Using Twitter's Mentions for Efficient Emergency Message Propagation

Using social media such as Twitter for emergency message propagation in times of crisis is widely thought to be a good addition to other traditional emergency population warning systems such as televisions. At the same time, most studies on Twitter influence propagation focus on retweetability of tweets. In this paper, we propose the importance of Twitter's mention function as another method of message propagation. Specifically, we show that graphs constructed from Twitter's retweet, mention, and reply functions show structural differences suggesting that using the mention function is the most efficient method of reaching the mass audience. Moreover, we show that influencers are the most prominent on the mention graph. From these analysis we conclude that we need further research in the direction of non-traditional methods of population warning systems. Further, this is the first paper that characterizes the structural differences of the retweet/mention/reply graphs in Twitter.

[1]  Jacob Ratkiewicz,et al.  Political Polarization on Twitter , 2011, ICWSM.

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

[3]  Hosung Park,et al.  What is Twitter, a social network or a news media? , 2010, WWW '10.

[4]  Krishna P. Gummadi,et al.  Measuring User Influence in Twitter: The Million Follower Fallacy , 2010, ICWSM.

[5]  Jonathan A. Ward,et al.  Structure, pace and balance in Twitter conversations , 2012 .

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

[7]  Malik Magdon-Ismail,et al.  Information Cascades in Social Media in Response to a Crisis : a Preliminary Model and a Case Study , 2012 .

[8]  A. Bruns,et al.  Local and global responses to disaster: #eqnz and the Christchurch earthquake , 2012 .

[9]  Timothy W. Finin,et al.  Why we twitter: understanding microblogging usage and communities , 2007, WebKDD/SNA-KDD '07.

[10]  Fang Wu,et al.  Social Networks that Matter: Twitter Under the Microscope , 2008, First Monday.

[11]  Preprint Mps Structure, pace and balance in Twitter conversations , 2012 .

[12]  Kenny Gruchalla,et al.  Integration and Dissemination of Citizen Reported and Seismically Derived Earthquake Information via Social Network Technologies , 2010, IDA.

[13]  Junghoo Cho,et al.  Topical semantics of twitter links , 2011, WSDM '11.

[14]  Rajeev Motwani,et al.  The PageRank Citation Ranking : Bringing Order to the Web , 1999, WWW 1999.

[15]  Barbara Poblete,et al.  Twitter under crisis: can we trust what we RT? , 2010, SOMA '10.

[16]  Leysia Palen,et al.  Microblogging during two natural hazards events: what twitter may contribute to situational awareness , 2010, CHI.