Jumping over the network threshold of information diffusion: testing the threshold hypothesis of social influence
暂无分享,去创建一个
[1] Mark S. Granovetter. Threshold Models of Collective Behavior , 1978, American Journal of Sociology.
[2] Fang Wu,et al. Novelty and collective attention , 2007, Proceedings of the National Academy of Sciences.
[3] Jie Tang,et al. Mining structural hole spanners through information diffusion in social networks , 2013, WWW.
[4] Jun Tian,et al. Characterizing information propagation patterns in emergencies: A case study with Yiliang Earthquake , 2018, Int. J. Inf. Manag..
[5] Tarleton Gillespie,et al. The politics of ‘platforms’ , 2010, New Media Soc..
[6] Lada A. Adamic,et al. The role of social networks in information diffusion , 2012, WWW.
[7] Yamir Moreno,et al. Cascading behaviour in complex socio-technical networks , 2013, J. Complex Networks.
[8] Dongwon Lee,et al. The Impact of Message Characteristics on Online Viral Diffusion in Online Social Media Services : The Case of Twitter , 2011 .
[9] Joseph Waksberg,et al. Sampling Methods for Random Digit Dialing , 1978 .
[10] Eva Lahuerta-Otero,et al. Retweet or like? That is the question , 2018, Online Inf. Rev..
[11] Hai Liang. Broadcast Versus Viral Spreading: The Structure of Diffusion Cascades and Selective Sharing on Social Media , 2018 .
[12] Jonathan J. H. Zhu,et al. A Random Digit Search (RDS) Method for Sampling of Blogs and Other User-Generated Content , 2011 .
[13] Matthew J. Salganik,et al. Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market , 2006, Science.
[14] Mark S. Granovetter. The Strength of Weak Ties , 1973, American Journal of Sociology.
[15] Jari Saramäki,et al. Small But Slow World: How Network Topology and Burstiness Slow Down Spreading , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.
[16] Gerardo Iñiguez,et al. Threshold driven contagion on weighted networks , 2017, Scientific Reports.
[17] Eva Lahuerta-Otero,et al. Looking for the perfect tweet. The use of data mining techniques to find influencers on twitter , 2016, Comput. Hum. Behav..
[18] B. Greenberg. Person-to-Person Communication in the Diffusion of News Events , 1964 .
[19] Bernardo A. Huberman,et al. Trends in Social Media: Persistence and Decay , 2011, ICWSM.
[20] Wolfgang Kellerer,et al. Outtweeting the Twitterers - Predicting Information Cascades in Microblogs , 2010, WOSN.
[21] Flavio Figueiredo,et al. The tube over time: characterizing popularity growth of youtube videos , 2011, WSDM '11.
[22] Gregory J. L. Tourte,et al. Twitter, information sharing and the London riots? , 2012 .
[23] Didier Sornette,et al. Robust dynamic classes revealed by measuring the response function of a social system , 2008, Proceedings of the National Academy of Sciences.
[24] Alessandro Flammini,et al. Optimal network clustering for information diffusion , 2014, Physical review letters.
[25] Roland Soong,et al. Threshold models of interpersonal effects in consumer demand , 1986 .
[26] Dylan Walker,et al. Creating Social Contagion Through Viral Product Design: A Randomized Trial of Peer Influence in Networks , 2010, ICIS.
[27] Yicheng Zhang,et al. Dynamics of information diffusion and its applications on complex networks , 2016 .
[28] Arun Sundararajan,et al. Distinguishing influence-based contagion from homophily-driven diffusion in dynamic networks , 2009, Proceedings of the National Academy of Sciences.
[29] Mark S. Granovetter,et al. Threshold models of diffusion and collective behavior , 1983 .
[30] Jintae Lee,et al. Understanding the uncertainty of disaster tweets and its effect on retweeting: The perspectives of uncertainty reduction theory and information entropy , 2019, J. Assoc. Inf. Sci. Technol..
[31] Bernardo A. Huberman,et al. What Trends in Chinese Social Media , 2011, ArXiv.
[32] Jintae Lee,et al. Content features of tweets for effective communication during disasters: A media synchronicity theory perspective , 2019, Int. J. Inf. Manag..
[33] Duncan J. Watts,et al. Everyone's an influencer: quantifying influence on twitter , 2011, WSDM '11.
[34] Jon M. Kleinberg,et al. Does Bad News Go Away Faster? , 2011, ICWSM.
[35] Jonathan J. H. Zhu,et al. Jumping onto the bandwagon of collective gatekeepers: Testing the bandwagon effect of information diffusion on social news website , 2019, Telematics Informatics.
[36] Ciro Cattuto,et al. Dynamical classes of collective attention in twitter , 2011, WWW.
[37] Eszter Hargittai,et al. The tweet smell of celebrity success: Explaining variation in Twitter adoption among a diverse group of young adults , 2011, New Media Soc..
[38] Peng Bao,et al. Cumulative Effect in Information Diffusion: Empirical Study on a Microblogging Network , 2013, PloS one.
[39] Duncan J. Watts,et al. Exploring Limits to Prediction in Complex Social Systems , 2016, WWW.
[40] Duncan J Watts,et al. A simple model of global cascades on random networks , 2002, Proceedings of the National Academy of Sciences of the United States of America.
[41] Thomas W. Valente,et al. Opinion Leadership and Social Contagion in New Product Diffusion , 2011, Mark. Sci..
[42] Melvin L. De Fleur,et al. The Growth and Decline of Research on the Diffusion of the News, 1945-1985 , 1987 .
[43] Duncan J. Watts,et al. The Structural Virality of Online Diffusion , 2015, Manag. Sci..
[44] Everett M. Rogers,et al. Reflections on News Event Diffusion Research , 2000 .
[45] Duncan J. Watts,et al. Who says what to whom on twitter , 2011, WWW.
[46] Wei Gao,et al. Mainstream media behavior analysis on Twitter: a case study on UK general election , 2013, HT '13.
[47] Eyton,et al. The Diffusion of Innovations in Social Networks , 2002 .
[48] Petter Holme,et al. Threshold model of cascades in temporal networks , 2012, ArXiv.
[49] Jukka-Pekka Onnela,et al. Spontaneous emergence of social influence in online systems , 2009, Proceedings of the National Academy of Sciences.
[50] Damon Centola,et al. The Spread of Behavior in an Online Social Network Experiment , 2010, Science.