Abstract
Social Network Services (SNS) such as Twitter play a significant role in reporting media, particularly during the extreme events. We examined the impact of tweet features on the diffusion of two types of messages during 2013 Boston marathon tragedy—rumor related and non-rumor related (both in the context of the Boston tragedy). Negative binomial analysis revealed that tweet features such as reaction time, number of followers, and usage of hashtag have an impact on tweet message diffusion during the tragedy. The number of followers showed a positive relationship with message diffusion. However, the relationship between tweet reaction time and message diffusion was negative. Finally, tweet messages that did not include hashtags diffused more than messages that contained hashtags. This paper contributes by adapting the innovation diffusion model to explore tweet message diffusion in Twitter space during extreme events.
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Ada, S., Rao, H. R., & Sharman, R. (2010). Online Social Networking Site (SNS) Use at the Campus Emergencies. Paper presented at the ICIS.
Allport, G. W., & Postman, L. (1947). The psychology of rumor. New York: Holt, Rinehart, & Wilson.
Cha, M., Mislove, A., & Gummadi, K. P. (2009). A measurement-driven analysis of information propagation in the flickr social network. Paper presented at the Proceedings of the 18th international conference on World wide web.
Chen, R., Rao, H. R., Sharman, R., Upadhyaya, S. J., & Kim, J. (2010). An empirical examination of it-enabled emergency response: the cases of hurricane Katrina and hurricane Rita. Communications of the Association for Information Systems, 26(8), 141–156.
DHS. (2014). Unclassified summary of information handling and sharing prior to the April 15, 2013 Boston Marathon Bombings.
Doerr, B., Fouz, M., & Friedrich, T. (2012). Why rumors spread so quickly in social networks. Communications of the ACM, 55(6), 70–75.
Hansen, L. K., Arvidsson, A., Nielsen, F. Å., Colleoni, E., & Etter, M. (2011). Good friends, bad news-affect and virality in twitter Future information technology (pp. 34–43): Berlin Heidelberg: Springer.
Harvey, C. G., Stewart, D. B., & Ewing, M. T. (2011). Forward or delete: What drives peer‐to‐peer message propagation across social networks? Journal of Consumer Behaviour, 10(6), 365–372.
Hausman, J. (1978). Specification tests in econometrics. Econometrica, 46(6), 1251–1271.
Hovav, A., Patnayakuni, R., & Schuff, D. (2001). Internet technology diffusion: Adoption of IPV6. Paper presented at the ECIS.
Jabr, W., & Zheng, E. (2014). Know yourself and know your enemy: An analysis of firm recommendations and consumer reviews in a competitive environment. Mis Quarterly, 38(3), 635–654.
Johnson, D. (2001). What is innovation and entrepreneurship? Lessons for larger organisations. Industrial and Commercial Training, 33(4), 135–140.
Kulakowski, K. (2013, April 20). Debunking rumors surrounding boston bombing, Infinity News Network. Retrieved from http://infinitynewsnetwork.com/2013/04/20/debunking-rumors-surrounding-boston-bombing/.
Kwon, K. H., Oh, O., Agrawal, M., & Rao, H. R. (2012). Audience gatekeeping in the twitter service: an investigation of tweets about the 2009 gaza conflict. AIS Transactions on Human-Computer Interaction, 4(4), 212–229.
Li, J., & Rao, H. (2010). Twitter as a rapid response news service: an exploration in the context of the 2008 China earthquake. The Electronic Journal of Information Systems in Developing Countries, 42(4), 1–22.
Li, J., Vishwanath, A., & Rao, H. R. (2014). Retweeting the Fukushima nuclear radiation disaster. Communications of the ACM, 57(1), 78–85.
Merriam-Webster.com. (2015). Rumor. Retrieved January 27, 2015, from http://www.merriam-webster.com/dictionary/rumor.
Oh, O., Agrawal, M., & Rao, H. R. (2013). Community intelligence and social media services: a rumor theoretic analysis of tweets during social crises. MIS Quarterly, 37(2), 407–426.
Osgood, D. W. (2000). Poisson-based regression analysis of aggregate crime rates. Journal of Quantitative Criminology, 16(1), 21–43.
oxforddictionaries.com. (2015). Rumor. Retrieved January 27, 2015, from http://www.oxforddictionaries.com/us/definition/american_english/rumor?searchDictCode=all.
Paternoster, R., & Brame, R. (1997). Multiple routes to delinquency? A test of developmental and general theories of crime. Criminology, 35(1), 49–84.
Petrovic, S., Osborne, M., & Lavrenko, V. (2011). RT to Win! Predicting message propagation in twitter. Paper presented at the ICWSM.
Piddock, C. (2014). Anatomy of a terrorist attack:The boston marathon bombing. Homeland security surverillance, detection, prevention & protection, 24–33.
Rogers, E. (1962). Diffusion of innovations (1st ed.). New York: Free Press.
Romero, D. M., Meeder, B., & Kleinberg, J. (2011). Differences in the mechanics of information diffusion across topics: idioms, political hashtags, and complex contagion on twitter. Paper presented at the Proceedings of the 20th international conference on World wide web.
Starbird, K., Maddock, J., Orand, M., & Mason, R. M. (2014). Rumors, false flags, and digital vigilantes: misinformation on twitter after the 2013 Boston Marathon bombing. iConference.
Suh, B., Hong, L., Pirolli, P., & Chi, E. H. (2010). Want to be retweeted? large scale analytics on factors impacting retweet in twitter network. Paper presented at the Social computing (socialcom), 2010 ieee second international conference on.
Taylor, R. (1990). Interpretation of the correlation coefficient: a basic review. Journal of Diagnostic Medical Sonography, 6(1), 35–39.
Twitter. (2013). Using hashtags on Twitter. Retrieved January 28, 2015, from https://support.twitter.com/.
Yang, L., Sun, T., Zhang, M., & Mei, Q. (2012). We know what@ you# tag: does the dual role affect hashtag adoption? Paper presented at the Proceedings of the 21st international conference on World Wide Web.
Ye, S., & Wu, S. F. (2010). Measuring message propagation and social influence on Twitter. com: Springer.
Zaman, T. R., Herbrich, R., Van Gael, J., & Stern, D. (2010). Predicting information spreading in twitter. Paper presented at the Workshop on computational social science and the wisdom of crowds, nips.
Zhou, Z., Bandari, R., Kong, J., Qian, H., & Roychowdhury, V. (2010). Information resonance on twitter: watching iran. Paper presented at the Proceedings of the First Workshop on Social Media Analytics.
Acknowledgments
This research is funded by National Science Foundation under grants 1353119 and 1353195. The usual disclaimer applies. We would like to thank Anu Mary Eapen, Basma Abdul Rehman, Sabharish Sainath, Megan Saldanha, and Swati Upadhya for their research support.
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Lee, J., Agrawal, M. & Rao, H.R. Message diffusion through social network service: The case of rumor and non-rumor related tweets during Boston bombing 2013. Inf Syst Front 17, 997–1005 (2015). https://doi.org/10.1007/s10796-015-9568-z
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DOI: https://doi.org/10.1007/s10796-015-9568-z