{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T01:59:22Z","timestamp":1760061562350},"reference-count":0,"publisher":"National Library of Serbia","issue":"1","license":[{"start":{"date-parts":[[2014,1,1]],"date-time":"2014-01-01T00:00:00Z","timestamp":1388534400000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["ComSIS","COMPUT SCI INF SYST","COMPUT SCI INFORM SY","COMPUTER SCI INFORM","COMSIS J"],"published-print":{"date-parts":[[2014]]},"abstract":"<jats:p>Information spreads much faster through social networking services (SNSs)\n   than through traditional news media because users can upload data anytime,\n   anywhere. SNSs users are likely to express their emotional status to let\n   their friends or other users know how they feel about certain events. This is\n   the main reason why many studies have employed social media data to uncover\n   hidden facts or issues by analyzing social relationships and reciprocated\n   messages between users. The main goal of this study is to discover who is\n   isolated, why, and how the issue of social bullying can be addressed through\n   an in-depth analysis of negative Tweets. For this, our study takes the basic\n   approach by tracking events considered to be exciting by users and then\n   analyzing the sentiment status of their Tweets collected between November and\n   December 2009 by Stanford University. The results suggest that users tend to\n   be happier during evenings than during afternoons. The results also identify\n   the precise date of breaking news.<\/jats:p>","DOI":"10.2298\/csis130205001c","type":"journal-article","created":{"date-parts":[[2014,1,3]],"date-time":"2014-01-03T11:37:09Z","timestamp":1388749029000},"page":"157-169","source":"Crossref","is-referenced-by-count":12,"title":["Tracing trending topics by analyzing the sentiment status of tweets"],"prefix":"10.2298","volume":"11","author":[{"given":"Dongjin","family":"Choi","sequence":"first","affiliation":[{"name":"Dept. of Computer Engineering, Chosun University, Seoseok-dong, Dong-gu, Gwangju, Republic of Korea"}]},{"given":"Myunggwon","family":"Hwang","sequence":"additional","affiliation":[{"name":"Korea Institute of Science and Technology Institute (KISTI), Daehak-ro, Yuseong-gu, Daejeon, Republic of Korea"}]},{"given":"Jeongin","family":"Kim","sequence":"additional","affiliation":[{"name":"Dept. of Computer Engineering, Chosun University, Seoseok-dong, Dong-gu, Gwangju, Republic of Korea"}]},{"given":"Byeongkyu","family":"Ko","sequence":"additional","affiliation":[{"name":"Dept. of Computer Engineering, Chosun University, Seoseok-dong, Dong-gu, Gwangju, Republic of Korea"}]},{"given":"Pankoo","family":"Kim","sequence":"additional","affiliation":[{"name":"Dept. of Computer Engineering, Chosun University, Seoseok-dong, Dong-gu, Gwangju, Republic of Korea"}]}],"member":"1078","container-title":["Computer Science and Information Systems"],"original-title":[],"language":"en","deposited":{"date-parts":[[2023,5,29]],"date-time":"2023-05-29T08:31:16Z","timestamp":1685349076000},"score":1,"resource":{"primary":{"URL":"https:\/\/doiserbia.nb.rs\/Article.aspx?ID=1820-02141400001C"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014]]},"references-count":0,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2014]]}},"URL":"https:\/\/doi.org\/10.2298\/csis130205001c","relation":{},"ISSN":["1820-0214","2406-1018"],"issn-type":[{"value":"1820-0214","type":"print"},{"value":"2406-1018","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014]]}}}