{"title":"Private Information Transmission on the Consumer Generated Media: Information Privacy in the Japanese Context","authors":"Yohko Orito, H. Okada, Hidenobu Sai","doi":"10.1109/ASONAM.2011.82","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.82","url":null,"abstract":"This study examined private information transmissions on CGM/UGM websites from the perspective of the Japanese sense of information privacy. The characteristics of Japanese private information transmission on the CGM are described and discussed.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124914856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Automatic Tag Attachment Scheme for Efficient File Search in Peer-to-Peer File Sharing Systems","authors":"T. Qin, S. Fujita","doi":"10.1109/ASONAM.2011.11","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.11","url":null,"abstract":"In this paper, we consider the problem of automatic tag attachment to the documents distributed over a P2P network aiming at improving the efficiency of file search in such networks. The proposed scheme combines text clustering with a modified tag extraction algorithm, and is executed in a fully distributed manner. We conducted experiments to evaluate the accuracy of the proposed scheme. The result of experiments indicates that for more than 90% of documents, it attaches the same tags as the ones attached by human reviewers.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125863717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Dynamics of Adolescent Friendships: The Interplay between Structure and Gender","authors":"Pei-Chun Ko, V. Buskens","doi":"10.1109/ASONAM.2011.30","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.30","url":null,"abstract":"This study investigates the network characteristics of adolescent friendship networks and the interaction between network characteristics and gender. Two competing hypotheses for closure and openness are derived and tested. Adolescents might strive for network closure, because this facilitates trust and trustworthiness among their friends. However, openness can also be beneficial because it facilitates establishing multi-layered identities and finding novel ideas for school tasks. The hypothesis for interaction between structure and gender is derived from the argument that gender influences the criteria for seeking and making friends during adolescence. SIENA is used to estimate the effects of network and individual characteristics on friendship formation. The data consists of longitudinal friendship nominations of 410 Taiwanese adolescents. We find that adolescents have a tendency to establish friendships that increase network closure. This tendency is stronger for male than for female adolescents in single-gender classes. On the contrary, the tendency towards network closure is stronger for female than for male adolescents in mixed-gender classes.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123400690","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Building a Learning Games Network in Cloud Learning Platform Based on Immigrant Education","authors":"Chien-Chih Tu, An-Pin Chen","doi":"10.1109/ASONAM.2011.125","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.125","url":null,"abstract":"As with rapid growth of the computer technology, E-learning systems usually require many hardware and software resources, There are numerous educational institutions that cannot offer such investments, and cloud learning platform is the best solution for them. This paper proposes a model of using cloud computing and learning network upon cloud-learning solutions development. The cloud-learning platform combined with different types of games is gradually noticed by people because it can enhance user learning motivation. This research has developed a Chinese language cloud-learning system for the new immigrant based on games mode, and investigated the properties of game-based cloud-learning system, expecting to help more and more new immigrants in Taiwan. The basic concept for designing the system is developing the learning games network using digital materials, which is applied to the cloud learning platform to attract the immigrant residents and assist them to improve Chinese language skills.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122068819","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Link Prediction Based on Local Information","authors":"Yuxiao Dong, Qing Ke, Bai Wang, Bin Wu","doi":"10.1109/ASONAM.2011.43","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.43","url":null,"abstract":"Link prediction in complex networks is an important issue in graph mining. It aims at estimating the likelihood of the existence of links between nodes by the know network structure information. Currently, most link prediction algorithms based on local information consider only the individual characteristics of common neighbors. In this paper, first, we study the link prediction results as the change of the exponent on the degree of common neighbors, and find some regular pattern between different networks and different exponent. After that, we come up with a new algorithm exploiting the interactions between common neighbors, namely Individual Attraction Index. To reduce the time complexity, we design a simple edition, called Simple Individual Attraction Index. We compare nine well-known local information metrics on eight real networks. The result proves well the best overall performance of these two new algorithms.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129518946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Post-Level Spam Detection for Social Bookmarking Web Sites","authors":"Hsin-Chang Yang, Chung-Hong Lee","doi":"10.1109/ASONAM.2011.81","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.81","url":null,"abstract":"Social book marking Web sites have emerged recently for collecting and sharing of interesting Web sites among users. People can add Web pages to such sites as bookmarks and allow themselves as well as others to manipulate them. One of the key features of the social book marking sites is the ability of annotating a Web page when it is being bookmarked. The annotation usually contains a set of words or phrases, which are collectively known as tags, that could reveal the semantics of the annotated Web page. Efficient and effective search of Web pages can then be achieved via such tags. However, spam tags that are irrelevant to the content of Web pages often appear to deceive other users for malicious or commercial purposes. Various techniques have been devised to tackle such tag spam detection problem. Most of these techniques were able to detect a user that always annotate spam tags. However, finer levels of detection are seldom discussed. In this work, we will propose a method based on a text mining approach to discover the relations between Web pages and there tag posts. These relations are then used to compute the similarity between a Web page and its tag post to decide if it is a spam post. Preliminary experiments show that the accuracy of the post-level spam detection task is 83%.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126986901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Modeling Player Performance in Massively Multiplayer Online Role-Playing Games: The Effects of Diversity in Mentoring Network","authors":"Kyong Jin Shim, Kuo-Wei Hsu, J. Srivastava","doi":"10.1109/ASONAM.2011.113","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.113","url":null,"abstract":"This study investigates and reports preliminary findings on player performance prediction approaches which model player's past performance and social diversity in mentoring network in Ever Quest II, a popular massively multiplayer online role-playing game (MMORPG) developed by Sony Online Entertainment. Our contributions include a better understanding of performance metrics used in the game and a foundation of recommendation systems for mentors and apprentices. We examined three different game servers from the Ever Quest II game logs. In all three servers, the results from our analyses suggest that increase in social diversity in terms of characters and classes encountered moderately negatively correlates with player performance. Based on this finding, we built predictive models to predict player's future performance based on past performance and social diversity in terms of mentoring activities. Our results indicate that 1) models employing past performance and social diversity perform better and 2) prediction for mentors is generally better than that for apprentices.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121545314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Community Detection in Dynamic Social Networks: A Random Walk Approach","authors":"Liang-Cheng Huang, T. Yen, S. Chou","doi":"10.1109/ASONAM.2011.77","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.77","url":null,"abstract":"This study aims to tackling community detection problems in dynamic social networks. The main approach focuses on exploring the idea of random walk in formulating modularity functions for community detection. Under this approach, a modularity function is defined as the difference between the probability of a Markov chain induced by a community and the probability of a null model that assumes no detectable community structure exists in the network. In this paper, we demonstrate the modularity-based approach by applying it to identify group boundaries in an adolescence friendship networks spanning a period of five months. Results and future directions will be discussed.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126371012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Applying Link Prediction to Ranking Candidates for High-Level Government Post","authors":"Jyishane Liu, Ke-Chih Ning","doi":"10.1109/ASONAM.2011.54","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.54","url":null,"abstract":"The main focus of this study is the computational evaluation of candidacy for an executive vacancy. We identified a new problem framework on bureaucratic promotion and proposed to tackle the problem with social network analysis that involved bipartite graph and link prediction. A bureaucratic career bipartite network model was developed to encode key information reflecting a candidate's service merit and the aggregated merit standards of an executive position. This allowed us to approximate merit measurement with node similarity. We implemented this candidacy evaluation approach and conducted experiments with data from Taiwan's bureaucratic career database. Empirical evaluation shows acceptable baseline performance and demonstrates feasibility of the link prediction approach to candidacy ranking. The results also seem to indicate that bureaucratic promotion for executive positions in Taiwan government is mostly a merit system, as opposed to at-will.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126526129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Finding and Matching Communities in Social Networks Using Data Mining","authors":"Slah Alsaleh, R. Nayak, Yue Xu","doi":"10.1109/ASONAM.2011.90","DOIUrl":"https://doi.org/10.1109/ASONAM.2011.90","url":null,"abstract":"The rapid growth in the number of users using social networks and the information that a social network requires about their users make the traditional matching systems insufficiently adept at matching users within social networks. This paper introduces the use of clustering to form communities of users and, then, uses these communities to generate matches. Forming communities within a social network helps to reduce the number of users that the matching system needs to consider, and helps to overcome other problems from which social networks suffer, such as the absence of user activities' information about a new user. The proposed system has been evaluated on a dataset obtained from an online dating website. Empirical analysis shows that accuracy of the matching process is increased using the community information.","PeriodicalId":416479,"journal":{"name":"2011 International Conference on Advances in Social Networks Analysis and Mining","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121710969","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}