2019年5月
Emotion Prediction and Cause Analysis Considering Spatio-Temporal Distribution
JOURNAL OF ADVANCED COMPUTATIONAL INTELLIGENCE AND INTELLIGENT INFORMATICS
- ,
- 巻
- 23
- 号
- 3
- 開始ページ
- 512
- 終了ページ
- 518
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.20965/jaciii.2019.p0512
- 出版者・発行元
- FUJI TECHNOLOGY PRESS LTD
This paper proposes an analytical model that clarifies the relationship between specific place and human emotions as well as the cause of the emotions using tweet data with location information. In addition, Twitter data with location information are analyzed to show the effectiveness of our proposed model. First, geotags are provided to collect Twitter data and increase the number of data for analysis. Second, training data with emotion labels based on the emotion expression dictionary are created and used, and supervised learning is done using fastText to obtain the emotion estimates. Finally, by using the result, topic extraction is performed to estimate the causes of the emotions. As a result, the transition of emotion in time and space as well as its cause is obtained.
- リンク情報
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- DOI
- https://doi.org/10.20965/jaciii.2019.p0512
- DBLP
- https://dblp.uni-trier.de/rec/journals/jaciii/KitaokaH19
- Web of Science
- https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000468345300017&DestApp=WOS_CPL
- URL
- https://dblp.uni-trier.de/db/journals/jaciii/jaciii23.html#KitaokaH19
- ID情報
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- DOI : 10.20965/jaciii.2019.p0512
- ISSN : 1343-0130
- eISSN : 1883-8014
- DBLP ID : journals/jaciii/KitaokaH19
- Web of Science ID : WOS:000468345300017