@techreport{oai:ipsj.ixsq.nii.ac.jp:00113226,
 author = {石井, 晃 and 小籔, 拓馬 and 北尾, 明子 and 鳥海, 不二夫 and 榊, 剛史},
 issue = {10},
 month = {Feb},
 note = {A mathematical theory for social events is presented based on a former mathematical model for the hit phenomenon in entertainment as a stochastic process of interactions of human dynamics. The model uses only the time distribution of advertisement budget as an input, and word-of-mouth (WOM) represented by posts on social network systems is used as data to compare with the calculated results. The unit of time is a day. The calculations of intention of people in Japanese society for the scandal of cell of stimulus-triggered acquisition of pluripotency (also known as STAP) agree very well with the twitter posting distribution in time. We focused on users' interests to classify each tweet to clusters. We devide the tweets of the STAP cell scandal into several clusters due to the frequent communication to each other. We found that the time variation of the intentions are very different for each clusters. We present some calculation due to the model for the two typical culsters; ordinary people and academic people., A mathematical theory for social events is presented based on a former mathematical model for the hit phenomenon in entertainment as a stochastic process of interactions of human dynamics. The model uses only the time distribution of advertisement budget as an input, and word-of-mouth (WOM) represented by posts on social network systems is used as data to compare with the calculated results. The unit of time is a day. The calculations of intention of people in Japanese society for the scandal of cell of stimulus-triggered acquisition of pluripotency (also known as STAP) agree very well with the twitter posting distribution in time. We focused on users' interests to classify each tweet to clusters. We devide the tweets of the STAP cell scandal into several clusters due to the frequent communication to each other. We found that the time variation of the intentions are very different for each clusters. We present some calculation due to the model for the two typical culsters; ordinary people and academic people.},
 title = {ヒット現象の数理モデルから見た社会現象の盛り上がりに関する考察},
 year = {2015}
}