Doug McAdam. Recruitment to High-Risk Activism: The Case of Freedom Summer , 1986, American Journal of Sociology.
[3] G. Marwell,et al. Social Networks and Collective Action: A Theory of the Critical Mass. III , 1988, American Journal of Sociology.
[4] G. Marwell,et al. A Theory of the Critical Mass , 1991 .
[5] Robin I. M. Dunbar. Neocortex size as a constraint on group size in primates , 1992 .
[6] R. Tibshirani,et al. An introduction to the bootstrap , 1993 .
[7] K. Opp,et al. Dissident Groups, Personal Networks, and Spontaneous Cooperation: The East German Revolution of 1989 , 1993 .
[8] W. B. Cavnar,et al. N-gram-based text categorization , 1994 .
[9] Robin I. M. Dunbar. Neocortex size and group size in primates: a test of the hypothesis , 1995 .
[10] Robert Huckfeldt,et al. Social Capital, Social Networks, and Political Participation , 1998 .
[11] Hinrich Schütze,et al. Book Reviews: Foundations of Statistical Natural Language Processing , 1999, CL.
[12] Patrick Ball,et al. EXPLORING THE IMPLICATIONS OF SOURCE SELECTION IN THE CASE OF GUATEMALAN STATE TERROR, 1977-1995 , 2002 .
[13] R. Huckfeldt,et al. The Social Calculus of Voting: Interpersonal, Media, and Organizational Influences on Presidential Choices , 2002, American Political Science Review.
[14] Lada A. Adamic,et al. The political blogosphere and the 2004 U.S. election: divided they blog , 2005, LinkKDD '05.
[15] Didier Sornette,et al. Discrete hierarchical organization of social group sizes , 2004, Proceedings of the Royal Society B: Biological Sciences.
[16] Marco Gonzalez,et al. Author's Personal Copy Social Networks Tastes, Ties, and Time: a New Social Network Dataset Using Facebook.com , 2022 .
[17] David W. Nickerson. Is Voting Contagious? Evidence from Two Field Experiments , 2008, American Political Science Review.
[18] S. Herring,et al. Beyond Microblogging: Conversation and Collaboration via Twitter , 2009, 2009 42nd Hawaii International Conference on System Sciences.
[19] A. Pentland,et al. Computational Social Science , 2009, Science.
[20] A. Pentland,et al. Life in the network: The coming age of computational social science: Science , 2009 .
[21] Bernardo A. Huberman,et al. Predicting the Future with Social Media , 2010, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology.
[22] S. Levinson,et al. WEIRD languages have misled us, too , 2010, Behavioral and Brain Sciences.
[23] Eni Mustafaraj,et al. From Obscurity to Prominence in Minutes: Political Speech and Real-Time Search , 2010 .
[24] Leysia Palen,et al. Pass it on?: Retweeting in mass emergency , 2010, ISCRAM.
[25] Isabell M. Welpe,et al. Predicting Elections with Twitter: What 140 Characters Reveal about Political Sentiment , 2010, ICWSM.
[26] Yutaka Matsuo,et al. Earthquake shakes Twitter users: real-time event detection by social sensors , 2010, WWW '10.
[27] Leysia Palen,et al. Microblogging during two natural hazards events: what twitter may contribute to situational awareness , 2010, CHI.
[28] Nils B. Weidmann,et al. Predicting Conflict in Space and Time , 2010 .
[29] Danah Boyd,et al. Tweet, Tweet, Retweet: Conversational Aspects of Retweeting on Twitter , 2010, 2010 43rd Hawaii International Conference on System Sciences.
[30] Robin I. M. Dunbar. Constraints on the evolution of social institutions and their implications for information flow , 2010, Journal of Institutional Economics.
[31] Danah Boyd,et al. Tweeting from the Town Square: Measuring Geographic Local Networks , 2010, ICWSM.
[32] Minas Gjoka,et al. Walking in Facebook: A Case Study of Unbiased Sampling of OSNs , 2010, 2010 Proceedings IEEE INFOCOM.
[33] Hosung Park,et al. What is Twitter, a social network or a news media? , 2010, WWW '10.
[34] 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.
[35] Hakan Ferhatosmanoglu,et al. Short text classification in twitter to improve information filtering , 2010, SIGIR.
[36] Kyumin Lee,et al. You are where you tweet: a content-based approach to geo-locating twitter users , 2010, CIKM.
[37] Sune Lehmann,et al. Understanding the Demographics of Twitter Users , 2011, ICWSM.
[38] Christian Borgs,et al. We know who you followed last summer: inferring social link creation times in twitter , 2011, WWW.
[39] Christopher M. Danforth,et al. Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter , 2011, PloS one.
[40] T. Zeitzoff. Using Social Media to Measure Conflict Dynamics , 2011 .
[41] Kelly Bergstrom,et al. "Don't feed the troll": Shutting down debate about community expectations on Reddit.com , 2011, First Monday.
[42] Alexander Halavais. Social science: Open up online research , 2011, Nature.
[43] Barbara Poblete,et al. Do all birds tweet the same?: characterizing twitter around the world , 2011, CIKM '11.
[44] Joshua Evan Blumenstock. Using mobile phone data to measure the ties between nations , 2011, iConference '11.
[45] Timothy Baldwin,et al. Lexical Normalisation of Short Text Messages: Makn Sens a #twitter , 2011, ACL.
[46] Salvatore Catanese,et al. Crawling Facebook for social network analysis purposes , 2011, WIMS '11.
[47] Chen Huang,et al. Microblogging after a major disaster in China: a case study of the 2010 Yushu earthquake , 2011, CSCW.
[48] Ed H. Chi,et al. Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles , 2011, CHI.
[49] Babak Rahimi. The Agonistic Social Media: Cyberspace in the Formation of Dissent and Consolidation of State Power in Postelection Iran , 2011 .
[50] E. Doheny. United States Agency for International Development , 2011 .
[51] Jacob Ratkiewicz,et al. Detecting and Tracking Political Abuse in Social Media , 2011, ICWSM.
[52] T. Zeitzoff,et al. Using Social Media to Measure Conflict Dynamics : An Application to the 2008 – 2009 Gaza Conflict , 2011 .
[53] Jacob Ratkiewicz,et al. Political Polarization on Twitter , 2011, ICWSM.
[54] Alessandro Vespignani,et al. Modeling Users' Activity on Twitter Networks: Validation of Dunbar's Number , 2011, PloS one.
[55] Yamir Moreno,et al. The Dynamics of Protest Recruitment through an Online Network , 2011, Scientific reports.
[56] Scott A. Golder,et al. Diurnal and Seasonal Mood Vary with Work, Sleep, and Daylength Across Diverse Cultures , 2011 .
[57] Johan Bollen,et al. Twitter mood predicts the stock market , 2010, J. Comput. Sci..
[58] Lars Backstrom,et al. The Anatomy of the Facebook Social Graph , 2011, ArXiv.
[59] D. Boyd,et al. The Arab Spring| The Revolutions Were Tweeted: Information Flows during the 2011 Tunisian and Egyptian Revolutions , 2011 .
[60] Filippo Menczer,et al. Partisan asymmetries in online political activity , 2012, EPJ Data Science.
[61] Cameron Marlow,et al. A 61-million-person experiment in social influence and political mobilization , 2012, Nature.
[62] Ning Wang,et al. Assessing the Bias in Communication Networks Sampled from Twitter , 2012, ArXiv.
[63] Daniel Gayo-Avello,et al. A Meta-Analysis of State-of-the-Art Electoral Prediction From Twitter Data , 2012, ArXiv.
[64] Emilio Ferrara,et al. A large-scale community structure analysis in Facebook , 2011, EPJ Data Science.
[65] Krishna P. Gummadi,et al. Geographic Dissection of the Twitter Network , 2012, ICWSM.
[66] Wendy Liu,et al. Homophily and Latent Attribute Inference: Inferring Latent Attributes of Twitter Users from Neighbors , 2012, ICWSM.
[67] Joshua E. Blumenstock,et al. Information Technology for Development Inferring Patterns of Internal Migration from Mobile Phone Call Records: Evidence from Rwanda Inferring Patterns of Internal Migration from Mobile Phone Call Records: Evidence from Rwanda , 2022 .
[68] H. Farrell. The Consequences of the Internet for Politics , 2012 .
[69] Yamir Moreno,et al. Broadcasters and Hidden Influentials in Online Protest Diffusion , 2012, ArXiv.
[70] Bernardo A. Huberman,et al. Artificial Inflation: The Real Story of Trends and Trend-Setters in Sina Weibo , 2012, 2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing.
[71] Stephanie M. Reich,et al. Friending, IMing, and hanging out face-to-face: overlap in adolescents' online and offline social networks. , 2012, Developmental psychology.
[72] Lindsay T. Graham,et al. A Review of Facebook Research in the Social Sciences , 2012, Perspectives on psychological science : a journal of the Association for Psychological Science.
[73] Yong Yu,et al. A comparative study of users' microblogging behavior on sina weibo and twitter , 2012, UMAP.
[74] Jonathan Hassid. Safety Valve or Pressure Cooker? Blogs in Chinese Political Life , 2012 .
[75] Zeynep Tufekci,et al. Social Media and the Decision to Participate in Political Protest: Observations From Tahrir Square , 2012 .
[76] Deen Freelon,et al. Introduction to the Special Issue on New Media and Social Unrest , 2013 .
[77] Nils W. Metternich,et al. Antigovernment networks in civil conflicts : how network structures affect conflictual behavior , 2013 .
[78] Bethan Jones,et al. From Usenet to Tumblr: the changing role of social media , 2013 .
[79] Lev Manovich,et al. Zooming into an Instagram City: Reading the local through social media , 2013, First Monday.
[80] Huan Liu,et al. Is the Sample Good Enough? Comparing Data from Twitter's Streaming API with Twitter's Firehose , 2013, ICWSM.
[81] Xiaokang Yang,et al. Analysis and identification of spamming behaviors in Sina Weibo microblog , 2013, SNAKDD '13.
[82] O. J. Reuter,et al. Online Social Media and Political Awareness in Authoritarian Regimes , 2013, British Journal of Political Science.
[83] Jure Leskovec,et al. What's in a Name? Understanding the Interplay between Titles, Content, and Communities in Social Media , 2013, ICWSM.
[84] Jussara M. Almeida,et al. A Picture of Instagram is Worth More Than a Thousand Words: Workload Characterization and Application , 2013, 2013 IEEE International Conference on Distributed Computing in Sensor Systems.
[85] Christopher M. Danforth,et al. Happiness and the Patterns of Life: A Study of Geolocated Tweets , 2013, Scientific Reports.
[86] A. Stefanidis,et al. Harvesting ambient geospatial information from social media feeds , 2011, GeoJournal.
[87] Eric Gilbert,et al. Widespread underprovision on Reddit , 2013, CSCW.
[88] Alessandro Vespignani,et al. The Twitter of Babel: Mapping World Languages through Microblogging Platforms , 2012, PloS one.
[89] Matthew A. Shapiro,et al. What's congress doing on twitter? , 2013, CSCW.
[90] Erika Check Hayden,et al. Guidance issued for US Internet research , 2013, Nature.
[91] Filippo Menczer,et al. The Geospatial Characteristics of a Social Movement Communication Network , 2013, PloS one.
[92] Scott A. Hale,et al. Where in the World Are You? Geolocation and Language Identification in Twitter* , 2013, ArXiv.
[93] Justin Grimmer,et al. Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts , 2013, Political Analysis.
[94] Dong Nguyen,et al. "How Old Do You Think I Am?" A Study of Language and Age in Twitter , 2013, ICWSM.
[95] Hongyan Liu,et al. Detecting Event Rumors on Sina Weibo Automatically , 2013, APWeb.
[96] Venkata Rama Kiran Garimella,et al. Secular vs. Islamist polarization in Egypt on Twitter , 2013, 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013).
[97] Keiji Yanai,et al. Visual event mining from geo-tweet photos , 2013, 2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW).
[98] Shaowen Wang,et al. Mapping the global Twitter heartbeat: The geography of Twitter , 2013, First Monday.
[99] Yan Liu,et al. What is Tumblr: a statistical overview and comparison , 2014, SKDD.
[100] Pablo Barberá. How Social Media Reduces Mass Political Polarization. Evidence from Germany, Spain, and the U.S. , 2014 .
[101] Zhigang Cao,et al. Analyzing user behavior of the micro-blogging website Sina Weibo during hot social events , 2013, 1304.3898.
[102] George Valkanas,et al. Mining Twitter Data with Resource Constraints , 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).
[103] Jiejun Xu,et al. Civil Unrest Prediction: A Tumblr-Based Exploration , 2014, SBP.
[104] Andreas Jungherr. Twitter in Politics: A Comprehensive Literature Review , 2014 .
[105] Nils B. Weidmann,et al. Using machine-coded event data for the micro-level study of political violence , 2014 .
[106] Susan C. Herring,et al. Multimodal communication on tumblr: "i have so many feels!" , 2014, WebSci '14.
[107] C. Bail. The cultural environment: measuring culture with big data , 2014, Theory and Society.
[108] Daron Acemoglu,et al. The Power of the Street: Evidence from Egypt&Apos;S Arab Spring , 2014 .
[109] Aravind Srinivasan,et al. 'Beating the news' with EMBERS: forecasting civil unrest using open source indicators , 2014, KDD.
[110] Michael Gamon,et al. Online And Social Media Data As A Flawed Continuous Panel Survey , 2014 .
[111] Nathan Kallus,et al. Predicting crowd behavior with big public data , 2014, WWW.
[112] Scott A. Golder,et al. Digital Footprints: Opportunities and Challenges for Online Social Research , 2014 .
[113] Heather K. Evans,et al. Twitter Style: An Analysis of How House Candidates Used Twitter in Their 2012 Campaigns , 2014, PS: Political Science & Politics.
[114] Subbarao Kambhampati,et al. What We Instagram: A First Analysis of Instagram Photo Content and User Types , 2014, ICWSM.
[115] Shankar Kalyanaraman,et al. Violence and Cell Phone Communication: Behavior and Prediction in Cote D’Ivoire , 2014 .
[116] Jeffrey T. Hancock,et al. Experimental evidence of massive-scale emotional contagion through social networks , 2014, Proceedings of the National Academy of Sciences.
[117] David G. Rand,et al. Structural Topic Models for Open‐Ended Survey Responses , 2014, American Journal of Political Science.
[118] Zeynep Tufekci,et al. Big Questions for Social Media Big Data: Representativeness, Validity and Other Methodological Pitfalls , 2014, ICWSM.
[119] Matthew S. Gerber,et al. Predicting crime using Twitter and kernel density estimation , 2014, Decis. Support Syst..
[120] Manuel Cebrián,et al. Using Friends as Sensors to Detect Global-Scale Contagious Outbreaks , 2012, PloS one.
[121] Andrea Tagarelli,et al. Online popularity and topical interests through the lens of instagram , 2014, HT.
[122] Margaret E. Roberts,et al. Reverse-engineering censorship in China: Randomized experimentation and participant observation , 2014, Science.
[123] Tomaso Aste,et al. When Can Social Media Lead Financial Markets? , 2014, Scientific Reports.
[124] Philip N. Howard,et al. Political Bots and the Manipulation of Public Opinion in Venezuela , 2015, ArXiv.
[125] Pablo Barberá. Birds of the Same Feather Tweet Together: Bayesian Ideal Point Estimation Using Twitter Data , 2015, Political Analysis.
[126] Dan Mercea,et al. Tents, Tweets, and Events: The Interplay Between Ongoing Protests and Social Media , 2015 .
[127] M. Shigematsu,et al. Using Social Media for Actionable Disease Surveillance and Outbreak Management: A Systematic Literature Review , 2015, PloS one.
[128] Michael Zimmer. The Twitter Archive at the Library of Congress: Challenges for information practice and information policy , 2015, First Monday.
[129] Jürgen Pfeffer,et al. Population Bias in Geotagged Tweets , 2015, Proceedings of the International AAAI Conference on Web and Social Media.
[130] T. Zeitzoff,et al. Using social media to measure foreign policy dynamics : An empirical analysis of the Iranian – Israeli confrontation ( 2012 – 13 ) , 2015 .
[131] Gabriel Cadamuro,et al. Predicting poverty and wealth from mobile phone metadata , 2015, Science.
[132] D. Watts,et al. Dissecting the Spirit of Gezi: Influence vs. Selection in the Occupy Gezi Movement. , 2015 .
[133] Margaret E. Roberts,et al. Computer-Assisted Text Analysis for Comparative Politics , 2015, Political Analysis.
[134] Alessandro Vespignani,et al. Online social networks and offline protest , 2015, EPJ Data Science.
[135] Dongjin Song,et al. High resolution population estimates from telecommunications data , 2015, EPJ Data Science.
[136] Lev Manovich,et al. Predicting social trends from non-photographic images on Twitter , 2015, 2015 IEEE International Conference on Big Data (Big Data).
[137] Joshua A. Tucker,et al. Is Online Political Communication More Than an Echo Chamber? , 2022 .
[138] Nils B. Weidmann. On the Accuracy of Media-based Conflict Event Data , 2015 .
[139] Manuel Cebrián,et al. Social Media Fingerprints of Unemployment , 2014, PloS one.
[140] M. Williams,et al. Who Tweets? Deriving the Demographic Characteristics of Age, Occupation and Social Class from Twitter User Meta-Data , 2015, PloS one.
[141] Marco Conti,et al. The structure of online social networks mirrors those in the offline world , 2015, Soc. Networks.
[142] Lada A. Adamic,et al. Exposure to ideologically diverse news and opinion on Facebook , 2015, Science.
[143] T. Zeitzoff,et al. Using social media to measure foreign policy dynamics , 2015 .
[144] O. Onuch. EuroMaidan Protests in Ukraine: Social Media Versus Social Networks , 2015 .
[145] Walid Magdy,et al. Content and Network Dynamics Behind Egyptian Political Polarization on Twitter , 2014, CSCW.
[146] Luke S Sloan,et al. Who Tweets with Their Location? Understanding the Relationship between Demographic Characteristics and the Use of Geoservices and Geotagging on Twitter , 2015, PloS one.
[147] Joshua A. Tucker,et al. The Critical Periphery in the Growth of Social Protests , 2015, PloS one.
[148] Shiry Ginosar,et al. Photographic home styles in Congress: a computer vision approach , 2016, ArXiv.
[149] What is Political Participation , 2016 .
[150] Jonathan Ronen,et al. Social Networks and Protest Participation: Evidence from 93 Million Twitter Users , 2016 .
[151] A. Coppock,et al. When Treatments are Tweets: A Network Mobilization Experiment over Twitter , 2016 .
[152] Filippo Menczer,et al. BotOrNot: A System to Evaluate Social Bots , 2016, WWW.
[153] Zachary C. Steinert-Threlkeld,et al. Structure, Agency, Hegemony, and Action: Ukrainian Nationalism in East Ukraine , 2016 .
[154] Emilio Ferrara,et al. Social Bots Distort the 2016 US Presidential Election Online Discussion , 2016, First Monday.
[155] Maeve Duggan,et al. Social Media Update 2016 , 2016 .
[156] Richard Bonneau,et al. Big Data, Social Media, and Protest: Foundations for a Research Agenda , 2016, Computational Social Science.
[157] Joann Cattlin,et al. Simple online privacy for Australia , 2016, First Monday.
[158] J. Pfeffer,et al. A Macroscopic Analysis of News Content in Twitter , 2016 .
[159] Filippo Menczer,et al. The rise of social bots , 2014, Commun. ACM.
[160] Michael Gamon,et al. Online and Social Media Data As an Imperfect Continuous Panel Survey , 2016, PloS one.
[161] Samuel C. Woolley,et al. Automating power: Social bot interference in global politics , 2016, First Monday.
[162] Zachary C. Steinert-Threlkeld. Spontaneous Collective Action: Peripheral Mobilization During the Arab Spring , 2017, American Political Science Review.
[163] Margaret E. Roberts,et al. How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument , 2017, American Political Science Review.
[164] Zachary C. Steinert-Threlkeld. Longitudinal Network Centrality Using Incomplete Data , 2017, Political Analysis.
[165] Kevin Munger. Tweetment Effects on the Tweeted: Experimentally Reducing Racist Harassment , 2017 .
[166] Michael F. Goodchild,et al. Location-Based Services , 2018, Encyclopedia of Social Network Analysis and Mining. 2nd Ed..
[167] T. Zeitzoff,et al. Does Social Media Influence Conflict? Evidence from the 2012 Gaza Conflict , 2018 .
[168] Nicholas Eubank. Social Networks and the Political Salience of Ethnicity , 2019, Quarterly Journal of Political Science.