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Social and Behavioral Sciences Commons

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Full-Text Articles in Social and Behavioral Sciences

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes Dec 2011

Wsm 2011: Third Acm Workshop On Social Media, Steven C. H. Hoi, Michal Jacovi, Ioannis Kompatsiaris, Jiebo Luo, Konstantinos Tserpes

Research Collection School Of Computing and Information Systems

The Third Workshop on Social Media (WSM2011) continues the series of Workshops on Social Media in 2009 and 2010 and has been established as a platform for the presentation and discussion of the latest, key research issues in social media analysis, exploration, search, mining, and emerging new social media applications. It is held in conjunction with the ACM International Multimedia Conference (MM'11) at Scottsdale, Arizona, USA, 2011 and has attracted contributions on various aspects of social media including data mining from social media, content organization, geo-localization, personalization, recommendation systems, user experience, machine learning and social media approaches and architectures for …


Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei Dec 2011

Context-Based Friend Suggestion In Online Photo-Sharing Community, Ting Yao, Chong-Wah Ngo, Tao Mei

Research Collection School Of Computing and Information Systems

With the popularity of social media, web users tend to spend more time than before for sharing their experience and interest in online photo-sharing sites. The wide variety of sharing behaviors generate different metadata which pose new opportunities for the discovery of communities. We propose a new approach, named context-based friend suggestion, to leverage the diverse form of contextual cues for more effective friend suggestion in the social media community. Different from existing approaches, we consider both visual and geographical cues, and develop two user-based similarity measurements, i.e., visual similarity and geo similarity for characterizing user relationship. The problem of …


Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li Dec 2011

Modeling Social Strength In Social Media Community Via Kernel-Based Learning, Jinfeng Zhuang, Tao Mei, Steven C. H. Hoi, Xian-Sheng Hua, Shipeng Li

Research Collection School Of Computing and Information Systems

Modeling continuous social strength rather than conventional binary social ties in the social network can lead to a more precise and informative description of social relationship among people. In this paper, we study the problem of social strength modeling (SSM) for the users in a social media community, who are typically associated with diverse form of data. In particular, we take Flickr---the most popular online photo sharing community---as an example, in which users are sharing their experiences through substantial amounts of multimodal contents (e.g., photos, tags, geo-locations, friend lists) and social behaviors (e.g., commenting and joining interest groups). Such heterogeneous …


Content Contribution Under Revenue Sharing And Reputation Concern In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston Dec 2011

Content Contribution Under Revenue Sharing And Reputation Concern In Social Media: The Case Of Youtube, Qian Tang, Bin Gu, Andrew B. Whinston

Research Collection School Of Computing and Information Systems

A key feature of social media is that it allows individuals and businesses to contribute contents for public viewing. However, little is known about how content providers derive payoffs from such activities. In this study, we build a dynamic structural model to recover the utility function for content providers. Our model distinguishes short-term payoffs based on ad revenue sharing from long-term payoffs driven by content providers’ reputation. The model was estimated using a panel data of 914 top 1000 providers and 381 randomly selected providers on YouTube from Jun 7th, 2010, to Aug 7th, 2011. The two different sets of …


Measuring Social Networks For Real-Time Competitive Advantage, Singapore Management University Nov 2011

Measuring Social Networks For Real-Time Competitive Advantage, Singapore Management University

Perspectives@SMU

Social networks offer up a goldmine of information just waiting to be exploited. For the first time, human relationships, comments and activities are documented quite publicly on platforms like Facebook and Twitter. Save for privacy concerns, never before has it been easier to know what people think, what they like, and to whom they are connected.


Exploring Tweets Normalization And Query Time Sensitivity For Twitter Search, Zhongyu Wei, Wei Gao, Lanjun Zhou, Binyang Li, Kam-Fai Wong Nov 2011

Exploring Tweets Normalization And Query Time Sensitivity For Twitter Search, Zhongyu Wei, Wei Gao, Lanjun Zhou, Binyang Li, Kam-Fai Wong

Research Collection School Of Computing and Information Systems

This paper presents our work for the Realtime Adhoc Task of TREC 2011 Microblog Track. Microblog texts like tweets are generally characterized by the inclusion of a large proportion of irregular expressions, such as ill-formed words, which can lead to significant mismatch between query terms and tweets. In addition, Twitter queries are distinguished from Web queries with many unique characteristics, one of which reflects the clearly distinct temporal aspects of Twitter search behavior. In this study, we deal with the first problem by normalizing tweet texts and the second by capturing the temporal characteristics of topic. We divided topics into …


On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu Oct 2011

On Modeling Virality Of Twitter Content, Tuan Anh Hoang, Ee Peng Lim, Palakorn Achananuparp, Jing Jiang, Feida Zhu

Research Collection School Of Computing and Information Systems

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In this paper, we study the virality of socio-political tweet content in the Singapore’s 2011 general election (GE2011). We collected tweet data generated by about 20K Singapore users from 1 April 2011 till 12 May 2011, and the follow relationships among them. We introduce several quantitative …


Virality Modeling And Analysis, Tuan Anh Hoang, Ee-Peng Lim Oct 2011

Virality Modeling And Analysis, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

Virality is a virus-like behavior that allows a piece of information to widely and quickly diffuse within the network of adopters through word of mouth. It is about how easy users propagate information to their friends and friends of friends by means of diffusion. While virality of information has several interesting applications, there are much research to be conducted on virality. These areas of research include understanding the mechanism of virality, modeling the virality both qualitatively and quantitatively, and applying virality to applications such as marketing, event detection, and others. In this paper, we survey existing works on quantitative models …


A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim Oct 2011

A Survey Of Information Diffusion Models And Relevant Problems, Minh Duc Luu, Tuan Anh Hoang, Ee-Peng Lim

Research Collection School Of Computing and Information Systems

There has been tremendous interest in diffusion of innovations or information in a social system. Nowadays, social networks (offline as well as online) are considered as important medium for diffusion and large amount of research has been conducted to understand the dynamics of diffusion in social networks. In this work, we review some of the models proposed for diffusion in social networks. We also highlight the major features of these models by dividing the surveyed models into two categories: non-network and network diffusion models. The former refers to user communities without any knowledge about the user relationship network and the …


Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim Oct 2011

Mining Direct Antagonistic Communities In Explicit Trust Networks, David Lo, Didi Surian, Zhang Kuan, Ee Peng Lim

Research Collection School Of Computing and Information Systems

There has been a recent increase of interest in analyzing trust and friendship networks to gain insights about relationship dynamics among users. Many sites such as Epinions, Facebook, and other social networking sites allow users to declare trusts or friendships between different members of the community. In this work, we are interested in extracting direct antagonistic communities (DACs) within a rich trust network involving trusts and distrusts. Each DAC is formed by two subcommunities with trust relationships among members of each sub-community but distrust relationships across the sub-communities. We develop an efficient algorithm that could analyze large trust networks leveraging …


Growing Singapore's Funny Bone: Laughing In The Face Of Dangers, Pitfalls And Politicians, Singapore Management University Sep 2011

Growing Singapore's Funny Bone: Laughing In The Face Of Dangers, Pitfalls And Politicians, Singapore Management University

Perspectives@SMU

There was once a time in Singapore when the mocking of authority figures would be regarded as a no-go zone. Leaders and politicians were rarely subjects of comedy for such jokes would be considered too distasteful and disrespectful for mass consumption. Acceptable local comedy, as such, was limited to the physical and sometimes lowbrow variety.


Media Landscape In Twitter: A World Of New Conventions And Political Diversity, Jisun An, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft Jul 2011

Media Landscape In Twitter: A World Of New Conventions And Political Diversity, Jisun An, Meeyoung Cha, Krishna Gummadi, Jon Crowcroft

Research Collection School Of Computing and Information Systems

We present a preliminary but groundbreaking study of the media landscape of Twitter. We use public data on whom follows who to uncover common behaviour in media consumption, the relationship between various classes of media, and the diversity of media content which social links may bring. Our analysis shows that there is a non-negligible amount of indirect media exposure, either through friends who follow particular media sources, or via retweeted messages. We show that the indirect media exposure expands the political diversity of news to which users are exposed to a surprising extent, increasing the range by between 60-98%. These …


Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li Jun 2011

Topical Keyphrase Extraction From Twitter, Xin Zhao, Jing Jiang, Jing He, Yang Song, Palakorn Achananuparp, Ee Peng Lim, Xiaoming Li

Research Collection School Of Computing and Information Systems

Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for keyphrase ranking. We evaluate our proposed methods on a large Twitter data set. Experiments show that these methods are very effective for topical keyphrase extraction.


Comparing Twitter And Traditional Media Using Topic Models, Wayne Xin Zhao, Jing Jiang, Jianshu Weng, Jing He, Ee Peng Lim, Hongfei Yan, Xiaoming Li Apr 2011

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 Apr 2011

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 …


Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu Feb 2011

Manipulation In Digital Word-Of-Mouth: A Reality Check For Book Reviews, Nan Hu, Indranil Bose, Yunjun Gao, Ling Liu

Research Collection School Of Computing and Information Systems

Built upon the discretionary accrual-based earnings management framework, our paper develops a discretionary manipulation proxy to study the management of online reviews. We reveal that fraudulent review manipulation is a serious problem for 1) non-bestseller books; 2) books whose reviews are classified as not very helpful; 3) books that experience greater variability in the helpfulness of their online reviews; and 4) popular books as well as high-priced books. We also show that review management decreases with the passage of time. Just like fraudulent earnings management, manipulated online reviews reflect inauthentic information from which consumers might derive wrong valuation especially for …