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Articles 211 - 220 of 220
Full-Text Articles in Social Media
Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li
Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li
Research Collection School Of Computing and Information Systems
Twitter as a new form of social media can potentially contain much useful information, but content analysis on Twitter has not been well studied. In particular, it is not clear whether as an information source Twitter can be simply regarded as a faster news feed that covers mostly the same information as traditional news media. In This paper we empirically compare the content of Twitter with a traditional news medium, New York Times, using unsupervised topic modeling. We use a Twitter-LDA model to discover topics from a representative sample of the entire Twitter. We then use text mining techniques to …
Utility-Oriented K-Anonymization On Social Networks, Yazhe Wang, Long Xie, Baihua Zheng, Ken C. K. Lee
Utility-Oriented K-Anonymization On Social Networks, Yazhe Wang, Long Xie, Baihua Zheng, Ken C. K. Lee
Research Collection School Of Computing and Information Systems
"Identity disclosure" problem on publishing social network data has gained intensive focus from academia. Existing k-anonymization algorithms on social network may result in nontrivial utility loss. The reason is that the number of the edges modified when anonymizing the social network is the only metric to evaluate utility loss, not considering the fact that different edge modifications have different impact on the network structure. To tackle this issue, we propose a novel utility-oriented social network anonymization scheme to achieve privacy protection with relatively low utility loss. First, a proper utility evaluation model is proposed. It focuses on the changes on …
Wsm'10: Second Acm Workshop On Social Media, Susanne Boll, Steven C. H. Hoi, Roelof Van Zwol, Jiebo Luo
Wsm'10: Second Acm Workshop On Social Media, Susanne Boll, Steven C. H. Hoi, Roelof Van Zwol, Jiebo Luo
Research Collection School Of Computing and Information Systems
The ACM SIGMM International Workshop on Social Media (WSM'10) is the second workshop held in conjunction with the ACM International Multimedia Conference (MM'10) at Firenze, Italy, 2010. This workshop provides a forum for researchers and practitioners from all over the world to share information on their latest investigations on social media analysis, exploration, search, mining, and emerging new social media applications.
Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng
Mining Interesting Link Formation Rules In Social Networks, Cane Wing-Ki Leung, Ee Peng Lim, David Lo, Jianshu Weng
Research Collection School Of Computing and Information Systems
Link structures are important patterns one looks out for when modeling and analyzing social networks. In this paper, we propose the task of mining interesting Link Formation rules (LF-rules) containing link structures known as Link Formation patterns (LF-patterns). LF-patterns capture various dyadic and/or triadic structures among groups of nodes, while LF-rules capture the formation of a new link from a focal node to another node as a postcondition of existing connections between the two nodes. We devise a novel LF-rule mining algorithm, known as LFR-Miner, based on frequent subgraph mining for our task. In addition to using a support-confidence framework …
Extracting Common Emotions From Blogs Based On Fine-Grained Sentiment Clustering, Shi Feng, Daling Wang, Ge Yu, Wei Gao, Kam-Fai Wong
Extracting Common Emotions From Blogs Based On Fine-Grained Sentiment Clustering, Shi Feng, Daling Wang, Ge Yu, Wei Gao, Kam-Fai Wong
Research Collection School Of Computing and Information Systems
Recently, blogs have emerged as the major platform for people to express their feelings and sentiments in the age of Web 2.0. The common emotions, which reflect people’s collective and overall sentiments, are becoming the major concern for governments, business companies and individual users. Different from previous literatures on sentiment classification and summarization, the major issue of common emotion extraction is to find out people’s collective sentiments and their corresponding distributions on the Web. Most existing blog clustering methods take into account keywords, stories or timelines but neglect the embedded sentiments, which are considered very important features of blogs. In …
Twitterrank: Finding Topic-Sensitive Influential Twitterers, Jianshu Weng, Ee Peng Lim, Jing Jiang, Qi He
Twitterrank: Finding Topic-Sensitive Influential Twitterers, Jianshu Weng, Ee Peng Lim, Jing Jiang, Qi He
Research Collection School Of Computing and Information Systems
This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called "following", in which each user can choose who she wants to "follow" to receive tweets from without requiring the latter to give permission first. In a dataset prepared for this study, it is observed that (1) 72.4% of the users in Twitter follow more than 80% of their followers, and (2) 80.5% of the users have 80% of users they are following follow them back. Our study reveals that the presence of "reciprocity" can …
First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King
First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King
Research Collection School Of Computing and Information Systems
No abstract provided.
First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King
First Acm Sigmm International Workshop On Social Media (Wsm'09), Suzanne Boll, Steven C. H. Hoi, Jiebo Luo, Rong Jin, Dong Xu, Irwin King
Research Collection School Of Computing and Information Systems
The ACM SIGMM International Workshop on Social Media(WSM’09) is the first workshop held in conjunction withthe ACM International Multimedia Conference (MM’09) atBejing, P.R. China, 2009. This workshop provides a forumfor researchers and practitioners from all over the world toshare information on their latest investigations on social mediaanalysis, exploration, search, mining, and emerging newsocial media applications.
Leveraging Social Context For Searching Social Media, Marc Smith, Vladimir Barash, Lise Getoor, Hady W. Lauw
Leveraging Social Context For Searching Social Media, Marc Smith, Vladimir Barash, Lise Getoor, Hady W. Lauw
Research Collection School Of Computing and Information Systems
The ability to utilize and benefit from today's explosion of social media sites depends on providing tools that allow users to productively participate. In order to participate, users must be able to find resources (both people and information) that they find valuable. Here, we argue that in order to do this effectively, we should make use of a user's "social context". A user's social context includes both their personal social context (their friends and the communities to which they belong) and their community social context (their role and identity in different communities).
National Culture And Its Effects On Knowledge Communication In Online Virtual Communities, Keng Siau, Fiona Fui-Hoon Nah, Min Ling
National Culture And Its Effects On Knowledge Communication In Online Virtual Communities, Keng Siau, Fiona Fui-Hoon Nah, Min Ling
Research Collection School Of Computing and Information Systems
Online virtual communities provide a powerful means of knowledge sharing. Despite the prevalence of online virtual communities, there is a paucity of research to investigate the effect of national culture differences on knowledge sharing in online virtual communities. Are there differences between online virtual communities from different national cultures? This research studies the differences in knowledge-sharing activities between US-based and China-based online virtual communities. Hofstede's dimensions of national culture serve as the theoretical foundation for this research.