2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing最新文献_第3页

On the Predictability of Human Contacts: Influence Factors and the Strength of Stronger Ties 人际交往的可预测性:影响因素与强关系的强度

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.49

Christoph Scholz, M. Atzmüller, Gerd Stumme

引用次数: 49

Modeling the Risk & Utility of Information Sharing in Social Networks 建模风险& &;社会网络中信息共享的效用

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.131

Mohamed R. Fouad, Khaled M. Elbassioni, E. Bertino

{"title":"Modeling the Risk & Utility of Information Sharing in Social Networks","authors":"Mohamed R. Fouad, Khaled M. Elbassioni, E. Bertino","doi":"10.1109/SocialCom-PASSAT.2012.131","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.131","url":null,"abstract":"With the widespread of social networks, the risk of information sharing has become inevitable. Sharing a user's particular information in social networks is an all-or-none decision. Users receiving friendship invitations from others may decide to accept this request and share their information or reject it in which case none of their information will be shared. Access control in social networks is a challenging topic. Social network users would want to determine the optimum level of details at which they share their personal information with other users based on the risk associated with the process. In this paper, we formulate the problem of data sharing in social networks using two different models: (i) a model based on emph{diffusion kernels}, and (ii) a model based on access control. We show that it is hard to apply the former in practice and explore the latter. We prove that determining the optimal levels of information sharing is an NP-hard problem and propose an approximation algorithm that determines to what extent social network users share their own information. We propose a trust-based model to assess the risk of sharing sensitive information and use it in the proposed algorithm. Moreover, we prove that the algorithm could be solved in polynomial time. Our results rely heavily on adopting the super modularity property of the risk function, which allows us to employ techniques from convex optimization. To evaluate our model, we conduct a user study to collect demographic information of several social networks users and get their perceptions on risk and trust. In addition, through experimental studies on synthetic data, we compare our proposed algorithm with the optimal algorithm both in terms of risk and time. We show that the proposed algorithm is scalable and that the sacrifice in risk is outweighed by the gain in efficiency.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116354009","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}

引用次数: 4

Towards an Identity-Based Data Model for an Automotive Privacy Process 基于身份的汽车隐私处理数据模型研究

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.87

Naim Asaj, Björn Wiedersheim, A. Held, M. Weber

引用次数: 1

Some Uses of Head Tilts and Shoulder Shrugs during Human Interaction, and Their Relation to Stancetaking 在人际交往中，头部倾斜和肩部耸肩的一些用法及其与站立的关系

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SOCIALCOM-PASSAT.2012.136

C. Debras, A. Cienki

引用次数: 23

Tagger: Bringing Real World Graffiti Social Interaction to Virtual San Francisco Tagger:将真实世界的涂鸦社交互动带到虚拟的旧金山

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.116

Carmen E. Au, Ray Rischpater, Chris Mockus, Jason Wither, D. Zucker

{"title":"Tagger: Bringing Real World Graffiti Social Interaction to Virtual San Francisco","authors":"Carmen E. Au, Ray Rischpater, Chris Mockus, Jason Wither, D. Zucker","doi":"10.1109/SocialCom-PASSAT.2012.116","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.116","url":null,"abstract":"We present Tagger, a game designed to reproduce the social interactions of graffiti lifestyle in a geo-accurate virtual mirror world. Players interact by placing user-generated artwork on photo realistic panoramas of the city of San Francisco. Tagger is unique in the scope and accuracy to which it reproduces an entire city in a virtual environment. We present our design, implementation experience, and results from two user studies. We show that real world graffiti social interactions occurred in our mirror world despite limitations with our first generation game play rules that inadvertently disincentivized this behavior. We also show that setting the game in a mirror of the real world contributes to player's enjoyment and choice of strategies. We expect Tagger will continue to serve as a powerful research platform as we investigate broader questions around how the virtual mirror world, perhaps combined with augmented reality technology, can extend social interactions beyond what is possible in today's physical world of graffiti.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126813531","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}

引用次数: 0

Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures 大规模社交网络的快速生成，同时包含传递闭包

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.130

Joseph J. Pfeiffer, T. L. Fond, Sebastián Moreno, Jennifer Neville

{"title":"Fast Generation of Large Scale Social Networks While Incorporating Transitive Closures","authors":"Joseph J. Pfeiffer, T. L. Fond, Sebastián Moreno, Jennifer Neville","doi":"10.1109/SocialCom-PASSAT.2012.130","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.130","url":null,"abstract":"A key challenge in the social network community is the problem of network generation - that is, how can we create synthetic networks that match characteristics traditionally found in most real world networks? Important characteristics that are present in social networks include a power law degree distribution, small diameter, and large amounts of clustering. However, most current network generators, such as the Chung Lu and Kronecker models, largely ignore the clustering present in a graph and focus on preserving other network statistics, such as the power law distribution. Models such as the exponential random graph model have a transitivity parameter that can capture clustering, but they are computationally difficult to learn, making scaling to large real world networks intractable. In this work, we propose an extension to the Chung Lu random graph model, the Transitive Chung Lu (TCL) model, which incorporates the notion transitive edges. Specifically, it combines the standard Chung Lu model with edges that are formed through transitive closure (e.g., by connecting a 'friend of a friend'). We prove TCL's expected degree distribution is equal to the degree distribution of the original input graph, while still providing the ability to capture the clustering in the network. The single parameter required by our model can be learned in seconds on graphs with millions of edges, networks can be generated in time that is linear in the number of edges. We demonstrate the performance of TCL on four real-world social networks, including an email dataset with hundreds of thousands of nodes and millions of edges, showing TCL generates graphs that match the degree distribution, clustering coefficients and hop plots of the original networks.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127939956","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}

引用次数: 37

A Secure Group Collaboration Protocol for Nonverbal Human Social Signals Featuring Deception Detection 基于欺骗检测的非语言人类社会信号安全群体协作协议

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.21

Munene W. Kanampiu, J. Zhan, Jinsuk Baek

{"title":"A Secure Group Collaboration Protocol for Nonverbal Human Social Signals Featuring Deception Detection","authors":"Munene W. Kanampiu, J. Zhan, Jinsuk Baek","doi":"10.1109/SocialCom-PASSAT.2012.21","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.21","url":null,"abstract":"Non-verbal human social signals have emerged as an important area of study including the analysis of human deception. The ability to credibly detect truth and deception can be critical today especially due to the wave of terrorism acts and illegal immigration upheavals just to mention a few instances where individuals might not be forthright with their information. Unlike for non-verbal human social signals, with other regular data many networked groups are collaboratively sharing data in order to achieve broader and more comprehensive results. To overcome the inherent danger of data exposure in groups with potential semi-honest participants, measures have been introduced to ensure privacy, integrity, and security in such collaborative exchanges. We do notice, however, that sharing of non-verbal human social signals data is lagging behind in such sharing. As this form of data is growing rapidly and prominently, we propose a protocol that extends group sharing of such data featuring human deception detection social signals among collaborative partners. The protocol will provide privacy, integrity, and security of the data during these exchanges.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132269797","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}

引用次数: 2

Characterizing Urban Landscapes Using Geolocated Tweets 使用地理定位推文描述城市景观

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.19

V. Frías-Martínez, Víctor Soto, Heath Hohwald, E. Frías-Martínez

{"title":"Characterizing Urban Landscapes Using Geolocated Tweets","authors":"V. Frías-Martínez, Víctor Soto, Heath Hohwald, E. Frías-Martínez","doi":"10.1109/SocialCom-PASSAT.2012.19","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.19","url":null,"abstract":"The pervasiveness of cell phones and mobile social media applications is generating vast amounts of geolocalized user-generated content. Since the addition of geotagging information, Twitter has become a valuable source for the study of human dynamics. Its analysis is shedding new light not only on understanding human behavior but also on modeling the way people live and interact in their urban environments. In this paper, we evaluate the use of geolocated tweets as a complementary source of information for urban planning applications. Our contributions are focussed in two urban planing areas: (1) a technique to automatically determine land uses in a specific urban area based on tweeting patterns, and (2) a technique to automatically identify urban points of interest as places with high activity of tweets. We apply our techniques in Manhattan (NYC) using 49 days of geolocated tweets and validate them using land use and landmark information provided by various NYC departments. Our results indicate that geolocated tweets are a powerful and dynamic data source to characterize urban environments.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128398306","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}

引用次数: 206

Task-Oriented Social Ego Network Generation via Dynamic Collaborator Selection 基于动态合作者选择的任务导向社会自我网络生成

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.46

Xing Fang, J. Zhan

引用次数: 2

The Impact of Communication Structure and Interpersonal Dependencies on Distributed Teams 沟通结构和人际依赖对分布式团队的影响

2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing Pub Date : 2012-09-03 DOI: 10.1109/SocialCom-PASSAT.2012.117

T. L. Fond, D. Roberts, Jennifer Neville, James Tyler, Stacey L. Connaughton

{"title":"The Impact of Communication Structure and Interpersonal Dependencies on Distributed Teams","authors":"T. L. Fond, D. Roberts, Jennifer Neville, James Tyler, Stacey L. Connaughton","doi":"10.1109/SocialCom-PASSAT.2012.117","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.117","url":null,"abstract":"In the past decade, we have witnessed an explosive growth of the Web, online communities, and social media. This has led to a substantial increase in the range and scope of electronic communication and distributed collaboration. In distributed teams, social communication is thought to be critical for creating and sustaining relationships, but there is often limited opportunity for team members to build interpersonal connections through face to face interactions. Although social science research has examined some relational aspects of distributed teams, this work has only recently begun to explore the potentially complex relationship between communication, interpersonal relationship formation, and the effectiveness of distributed teams. In this work, we analyze data from an experimental study comparing distributed and co-located teams of undergraduates working to solve logic problems. We use a combined set of tools, including statistical analysis, social network analysis, and machine learning, to analyze the influence of interpersonal communication on the effectiveness of distributed and co-located teams. Our results indicate there are significant differences in participants' self- and group perceptions with respect to: (i) distributed vs. co-located settings, and (ii) communication structures within the team.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-09-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128428202","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}

引用次数: 4