Results 1 - 10 of 156

Connecting Users with Similar Interests via Tag Network Inference

by Xufei Wang, Huan Liu, Wei Fan
"... The popularity of social networking greatly increases interaction among people. However, one major challenge remains — how to connect people who share similar interests. In a social network, the majority of people who share similar interests with given a user are in the long tail that accounts for 8 ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
for 80 % of total population. Searching for similar users by following links in social network has two limitations: it is inefficient and incomplete. Thus, it is desirable to design new methods to find like-minded people. In this paper, we propose to use collective wisdom from the crowd or tag networks

Visualizing the signatures of social roles in online discussion groups, The

by Howard T. Welser, Eric Gleave, Danyel Fisher, Marc Smith - Journal of Social Structure , 2007
"... Abstract: Social roles in online discussion forums can be described by patterned characteristics of communication between network members which we conceive of as ‘structural signatures. ' This paper uses visualization methods to reveal these structural signatures and regression analysis to conf ..."
Abstract - Cited by 93 (10 self) - Add to MetaCart
Abstract: Social roles in online discussion forums can be described by patterned characteristics of communication between network members which we conceive of as ‘structural signatures. ' This paper uses visualization methods to reveal these structural signatures and regression analysis

Semantic stability in social tagging streams

by Claudia Wagner, Markus Strohmaier, Bernardo A. Huberman - In Proceedings of the Twenty-Third International World Wide Web Conference , 2014
"... One potential disadvantage of social tagging systems is that due to the lack of a centralized vocabulary, a crowd of users may never manage to reach a consensus on the description of resources (e.g., books, users or songs) on the Web. Yet, previous research has provided interesting evidence that the ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
that the tag distributions of resources may become semantically sta-ble over time as more and more users tag them. At the same time, previous work has raised an array of new ques-tions such as: (i) How can we assess the semantic stability of social tagging systems in a robust and methodical way? (ii) Does

Review and alignment of tag ontologies for semantically-linked data in collaborative tagging spaces

by Hak Lae Kim, Re Passant, John G. Breslin, Simon Scerri, Stefan Decker - Paper presented at the 2nd International Conference on Semantic Computing , 2008
"... Abstract—As the number of Web 2.0 sites offering tagging facilities for the users ’ voluntary content annotation increases, so do the efforts to analyze social phenomena resulting from generated tagging and folksonomies. Most of these efforts provide different views for the understanding of various ..."
Abstract - Cited by 20 (5 self) - Add to MetaCart
relations via tagging data, it proves no worth for users if this data cannot be reused. In this paper we propose a solution for tag data representation which allows data reuse across different tagging systems. To achieve this goal, we analyze current social tagging practices, existing folksonomy usage

Bringing the Associative Ability to Social Tag Recommendation

by Miao Fan, Yingnan Xiao, Qiang Zhou
"... Social tagging systems, which allow users to freely annotate online resources with tags, become popular in the Web 2.0 era. In order to ease the annotation process, research on social tag recommendation has drawn much attention in recent years. Modeling the social tagging behavior could better refle ..."
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Social tagging systems, which allow users to freely annotate online resources with tags, become popular in the Web 2.0 era. In order to ease the annotation process, research on social tag recommendation has drawn much attention in recent years. Modeling the social tagging behavior could better

Connecting Users with Similar Interests Across Multiple Web Services

by Haewoon Kwak, Hwa-yong Shin, Jong-il Yoon, Sue Moon
"... Most online social networking services provide a feature for users to build interest groups. Based on the profiles and behavior data, web services can assist users to join groups by recommending relevant interest groups. In this paper, we propose a novel method to connect users across multiple servi ..."
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Most online social networking services provide a feature for users to build interest groups. Based on the profiles and behavior data, web services can assist users to join groups by recommending relevant interest groups. In this paper, we propose a novel method to connect users across multiple

Trust Prediction via Aggregating Heterogeneous Social Networks

by Jin Huang, Feiping Nie, Yi-cheng Tu, Heng Huang
"... Along with the increasing popularity of social web sites, users rely more on the trustworthiness information for many online activities among users. However, such social network data often suffers from severe data sparsity and are not able to provide users with enough information. Therefore, trust p ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
information, is often accessible and therefore could potentially help the trust prediction. In this paper, we address the link prediction problem by aggregating heterogeneous social networks and propose a novel joint manifold factorization (JMF) method. Our new joint learning model explores the user group

Uncovering Groups via Heterogeneous Interaction Analysis

by Lei Tang, Xufei Wang, Huan Liu
"... Abstract—With the pervasive availability of Web 2.0 and social networking sites, people can interact with each other easily through various social media. For instance, popular sites like Del.icio.us, Flickr, and YouTube allow users to comment shared content (bookmark, photos, videos), and users can ..."
Abstract - Cited by 26 (6 self) - Add to MetaCart
Abstract—With the pervasive availability of Web 2.0 and social networking sites, people can interact with each other easily through various social media. For instance, popular sites like Del.icio.us, Flickr, and YouTube allow users to comment shared content (bookmark, photos, videos), and users can

Discovering overlapping groups in social media

by Xufei Wang, Lei Tang, Huiji Gao, Huan Liu - In 2010 IEEE International Conference on Data Mining , 2010
"... Abstract—The increasing popularity of social media is shortening the distance between people. Social activities, e.g., tagging in Flickr, bookmarking in Delicious, twittering in Twitter, etc. are reshaping people’s social life and redefining their social roles. People with shared interests tend to f ..."
Abstract - Cited by 22 (11 self) - Add to MetaCart
via tags and tags are connected to users. This explicit representation of users and tags is useful for understanding group evolution by looking at who is interested in what. The efficacy of our method is supported by empirical evaluation in both synthetic and online social networking data.

1 Modeling Social Interactions: Identification, Empirical Methods and Policy Implications

by Wesley R. Hartmann, David Godes, Catherine Tucker , 2007
"... Social interactions occur when agents in a network affect other agents ’ choices directly, as opposed to via the intermediation of markets. The study of such interactions and the resultant outcomes has long been an area of interest across a wide variety of social sciences. With the advent of electro ..."
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Social interactions occur when agents in a network affect other agents ’ choices directly, as opposed to via the intermediation of markets. The study of such interactions and the resultant outcomes has long been an area of interest across a wide variety of social sciences. With the advent
Results 1 - 10 of 156