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Hwang, S.-Y.; Yang, W.-S.; Ting, K.-D.: Automatic index construction for multimedia digital libraries (2010)
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Huang, H.; Chu, S. K.-W.; Chen, D. Y.-T.: Interactions between English-speaking and Chinese-speaking users and librarians on social networking sites (2015)
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Social Media und Web Science : das Web als Lebensraum, Düsseldorf, 22. - 23. März 2012, Proceedings, hrsg. von Marlies Ockenfeld, Isabella Peters und Katrin Weller. DGI, Frankfurt am Main 2012 (2012)
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- Editor
- Ockenfeld, M., I. Peters u. K. Weller
-
Thelwall, M.; Buckley, K.; Paltoglou, G.: Sentiment in Twitter events (2011)
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- Date
- 22. 1.2011 14:27:06
-
Griesbaum, J.; Mahrholz, N.; Kiedrowski, K. von Löwe; Rittberger, M.: Knowledge generation in online forums : a case study in the German educational domain (2015)
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- Date
- 20. 1.2015 18:30:22
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Chen, Y.-L.; Chuang, C.-H.; Chiu, Y.-T.: Community detection based on social interactions in a social network (2014)
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Liu, Y.; Du, F.; Sun, J.; Silva, T.; Jiang, Y.; Zhu, T.: Identifying social roles using heterogeneous features in online social networks (2019)
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Zhang, Y.; Sun, Y.; Xie, B.: Quality of health information for consumers on the web : a systematic review of indicators, criteria, tools, and evaluation results (2015)
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Kim, Y.-M.: ¬The adoption of university library Web site resources : a multigroup analysis (2010)
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Tashiro, H.; Lau, A.; Mori, J.; Fujii, N.; Kajikawa, Y.: E-mail networks and leadership performance (2012)
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Yang, S.; Han, R.; Ding, J.; Song, Y.: ¬The distribution of Web citations (2012)
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Shmargad, Y.: Structural diversity and tie strength in the purchase of a social networking app (2018)
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Song, L.; Tso, G.; Fu, Y.: Click behavior and link prioritization : multiple demand theory application for web improvement (2019)
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Schultz, S.: ¬Die eine App für alles : Mobile Zukunft in China (2016)
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- Date
- 22. 6.2018 14:22:02
-
Strittmatter, K.: Chinas digitaler Plan für den besseren Menschen (2017)
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Song, M.; Jeong, Y.K.; Kim, H.J.: Identifying the topology of the K-pop video community on YouTube : a combined co-comment analysis approach (2015)
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- Abstract
- YouTube is a successful social network that people use to upload, watch, and comment on videos. We believe comments left on these videos can provide insight into user interests, but to this point have not been used to map out a specific video community. Our study investigates whether and how user commenting behavior impacts the topology of the K-pop video community through analysis of co-commenting behavior on these videos. We apply a traditional author cocitation analysis to this behavior, in a process we refer to as co-comment analysis, to detect the topology of this community. This involves: a) an analysis of user co-comments to elicit the inclination of user homophily within the community; b) an analysis of user co-comments, weighted frequency of co-comments, to detect user interests in the community; and c) an analysis of user co-comments, weighted sentiment scores, to capture user opinions by polarity. The results indicate that users who comment on specific K-pop videos also tend to comment on topically similar YouTube videos. We also find that the number of comments made by users correlates with the degree of positivity of their comments. Conversely, users who comment negatively on K-pop videos are not inclined to form specific user groups, but rather present only their opinions individually.
-
Bar-Ilan, J.; Zhitomirsky-Geffet, M.; Miller, Y.; Shoham, S.: ¬The effects of background information and social interaction on image tagging (2010)
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Yang, M.; Kiang, M.; Chen, H.; Li, Y.: Artificial immune system for illicit content identification in social media (2012)
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Bae, Y.; Lee, H.: Sentiment analysis of twitter audiences : measuring the positive or negative influence of popular twitterers (2012)
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Xiao, C.; Zhou, F.; Wu, Y.: Predicting audience gender in online content-sharing social networks (2013)
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