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

{"title":"How Are You Related? Predicting the Type of a Social Relationship Using Call Graph Data","authors":"Krishna Janakiraman, Sara Gatmir-Motahari","doi":"10.1109/SocialCom-PASSAT.2012.79","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.79","url":null,"abstract":"Social relationships defined by phone calls made between people can be grouped into various relationship types or categories, such as family members, co-workers, etc. We propose and evaluate a method that predicts the \"relationship type\" between a pair of mobile phone subscribers using features that abstract their communication behavior and social network patterns. Our dataset consists of call detail records of a major wireless carrier sampled from four demographically diverse regions, from which we built a directed social graph, with over 200,000 vertices and 400,000 edges. Using account and subscription plan information, we labeled each edge in the graph as one of the following four relationships: family, co-worker, customer and service. Our analysis of the dataset shows that these four relationship types exhibit distinct communication behavior patterns and generate characteristic topological features on the social network surrounding the pairs. For instance, subscriber pairs with a family relationship generate high average number of calls, have low call duration, call more frequently and share more mutual contacts than pairs with a service or co-worker relationship. Using a set of features that abstract these characteristics and the Random Forest supervised machine learning classifier, we demonstrate that it is possible to predict the relationship type between a subscriber pair with an accuracy of 87%.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"118 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":"124206360","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":"Can You Believe an Anonymous Contributor? On Truthfulness in Yahoo! Answers","authors":"D. Pelleg, E. Yom-Tov, Y. Maarek","doi":"10.1109/SocialCom-PASSAT.2012.13","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.13","url":null,"abstract":"Internet users notoriously take an assumed identity or masquerade as someone else, for reasons such as financial profit or social benefit. But often the converse is also observed, where people choose to reveal true features of their identity, including deeply intimate details. This work attempts to explore several of the conditions that allow this to happen by analyzing the content generated by these users. We examine multiple social media on the Web, specifically focusing on Yahoo! Answers, encompassing more than a billion answers posted since 2006. Our analysis covers discussions of personal topics such as body measurements and income, and of socially sensitive subjects such as sexual behaviors. We offer quantitative proof that people are aware of the fact that they are posting sensitive information, and yet provide accurate information to fulfill specific information needs. Our analysis further reveals that on community question answering sites, when users are truthful, their expectation of an accurate answer is met.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"21 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":"121447752","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":"Psychological Aspects of Social Communities","authors":"Adrien Friggeri, R. Lambiotte, Michal Kosinskihttps://www.semanticscholar.org/me/account, E. Fleury","doi":"10.1109/SOCIALCOM-PASSAT.2012.104","DOIUrl":"https://doi.org/10.1109/SOCIALCOM-PASSAT.2012.104","url":null,"abstract":"Social Network Analysis has often focused on the structure of the network without taking into account the characteristics of the individual involved. In this work, we aim at identifying how individual differences in psychological traits affect the community structure of social networks. Instead of choosing to study only either structural or psychological properties of an individul, our aim is to exhibit in which way the psychological attributes of interacting individuals impacts the social network topology. Using psychological data from the my Personality application and social data from Facebook, we confront the personality traits of the subjects to metrics obtained after applying the C3 community detection algorithm to the social neighborhood of the subjects. We observe that introverts tend to have less communities and hide into large communities, whereas extroverts tend to act as bridges between more communities, which are on average smaller and of varying cohesion.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"7 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":"132709031","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":"How Do We React to Context? Annotation of Individual and Group Engagement in a Video Corpus","authors":"Francesca Bonin, Ronald Böck, N. Campbell","doi":"10.1109/SocialCom-PASSAT.2012.110","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.110","url":null,"abstract":"One of the main challenges of recent years is to create socially intelligent machines: machines able not only to communicate but also to understand social signals and make sense of the various social contexts. In this paper we describe a new annotation method for the analysis of involvement, aiming at exploring the relation between the individual and the social context in terms of perceived involvement, starting from the idea that the group is more than the sum of its parts. We present a description of the annotation method and preliminary results of an analysis of a multi-party casual conversation extracted from a multimedia multimodal corpus. The work aims to explore the mechanisms by which we react to social context so that we can develop automatic dialogue systems that are able to adapt to their environment in a similar way.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"74 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":"130106759","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":"Privacy-Preserving Techniques and System for Streaming Databases","authors":"Anderson Santana de Oliveira, F. Kerschbaum, Hoonwei Lim, Su-Yang Yu","doi":"10.1109/SocialCom-PASSAT.2012.85","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.85","url":null,"abstract":"Streaming databases and other distributed, event-based systems are very useful tools for business and security applications. When event sources and event processing are distributed across multiple distinct domains, confidentiality and privacy issues emerge. These can be addressed by a number of cryptographic techniques. In this paper we consider high-performance symmetric encryption techniques. We build a system for privacy-preserving event correlation and evaluate the performance of the its techniques. We demonstrate efficient privacy-preserving event correlation using equality tests, greater-than comparisons and range queries. The results indicate that in comparable settings, it is therefore recommended to employ these techniques to address pertinent security and privacy concerns.","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":"130471600","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":"Actionable Information during Extreme Events -- Case Study: Warnings and 2011 Tohoku Earthquake","authors":"Yulia Tyshchuk, W. Wallace","doi":"10.1109/SocialCom-PASSAT.2012.77","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.77","url":null,"abstract":"Social media is rapidly becoming an integral part of modern society. People use social media as a channel of communications with each other, a targeted group or a general public. Concurrently, researchers are studying this channel of communications in an attempt to link the characteristics of the message, such as content, sender-receiver, etc. to the behavior of those using this media. The focus of the research reported herein is to analyze human behavior in response to actionable information in the context of an extreme event. A specific case of actionable information presented in this paper is recommendations to take actions to reduce the chance of harm from the consequences of an extreme event i.e. an alert or warning. Authorized officials via multiple channels of communication issue the warnings to the public. At present, social media is not used universally as an official channel of communication. There is still no clear consensus among emergency management organizations on how the social media can be utilized to disseminate warnings to the public. The first step is to understand people's behaviors on social media in response to actionable information during extreme events. In order to understand people's behaviors on social media, we need to understand the content of their messages and how the messages travel through social media. The paper focuses on identifying hidden key actors (individual/organizations) using advanced social network analysis techniques. Additionally, the paper examines the formation of the cohesive groups in the network and the role of the key actors in those groups. Our conclusion is that the key actors play an important role in diffusion of actionable information. The diffusion begins with central and prominent actors and diffuses through the `gatekeepers' of information to the rest of the network. The key actors exhibit intentions to take a prescribed action and urge others to do so. Finally, the key actors play in important role of bridging cohesive groups in the network in order to facilitate the diffusion of actionable information.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"3 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":"131742791","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":"Flash: Efficient, Stable and Optimal K-Anonymity","authors":"F. Kohlmayer, F. Prasser, C. Eckert, A. Kemper, K. Kuhn","doi":"10.1109/SocialCom-PASSAT.2012.52","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.52","url":null,"abstract":"K-anonymization is an important technique for the de-identification of sensitive datasets. In this paper, we briefly describe an implementation framework which has been carefully engineered to meet the needs of an important class of k-anonymity algorithms. We have implemented and evaluated two major well-known algorithms within this framework and show that it allows for highly efficient implementations. Regarding their runtime behaviour, we were able to closely reproduce the results from previous publications but also found some algorithmic limitations. Furthermore, we propose a new algorithm that achieves very good performance by implementing a novel strategy and exploiting different aspects of our implementation framework. In contrast to the current state-of-the-art, our algorithm offers algorithmic stability, with execution time being independent of the actual representation of the input data. Experiments with different real-world datasets show that our solution clearly outperforms the previous algorithms.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"11 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":"117284580","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":"Pedagogical Stance: The Teacher's Position and Its Social Signals","authors":"Francesca D’Errico, G. Leone, I. Poggi","doi":"10.1109/SOCIALCOM-PASSAT.2012.121","DOIUrl":"https://doi.org/10.1109/SOCIALCOM-PASSAT.2012.121","url":null,"abstract":"The work defines the notion of \"pedagogical stance\", viewed as the type of position taken, the role assumed, the image projected and the type of social behavior performed by a teacher in his/her teaching interaction with a pupil. At any moment while interacting with pupil(s), a teacher takes a \"didactic\" stance, concerning his/her cognitive work on the student, how s/he intends to bring about his/her learning, and an \"affective -- relational\" stance, the type of relationship s/he wants to entertain with the pupil and the type of emotions she tends to elicit in him/her or by which s/he colors interaction. Two types of \"didactic\" stance (maieutic and efficient) and four types of \"affective -- relational\" stance (friendly, dominating, warm dominating, and secure base) are distinguished, their typical verbal and multimodal social signals are singled out, and a study is presented to detect stances from these social signals in 21 teacher-pupil interactions.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"58 2 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":"134175641","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":"Measuring Pair-Wise Social Influence in Microblog","authors":"Zibin Yin, Ya Zhang","doi":"10.1109/SocialCom-PASSAT.2012.10","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.10","url":null,"abstract":"The development of Microblog services has created an unprecedented opportunity for people to share information. To better understand the information propagation behaviors in such social networks, an important task is to measure the influence among users. A number of previous works measure users' influence through analyzing the network characteristics or by retweet rate. However, high in degree not necessarily means influential and retweet rate fluctuates over time. In this paper, we propose a user interaction model in microblog by considering the following three key factors: user's active level, user's willingness to retweet, and the influence between a pair of users. One advantage of this model is that the model fitting only requires a sub graph and hence may be performed in a piece-wise fashion. Furthermore, we can find the users with potential influence in the network. We fit the model with a Sina Microblog dataset. We show that this model is able to predict influence at high accuracy. Moreover, this model can be used to predicting retweet rate and finding influential users.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"219 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":"132724394","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":"Privacy Threats Related to User Profiling in Online Social Networks","authors":"Fredrik Erlandsson, Martin Boldt, H. Johnson","doi":"10.1109/SocialCom-PASSAT.2012.16","DOIUrl":"https://doi.org/10.1109/SocialCom-PASSAT.2012.16","url":null,"abstract":"The popularity of Online Social Networks (OSNs) has increased the visibility of users profiles and interactions performed between users. In this paper we structure different privacy threats related to OSNs and describe six different types of privacy threats. One of these threats, named public information harvesting, is previously not documented so we therefore present it in further detail by also presenting the results from a proof-of-concept implementation of that threat. The basis of the attack is gathering of user interactions from various open groups on Facebook which then is transformed into a social interaction graph. Since the data gathered from the OSN originates from open groups it could be executed by any third-party connected to the Internet independently of the users' privacy settings. In addition to presenting the different privacy threats we also we propose a range of different protection techniques.","PeriodicalId":129526,"journal":{"name":"2012 International Conference on Privacy, Security, Risk and Trust and 2012 International Confernece on Social Computing","volume":"37 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":"133294575","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}