title: Does Twitter trigger bursts in signature collections?
abstract: BACKGROUND
  The quantification of social media impacts on societal and political events is a difficult undertaking. The Japanese Society of Oriental Medicine started a signature-collecting campaign to oppose a medical policy of the Government Revitalization Unit to exclude a traditional Japanese medicine, "Kampo," from the public insurance system. The signature count showed a series of aberrant bursts from November 26 to 29, 2009. In the same interval, the number of messages on Twitter including the keywords "Signature" and "Kampo," increased abruptly. Moreover, the number of messages on an Internet forum that discussed the policy and called for signatures showed a train of spikes.
  
  
  RESULTS
  In order to estimate the contributions of social media, we developed a statistical model with state-space modeling framework that distinguishes the contributions of multiple social media in time-series of collected public opinions. We applied the model to the time-series of signature counts of the campaign and quantified contributions of two social media, i.e., Twitter and an Internet forum, by the estimation. We found that a considerable portion (78%) of the signatures was affected from either of the social media throughout the campaign and the Twitter effect (26%) was smaller than the Forum effect (52%) in total, although Twitter probably triggered the initial two bursts of signatures. Comparisons of the estimated profiles of the both effects suggested distinctions between the social media in terms of sustainable impact of messages or tweets. Twitter shows messages on various topics on a time-line; newer messages push out older ones. Twitter may diminish the impact of messages that are tweeted intermittently.
  
  
  CONCLUSIONS
  The quantification of social media impacts is beneficial to better understand people's tendency and may promote developing strategies to engage public opinions effectively. Our proposed method is a promising tool to explore information hidden in social phenomena.
authors.affiliation: Human Genome Center, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
authors.forename: Rui
authors.initials: R
authors.lastname: Yamaguchi
authors.forename: Seiya
authors.initials: S
authors.lastname: Imoto
authors.forename: Masahiro
authors.initials: M
authors.lastname: Kami
authors.forename: Kenji
authors.initials: K
authors.lastname: Watanabe
authors.forename: Satoru
authors.initials: S
authors.lastname: Miyano
authors.forename: Koichiro
authors.initials: K
authors.lastname: Yuji
mesh_terms: D006801:Humans; D033181:Information Dissemination; D020407:Internet / Q000706:statistics & numerical data*; D007564:Japan; D015233:Models, Statistical; D011639:Public Opinion