著者
川野 陽慈 山野辺 一記 栗原 聡 Yoji Kawano Ituki Yamanobe Satoshi Kurihara
雑誌
SIG-SAI = SIG-SAI
巻号頁・発行日
vol.31, no.1, pp.1-8, 2018-03-01

現在,世界的にゲーム市場が拡大し必要なシナリオも増加している.シナリオライターの負担軽減と物語多様性の担保という観点から,シナリオ自動生成システムの開発が必要であると考えられる.そこで本研究では,シナリオの8割以上が当てはまるシナリオ構造である13フェイズ構造を活用し,それによるシナリオ作成一連の工程をすべて自動化,シナリオを生成するシステムASBS(Automatic Scenario Building System)の開発を行う.今回は,シナリオ作成に必要な,プロットの生成自動化をASBSによって行った.
著者
岡田 佳之 榊 剛史 鳥海 不二夫 篠田 孝祐 風間 一洋 野田 五十樹 沼尾 正行 栗原 聡 Okada Yoshiyuki Takeshi Sakaki Fujio Toriumi Kosuke Shinoda Kazuhiro Kazama Itsuki Noda Masayuki Numao Satoshi Kurihara
雑誌
SIG-SAI = SIG-SAI
巻号頁・発行日
vol.16, no.1, pp.1-9, 2013-03-11

Twitter is a famous social networking service and has received attention recently. Twitter user have increased rapidly, and many users exchange information. When 2011 Tohoku earthquake and tsunami happened, people were able to obtain information from social networking service. Though Twitter played the important role, one of the problem of Twitter, a false rumor diffusion, was pointed out. In this research, we focus on a false rumor diffusion. We propose a information diffusion model based on SIR model, classify the way of diffusion in four categories, and reapper the real diffussion by using this new model.
著者
Yoshiyuki Okada Keisuke Ikeda Kosuke Shinoda Fujio Toriumi Takeshi Sakaki Kazuhiro Kazama Masayuki Numao Itsuki Noda Satoshi Kurihara
出版者
Fuji Technology Press Ltd.
雑誌
Journal of Advanced Computational Intelligence and Intelligent Informatics (ISSN:13430130)
巻号頁・発行日
vol.18, no.4, pp.598-607, 2014-07-20 (Released:2019-07-01)
参考文献数
11
被引用文献数
11

Nowadays, users of Twitter, one of famous social networking service, have rapidly increased in number, and many people have been exchanging information by Twitter. When the Great East Japan Earthquake struck in 2011, people were able to obtain information from social networking services. Though Twitter played an important role, one problem was especially pointed out: false rumor diffusion. In this study, we propose an information diffusion model based on the SIR model and discuss how to prevent false rumor diffusion.