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Full-Text Articles in Social Media
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 …