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題名 Event detection in an ego network on Facebook
作者 徐國偉
Chiu, Shu I
Hsu, Kuowei
貢獻者 資科系
關鍵詞 Ego network; Online social networking service; Topic identification
日期 2016
上傳時間 23-Aug-2017 16:43:42 (UTC+8)
摘要 Online social networking services, such as Twitter and Facebook have attracted considerable research interests. Event detection has been studied for quite some time, and there are studies that discuss event detection on Twitter; social network analysis has been studied for an even longer time, and there are studies that apply social network analysis to data collected from Facebook. However, not much research attention is on event detection on Facebook. In this paper, we address the problem of how to detect events in an ego network on Facebook. Our proposed approach first uses K-Means to cluster posts based on words, then builds an interaction graph based on comments and likes given to posts, then applies PageRank to the interaction graph in order to identify active posters, and finally finds the topics based on the frequent words used by the active posters. Based on the experiment result, our proposed approach can identify topics that are highly relevant to real-world events and simultaneously identify users who are of higher degrees of interaction.
關聯 Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedings
20th Pacific Asia Conference on Information Systems, PACIS 2016; Chiayi; Taiwan; 27 June 2016 到 1 July 2016; 代碼 125137
資料類型 conference
dc.contributor 資科系zh_TW
dc.creator (作者) 徐國偉zh-TW
dc.creator (作者) Chiu, Shu Ien-US
dc.creator (作者) Hsu, Kuoweien-US
dc.date (日期) 2016
dc.date.accessioned 23-Aug-2017 16:43:42 (UTC+8)-
dc.date.available 23-Aug-2017 16:43:42 (UTC+8)-
dc.date.issued (上傳時間) 23-Aug-2017 16:43:42 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/112134-
dc.description.abstract (摘要) Online social networking services, such as Twitter and Facebook have attracted considerable research interests. Event detection has been studied for quite some time, and there are studies that discuss event detection on Twitter; social network analysis has been studied for an even longer time, and there are studies that apply social network analysis to data collected from Facebook. However, not much research attention is on event detection on Facebook. In this paper, we address the problem of how to detect events in an ego network on Facebook. Our proposed approach first uses K-Means to cluster posts based on words, then builds an interaction graph based on comments and likes given to posts, then applies PageRank to the interaction graph in order to identify active posters, and finally finds the topics based on the frequent words used by the active posters. Based on the experiment result, our proposed approach can identify topics that are highly relevant to real-world events and simultaneously identify users who are of higher degrees of interaction.en_US
dc.format.extent 343554 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) Pacific Asia Conference on Information Systems, PACIS 2016 - Proceedingsen_US
dc.relation (關聯) 20th Pacific Asia Conference on Information Systems, PACIS 2016; Chiayi; Taiwan; 27 June 2016 到 1 July 2016; 代碼 125137en_US
dc.subject (關鍵詞) Ego network; Online social networking service; Topic identificationen_US
dc.title (題名) Event detection in an ego network on Facebooken_US
dc.type (資料類型) conference