Conference on Online Social Networks最新文献_第4页

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512944

E. Cohen, D. Delling, Fabian Fuchs, A. Goldberg, M. Goldszmidt, Renato F. Werneck

{"title":"Scalable similarity estimation in social networks: closeness, node labels, and random edge lengths","authors":"E. Cohen, D. Delling, Fabian Fuchs, A. Goldberg, M. Goldszmidt, Renato F. Werneck","doi":"10.1145/2512938.2512944","DOIUrl":"https://doi.org/10.1145/2512938.2512944","url":null,"abstract":"Similarity estimation between nodes based on structural properties of graphs is a basic building block used in the analysis of massive networks for diverse purposes such as link prediction, product recommendations, advertisement, collaborative filtering, and community discovery. While local similarity measures, based on properties of immediate neighbors, are easy to compute, those relying on global properties have better recall. Unfortunately, this better quality comes with a computational price tag. Aiming for both accuracy and scalability, we make several contributions. First, we define closeness similarity, a natural measure that compares two nodes based on the similarity of their relations to all other nodes. Second, we show how the all-distances sketch (ADS) node labels, which are efficient to compute, can support the estimation of closeness similarity and shortest-path (SP) distances in logarithmic query time. Third, we propose the randomized edge lengths (REL) technique and define the corresponding REL distance, which captures both path length and path multiplicity and therefore improves over the SP distance as a similarity measure. The REL distance can also be the basis of closeness similarity and can be estimated using SP computation or the ADS labels. We demonstrate the effectiveness of our measures and the accuracy of our estimates through experiments on social networks with up to tens of millions of nodes.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125324383","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: 32

Call me maybe: understanding nature and risks of sharing mobile numbers on online social networks 或许给我打电话:了解在在线社交网络上分享手机号码的本质和风险

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512959

Prachi Jain, P. Kumaraguru

{"title":"Call me maybe: understanding nature and risks of sharing mobile numbers on online social networks","authors":"Prachi Jain, P. Kumaraguru","doi":"10.1145/2512938.2512959","DOIUrl":"https://doi.org/10.1145/2512938.2512959","url":null,"abstract":"Little research explores the activity of sharing mobile numbers on OSNs, in particular via public posts. In this work, we understand the characteristics and risks of mobile numbers shared on OSNs either via profile or public posts and focus on Indian mobile numbers. We collected 76,347 unique mobile numbers posted by 85,905 users on Twitter and Facebook and analyzed 2,997 numbers, prefixed with +91. We observed that most users shared their own mobile numbers to spread urgent information and to market products, IT facilities and escort business. Users resorted to applications like Twitterfeed and TweetDeck to post and popularize mobile numbers on multiple OSNs. To assess risks associated with mobile numbers exposed on OSNs, we used mobile numbers to gain sensitive information (e.g. name, Voter ID) about their owners. We communicated the observed risks to the owners by calling them on their mobile number. Few users were surprised to know the online presence of their number, while few users intentionally put it online for business purposes. With these observations, we highlight that there is a need to monitor leakage of mobile numbers via profile and public posts. To the best of our knowledge, this is the first exploratory study to critically investigate the exposure of mobile numbers on OSNs.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114730569","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: 10

Ads by whom? ads about what?: exploring user influence and contents in social advertising 谁做的广告?关于什么的广告?:探索社交广告中的用户影响力和内容

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512950

J. Y. Park, Kyoung-Won Lee, Sangyeon Kim, C. Chung

{"title":"Ads by whom? ads about what?: exploring user influence and contents in social advertising","authors":"J. Y. Park, Kyoung-Won Lee, Sangyeon Kim, C. Chung","doi":"10.1145/2512938.2512950","DOIUrl":"https://doi.org/10.1145/2512938.2512950","url":null,"abstract":"Despite the growing interest in using online social networking services (OSNS) for advertising, little is understood about what contributes to the social advertising performance. In this research, we pose following questions: How many clicks do social advertisements actually receive? What are the characteristics of the advertisements that receive many clicks? What factors contribute to the clicks on advertisements? In order to answer these questions, we collect data from AdbyMe, a social media advertisement platform that connects businesses, or advertisers, with users of online social network services. Businesses can reach a large target audience through AdbyMe users who publish the advertisements on their social networks. We analyze the factors that may affect the clicks on advertisements being published on OSNS. In particular, we look into the advertised contents as well as the characteristics of users who publish the advertisements. We find that the traditional advertisement content analysis alone cannot fully explain the effectiveness of social advertisements. More importantly, we discover that in a social advertising paradigm, social influence of a publisher has a strong impact on the number of clicks on the advertisements. Our findings suggest that considering both the advertised contents and the influence of advertising publishers allows better understanding of the social advertisement phenomenon.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"107 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134532435","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: 9

Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo 压力下的推文:分析新浪微博的热门话题和词汇选择的演变

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512940

Le Chen, Chi Zhang, Christo Wilson

{"title":"Tweeting under pressure: analyzing trending topics and evolving word choice on sina weibo","authors":"Le Chen, Chi Zhang, Christo Wilson","doi":"10.1145/2512938.2512940","DOIUrl":"https://doi.org/10.1145/2512938.2512940","url":null,"abstract":"In recent years, social media has risen to prominence in China, with sites like Sina Weibo and Renren each boasting hundreds of millions of users. Social media in China plays a profound role as a platform for breaking news and political commentary that is not available in the state-sanctioned news media. However, like all websites in China, Chinese social media is subject to censorship. Although several studies have identified censorship on Weibo and Chinese blogs, to date no studies have examined the overall impact of censorship on discourse in social media.\u0000 In this study, we examine how censorship impacts discussions on Weibo, and how users adapt to avoid censorship. We gather tweets and comments from 280K politically active Weibo users for 44 days and use NLP techniques to identify trending topics. We observe that the magnitude of censorship varies dramatically across topics, with 82% of tweets in some topics being censored. However, we find that censorship of a topic correlates with high user engagement, suggesting that censorship does not stifle discussion of sensitive topics. Furthermore, we find that users adopt variants of words (known as morphs) to avoid keyword-based censorship. We analyze emergent morphs to learn how they are adopted and spread by the Weibo user community.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128729654","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: 56

Appinspect: large-scale evaluation of social networking apps Appinspect:社交网络应用的大规模评估

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512942

Markus Huber, M. Mulazzani, S. Schrittwieser, E. Weippl

{"title":"Appinspect: large-scale evaluation of social networking apps","authors":"Markus Huber, M. Mulazzani, S. Schrittwieser, E. Weippl","doi":"10.1145/2512938.2512942","DOIUrl":"https://doi.org/10.1145/2512938.2512942","url":null,"abstract":"Third-party apps for social networking sites have emerged as a popular feature for online social networks, and are used by millions of users every day. In exchange for additional features, users grant third parties access to their personal data. However, these third parties do not necessarily protect the data to the same extent as social network providers. To automatically analyze the unique privacy and security issues of social networking applications on a large scale, we propose a novel framework, called AppInspect. Our framework enumerates available social networking apps and collects metrics such as the personal information transferred to third party developers. AppInspect furthermore identifies web trackers, as well as information leaks, and provides insights into the hosting infrastructures of apps. We implemented a prototype of our novel framework to evaluate Facebook's application ecosystem. Our evaluation shows that AppInspect is able to detect malpractices of social networking apps in an automated fashion. During our study we collaborated with Facebook to mitigate shortcomings of popular apps that affected the security and privacy of millions of social networking users.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115533155","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: 26

Social affinity filtering: recommendation through fine-grained analysis of user interactions and activities 社会亲和力过滤:通过细粒度分析用户交互和活动进行推荐

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512947

S. Sedhain, S. Sanner, Lexing Xie, R. Kidd, Khoi-Nguyen Tran, P. Christen

{"title":"Social affinity filtering: recommendation through fine-grained analysis of user interactions and activities","authors":"S. Sedhain, S. Sanner, Lexing Xie, R. Kidd, Khoi-Nguyen Tran, P. Christen","doi":"10.1145/2512938.2512947","DOIUrl":"https://doi.org/10.1145/2512938.2512947","url":null,"abstract":"Content recommendation in social networks poses the complex problem of learning user preferences from a rich and complex set of interactions (e.g., likes, comments and tags for posts, photos and videos) and activities (e.g., favourites, group memberships, interests). While many social collaborative filtering approaches learn from aggregate statistics over this social information, we show that only a small subset of user interactions and activities are actually useful for social recommendation, hence learning which of these are most informative is of critical importance. To this end, we define a novel social collaborative filtering approach termed social affinity filtering (SAF). On a preference dataset of Facebook users and their interactions with 37,000+ friends collected over a four month period, SAF learns which fine-grained interactions and activities are informative and outperforms state-of-the-art (social) collaborative filtering methods by over 6% in prediction accuracy; SAF also exhibits strong cold-start performance. In addition, we analyse various aspects of fine-grained social features and show (among many insights) that interactions on video content are more informative than other modalities (e.g., photos), the most informative activity groups tend to have small memberships, and features corresponding to ``long-tailed'' content (e.g., music and books) can be much more predictive than those with fewer choices (e.g., interests and sports). In summary, this work demonstrates the substantial predictive power of fine-grained social features and the novel method of SAF to leverage them for state-of-the-art social recommendation.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126906821","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: 21

On the performance of percolation graph matching 论渗透图匹配的性能

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512952

Lyudmila Yartseva, M. Grossglauser

{"title":"On the performance of percolation graph matching","authors":"Lyudmila Yartseva, M. Grossglauser","doi":"10.1145/2512938.2512952","DOIUrl":"https://doi.org/10.1145/2512938.2512952","url":null,"abstract":"Graph matching is a generalization of the classic graph isomorphism problem. By using only their structures a graph-matching algorithm finds a map between the vertex sets of two similar graphs. This has applications in the de-anonymization of social and information networks and, more generally, in the merging of structural data from different domains.\u0000 One class of graph-matching algorithms starts with a known seed set of matched node pairs. Despite the success of these algorithms in practical applications, their performance has been observed to be very sensitive to the size of the seed set. The lack of a rigorous understanding of parameters and performance makes it difficult to design systems and predict their behavior.\u0000 In this paper, we propose and analyze a very simple percolation - based graph matching algorithm that incrementally maps every pair of nodes (i,j) with at least r neighboring mapped pairs. The simplicity of this algorithm makes possible a rigorous analysis that relies on recent advances in bootstrap percolation theory for the G(n,p) random graph. We prove conditions on the model parameters in which percolation graph matching succeeds, and we establish a phase transition in the size of the seed set. We also confirm through experiments that the performance of percolation graph matching is surprisingly good, both for synthetic graphs and real social-network data.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127121873","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: 157

Crowd crawling: towards collaborative data collection for large-scale online social networks 人群爬行:面向大规模在线社交网络的协同数据收集

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512958

Cong Ding, Yang Chen, Xiaoming Fu

引用次数: 38

Hierarchical community decomposition via oblivious routing techniques 通过遗忘路由技术进行分层社区分解

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512953

W. Kennedy, Jamie Morgenstern, G. Wilfong, Lisa Zhang

{"title":"Hierarchical community decomposition via oblivious routing techniques","authors":"W. Kennedy, Jamie Morgenstern, G. Wilfong, Lisa Zhang","doi":"10.1145/2512938.2512953","DOIUrl":"https://doi.org/10.1145/2512938.2512953","url":null,"abstract":"The detection of communities in real-world large-scale complex networks is a fundamental step in many applications, such as describing community structure and predicting the dissemination of information. Unfortunately, community detection is a computationally expensive task. Indeed, many approaches with strong theoretic guarantees are infeasible when applied to networks of large scale. Numerous approaches have been designed to scale community detection algorithms, many of which leverage local optimizations or local greedy decisions to iteratively find the communities. Solely relying on local techniques to detect communities, rather than a global objective function, can fail to detect global structure of the network.\u0000 In this work, we instead formulate a notion of a hierarchical community decomposition (HCD), which takes a more global view of hierarchical community structure. Our main contributions are as follows. We formally define a (λ, delta)-HCD where λ parametrizes the connectivity within each sub-community at the same hierarchical level and δ parametrizes the relationship between communities across two consecutive levels. Based on a method of Racke originally designed for oblivious routing, we provide an algorithm to construct a HCD and prove that an (O(log n);O(1))-HCD can always be found for any n-node input graph. Further, our algorithm does not rely on a pre-specified number of communities or depth of decomposition. Since the algorithm is of exponential complexity, we also describe a practical efficient, yet heuristic, implementation and perform an experimental validation on synthetic and real-world networks. We experiment first with synthetic networks with well-defined \"intended\" decompositions, on which we verify the quality of the decompositions produced by our method. Armed with the confidence these positive results provide, we use our implementation to compute the hierarchical community structure of more complex, real-world networks.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125870309","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: 3

Building confederated web-based services with Priv.io 使用privo .io构建基于web的联合服务

Conference on Online Social Networks Pub Date : 2013-10-07 DOI: 10.1145/2512938.2512943

L. Zhang, A. Mislove

{"title":"Building confederated web-based services with Priv.io","authors":"L. Zhang, A. Mislove","doi":"10.1145/2512938.2512943","DOIUrl":"https://doi.org/10.1145/2512938.2512943","url":null,"abstract":"With the increasing popularity of Web-based services, users today have access to a broad range of free sites, including social networking, microblogging, and content sharing sites. In order to offer a service for free, service providers typically monetize user content, selling results to third parties such as advertisers. As a result, users have little control over their data or privacy. A number of alternative approaches to architecting today's Web-based services have been proposed, but they suffer from limitations such as relying the creation and installation of additional client-side software, providing insufficient reliability, or imposing an excessive monetary cost on users.\u0000 In this paper, we present Priv.io, a new approach to building Web-based services that offers users greater control and privacy over their data. We leverage the fact that today, users can purchase storage, bandwidth, and messaging from cloud providers at fine granularity: In Priv.io, each user provides the resources necessary to support their use of the service using cloud providers such as Amazon Web Services. Users still access the service using a Web browser, all computation is done within users' browsers, and Priv.io provides rich and secure support for third-party applications. An implementation demonstrates that Priv.io works today with unmodified versions of common Web browsers on both desktop and mobile devices, is both practical and feasible, and is cheap enough for the vast majority users.","PeriodicalId":304931,"journal":{"name":"Conference on Online Social Networks","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125014994","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: 14