Information Dissemination Model of Microblogging with Internet Marketers

Microblogging services (such as Twitter) are the representative information communication networks during the Web 2.0 era, which have gained remarkable popularity. Weibo has become a popular platform for information dissemination in online social networks due to its large number of users. In this study, a microblog information dissemination model is presented. Related concepts are introduced and analyzed based on the dynamic model of infectious disease, and new influencing factors are proposed to improve the susceptibleinfective-removal (SIR) information dissemination model. Correlation analysis is conducted on the existing information dissemination risk and the rumor dissemination model of microblog. In this study, web hyper is used to model rumor dissemination. Finally, the experimental results illustrate the effectiveness of the method in reducing the rumor dissemination of microblogs.

[1]  Matthew K. O. Lee,et al.  User satisfaction with microblogging: Information dissemination versus social networking , 2016, J. Assoc. Inf. Sci. Technol..

[2]  Wu Yang,et al.  Information influence measurement based on user quality and information attribute in microblogging , 2016, 2016 8th IEEE International Conference on Communication Software and Networks (ICCSN).

[3]  Hakim Hacid,et al.  A predictive model for the temporal dynamics of information diffusion in online social networks , 2012, WWW.

[4]  Ling Feng,et al.  Predicting lifespans of popular tweets in microblog , 2012, SIGIR '12.

[5]  Duncan J. Watts,et al.  Who says what to whom on twitter , 2011, WWW.

[6]  Qingpu Zhang,et al.  Empirical Analysis of Microblog Information Flow Features Based on Complex Network Theory , 2012 .

[7]  Leysia Palen,et al.  (How) will the revolution be retweeted?: information diffusion and the 2011 Egyptian uprising , 2012, CSCW.

[8]  Feng Ling,et al.  ReTweeting analysis and prediction in microblogs: An epidemic inspired approach , 2013, China Communications.

[9]  Zhien Ma,et al.  Modeling and dynamics of infectious diseases , 2009 .

[10]  Zhu Shi-ruia,et al.  Simulation Investigation of Rumor Propagation in Microblogging Community , 2011 .

[11]  Sudha Ram,et al.  Sharing News Articles Using 140 Characters: A Diffusion Analysis on Twitter , 2012, 2012 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining.

[12]  Lada A. Adamic,et al.  The role of social networks in information diffusion , 2012, WWW.

[13]  Xi Chen,et al.  Rumor Propagation in Online Social Networks Like Twitter -- A Simulation Study , 2011, 2011 Third International Conference on Multimedia Information Networking and Security.

[14]  Sara Cohen,et al.  A Social Network Database that Learns How to Answer Queries , 2013, CIDR.

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

[16]  Cheng Hui,et al.  The research of information dissemination model on online social network , 2011 .

[17]  Junhee Seok,et al.  Information propagation modeling in a drone network using disease epidemic models , 2016, 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN).

[18]  Christos Faloutsos,et al.  Rise and fall patterns of information diffusion: model and implications , 2012, KDD.

[19]  Mei Xue,et al.  Does microblogging convey firm-specific information? Evidence from China , 2017 .

[20]  Zhang Wei,et al.  Information Diffusion Model Based on Social Network , 2013 .

[21]  Mejari Kumar,et al.  Connecting Social Media to E-Commerce: Cold-Start Product Recommendation using Microblogging Information , 2018 .

[22]  Yi-Jun Liu,et al.  Isolation, insertion, and reconstruction: Three strategies to intervene in rumor spread based on supernetwork model , 2014, Decis. Support Syst..

[23]  Yi Chengq Research on Mechanism of Large-Scale Information Dissemination Based on Sina Weibo , 2013 .

[24]  Lu Liu,et al.  Information diffusion through online social networks , 2010, 2010 IEEE International Conference on Emergency Management and Management Sciences.

[25]  Krishna P. Gummadi,et al.  Measurement and analysis of online social networks , 2007, IMC '07.

[26]  Bernardo A. Huberman,et al.  What Trends in Chinese Social Media , 2011, ArXiv.

[27]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[28]  Michael Levine,et al.  Information Propagation in Developmental Enhancers , 2017 .

[29]  Jon M. Kleinberg,et al.  Tracing information flow on a global scale using Internet chain-letter data , 2008, Proceedings of the National Academy of Sciences.

[30]  Qinghua Zheng,et al.  Analyzing and modeling dynamics of information diffusion in microblogging social network , 2017, J. Netw. Comput. Appl..