Matches in ScholarlyData for { ?s ?p ?o. }
- item-1 hasContent ulrik-brandes.
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- item-2 hasContent patrick-kenis.
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- item-3 hasContent juergen-lerner.
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- item-4 hasContent denise-van-raaij.
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- 75 type InProceedings.
- 75 label "The Slashdot Zoo: Mining a Social Network with Negative Edges".
- 75 sameAs 75.
- 75 abstract "We analyse the corpus of user relationships of the Slash- dot technology news site. The data was collected from the Slashdot Zoo feature where users of the website can tag other users as friends and foes, providing positive and negative en- dorsements. We adapt social network analysis techniques to the problem of negative edge weights. In particular, we con- sider signed variants of global network characteristics such as the clustering coefficient, node-level characteristics such as centrality and popularity measures, and link-level character- istics such as distances and similarity measures. We evaluate these measures on the task of identifying unpopular users, as well as on the task of predicting the sign of links and show that the network exhibits multiplicative transitivity which allows algebraic methods based on matrix multiplication to be used. We compare our methods to traditional methods which are only suitable for positively weighted edges.".
- 75 hasAuthorList authorList.
- 75 isPartOf proceedings.
- 75 keyword "Social Networks and Web 2.0".
- 75 title "The Slashdot Zoo: Mining a Social Network with Negative Edges".
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- item-1 hasContent jerome-kunegis.
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- item-2 hasContent andreas-lommatzsch.
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- item-3 hasContent christian-bauckhage.
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- 76 type InProceedings.
- 76 label "Community Gravity: Measuring Bidirectional Effects by Trust and Rating on Online Social Networks".
- 76 sameAs 76.
- 76 abstract "Several attempts have been made to analyze customer behavior on online E-commerce sites. Some studies particularly emphasize the social networks of customers. Users' reviews and ratings of a product exert effects on other consumers' purchasing behavior. Whether a user refers to other users' ratings depends on the trust accorded by a user to the reviewer. On the other hand, the trust that is felt by a user for another user correlates with the similarity of two users' ratings. This bidirectional interaction that involves trust and rating is an important aspect of understanding consumer behavior in online communities because it suggests clustering of similar users and the evolution of strong communities. This paper presents a theoretical model along with analyses of an actual online E-commerce site. We analyzed a large community site in Japan: @cosme. The noteworthy characteristics of @cosme are that users can bookmark their trusted users; in addition, they can post their own ratings of products, which facilitates our analyses of the ratings' bidirectional effects on trust and ratings. We describe an overview of the data in @cosme, analyses of effects from trust to rating and vice versa, and our proposition of a measure of of community gravity, which measures how strongly a user might be attracted to a community. Our study is based on the @cosme dataset in addition to the Epinions dataset. It elucidates important insights and proposes a potentially important measure for mining online social networks.".
- 76 hasAuthorList authorList.
- 76 isPartOf proceedings.
- 76 keyword "Social Networks and Web 2.0".
- 76 title "Community Gravity: Measuring Bidirectional Effects by Trust and Rating on Online Social Networks".
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- item-1 hasContent yutaka-matsuo.
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- item-2 hasContent hikaru-yamamoto.
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- 77 type InProceedings.
- 77 label "Mapping the World's Photos".
- 77 sameAs 77.
- 77 abstract "We investigate how to organize a large collection of geotagged photos, working with a dataset of about 35 million images collected from Flickr. Our approach combines content analysis based on text tags and image data with structural analysis based on geospatial data. We use the spatial distribution of where people take photos to define a relational structure between the photos that are taken at popular places. We then study the interplay between this structure and the content, using classification methods for predicting such locations from visual, textual and temporal features of the photos. We find that visual and temporal features improve the ability to estimate the location of a photo, compared to using just textual features. We illustrate using these techniques to organize a large photo collection, while also revealing various interesting properties about popular cities and landmarks at a global scale.".
- 77 hasAuthorList authorList.
- 77 isPartOf proceedings.
- 77 keyword "Social Networks and Web 2.0".
- 77 title "Mapping the World's Photos".
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- item-1 hasContent david-crandall.
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- item-2 hasContent lars-backstrom.
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- item-3 hasContent daniel-huttenlocher.
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- item-4 hasContent jon-kleinberg.
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- 78 type InProceedings.
- 78 label "Ranking and Classifying Attractiveness of Photos in Folksonomies".
- 78 sameAs 78.
- 78 abstract "Web 2.0 applications like Flickr, YouTube, or Del.icio.us are increasingly popular online communities for creating, editing and sharing content. The growing size of these folksonomies poses new challenges in terms of search and data mining. In this paper we introduce a novel methodology for automatically ranking and classifying photos according to their attractiveness for folksonomy members. To this end, we exploit image features known for having significant effects on the visual quality perceived by humans (e.g. sharpness and colorfulness) as well as textual meta data, in what is a multi-modal approach. Using feedback and annotations available in the Web 2.0 photo sharing system Flickr, we assign relevance values to the photos and train classification and regression models based on these relevance assignments. With the resulting machine learning models we categorize and rank photos according to their attractiveness. Applications include enhanced ranking functions for search and recommender methods for attractive content. Large scale experiments on a collection of Flickr photos demonstrate the viability of our approach.".
- 78 hasAuthorList authorList.
- 78 isPartOf proceedings.
- 78 keyword "Social Networks and Web 2.0".
- 78 title "Ranking and Classifying Attractiveness of Photos in Folksonomies".
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- item-1 hasContent jose-san-pedro.