TY - CHAP
T1 - Media mediate sentiments
T2 - Exploratory analysis of tweets posted before, during, and after the great East Japan earthquake
AU - Matsumura, Naohiro
AU - Miura, Asako
AU - Komori, Masashi
AU - Hiraishi, Kai
PY - 2019/9/6
Y1 - 2019/9/6
N2 - When the Great East Japan Earthquake occurred, Twitter was used as an infrastructure for sharing information carried by other media. In other words, Twitter is considered as a "meta medium." Earthquakerelated tweets included information that was of questionable veracity, contained vicious rumors, and propagated matters of controversy that often gave rise to various discussions and arguments. In this research, the authors analyzed 89,351,242 tweets posted from December 11, 2010 to April 16, 2012. They then extracted 9,816,625 URLs and classified the top 100 domains of these URLs into 19 media categories. The emotional reactions of Twitter users were investigated by counting the terms conveying positive and negative emotions included in the body of tweets along with the media URLs. The authors' findings revealed differences in terms of the frequency with which terms expressing emotions were evoked and differences in the patterns of their surges, across the various media. The authors also considered the usage of various terms appearing in tweets concurrently with the terms expressing emotion.
AB - When the Great East Japan Earthquake occurred, Twitter was used as an infrastructure for sharing information carried by other media. In other words, Twitter is considered as a "meta medium." Earthquakerelated tweets included information that was of questionable veracity, contained vicious rumors, and propagated matters of controversy that often gave rise to various discussions and arguments. In this research, the authors analyzed 89,351,242 tweets posted from December 11, 2010 to April 16, 2012. They then extracted 9,816,625 URLs and classified the top 100 domains of these URLs into 19 media categories. The emotional reactions of Twitter users were investigated by counting the terms conveying positive and negative emotions included in the body of tweets along with the media URLs. The authors' findings revealed differences in terms of the frequency with which terms expressing emotions were evoked and differences in the patterns of their surges, across the various media. The authors also considered the usage of various terms appearing in tweets concurrently with the terms expressing emotion.
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U2 - 10.4018/978-1-5225-9869-5.ch030
DO - 10.4018/978-1-5225-9869-5.ch030
M3 - Chapter
AN - SCOPUS:85077829721
SN - 1522598693
SN - 9781799800866
SP - 513
EP - 528
BT - Media Controversy
PB - IGI Global
ER -