2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)最新文献_第7页

Modeling individuals and making recommendations using multiple social networks 对个人进行建模并使用多个社交网络提出建议

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2808898

Makbule Gülçin Özsoy, Faruk Polat, R. Alhajj

{"title":"Modeling individuals and making recommendations using multiple social networks","authors":"Makbule Gülçin Özsoy, Faruk Polat, R. Alhajj","doi":"10.1145/2808797.2808898","DOIUrl":"https://doi.org/10.1145/2808797.2808898","url":null,"abstract":"Web-based platforms, such as social networks, review web-sites, and e-commerce web-sites, commonly use recommendation systems to serve their users. The common practice is to have each platform captures and maintains data related to its own users. Later the data is analyzed to produce user specific recommendations. We argue that recommendations could be enriched by considering data consolidated from multiple sources instead of limiting the analysis to data captured from a single source. Integrating data from multiple sources is analogous to watching the behavior and preferences of each user on multiple platforms instead of a limited one platform based vision. Motivated by this, we developed a recommendation framework which utilizes user specific data collected from multiple platforms. To the best of our knowledge, this is the first work aiming to make recommendations by consulting multiple social networks to produce a rich modeling of user behavior. For this purpose, we collected and anonymized a specific dataset that contains information from BlogCatalog, Twitter and Flickr web-sites. We implemented several different types of recommendation methodologies to observe their performances while using single versus multiple features from a single source versus multiple sources. The conducted experiments showed that using multiple features from multiple social networks produces a wider perspective of user behavior and preferences leading to improved recommendation outcome.","PeriodicalId":371988,"journal":{"name":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130645499","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

Policy oriented exchange networks: Was a copenhagen climate treaty possible? Scientific analysis providing new insights for agreement and a better treaty for the planet 政策导向的交流网络:哥本哈根气候条约可能达成吗?科学分析为达成协议和为地球制定更好的条约提供了新的见解

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2808911

F. Stokman

引用次数: 1

The influence of social status on consensus building in collaboration networks 社会地位对协作网络共识构建的影响

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2808887

Ilire Hasani-Mavriqi, Florian Geigl, S. Pujari, E. Lex, D. Helic

{"title":"The influence of social status on consensus building in collaboration networks","authors":"Ilire Hasani-Mavriqi, Florian Geigl, S. Pujari, E. Lex, D. Helic","doi":"10.1145/2808797.2808887","DOIUrl":"https://doi.org/10.1145/2808797.2808887","url":null,"abstract":"In this paper, we analyze the influence of social status on opinion dynamics and consensus building in collaboration networks. To that end, we simulate the diffusion of opinions in empirical collaboration networks by taking into account both the network structure and the individual differences of people reflected through their social status. For our simulations, we adapt a well-known Naming Game model and extend it with the Probabilistic Meeting Rule to account for the social status of individuals participating in a meeting. This mechanism is sufficiently flexible and allows us to model various situations in collaboration networks, such as the emergence or disappearance of social classes. In this work, we concentrate on studying three well-known forms of class society: egalitarian, ranked and stratified. In particular, we are interested in the way these society forms facilitate opinion diffusion. Our experimental findings reveal that (i) opinion dynamics in collaboration networks is indeed affected by the individuals' social status and (ii) this effect is intricate and non-obvious. In particular, although the social status favors consensus building, relying on it too strongly can slow down the opinion diffusion, indicating that there is a specific setting for each collaboration network in which social status optimally benefits the consensus building process.","PeriodicalId":371988,"journal":{"name":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131208070","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

EnTwine: Feature analysis and candidate selection for social user identity aggregation 社交用户身份聚合的特征分析与候选选择

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809340

Niyati Chhaya, Dhwanit Agarwal, Nikaash Puri, Paridhi Jain, Deepak Pai, P. Kumaraguru

引用次数: 2

Interaction prediction in dynamic networks exploiting community discovery 基于社区发现的动态网络交互预测

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809401

Giulio Rossetti, Riccardo Guidotti, Diego Pennacchioli, D. Pedreschi, F. Giannotti

引用次数: 22

Human behaviour in different social medias: A case study of Twitter and Disqus 不同社交媒体中的人类行为:以Twitter和Disqus为例

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809395

H. Maruf, Nagib Meshkat, Mohammed Eunus Ali, J. Mahmud

{"title":"Human behaviour in different social medias: A case study of Twitter and Disqus","authors":"H. Maruf, Nagib Meshkat, Mohammed Eunus Ali, J. Mahmud","doi":"10.1145/2808797.2809395","DOIUrl":"https://doi.org/10.1145/2808797.2809395","url":null,"abstract":"Contemporary modern world has witnessed the widespread emergence of online social media and similar technologies. Peoples' behaviour over different social network platform has become an interesting topic of research. In this study, we investigate whether people express analogous identity over different platforms and analysis of different social platform usage contributes to reveal more of a person. We analyse people's usage pattern in two major online platforms, the most widely used social media platform Twitter and a major online commenting platform Disqus. We extract linguistic features and infer personality traits from both of these platforms. Our study reveals differential relationship between personality traits and Disqus and Twitter usage. We also find that social media has an influence on a person's discussion topic. People share opinion on varieties of topics and entities exclusively in Twitter and Disqus. Moreover Disqus provides stronger assessment of a person's sentiment over a topic or entity. Combination of these two profiles gives an extensive view of a user's interest and sensitivity which justify the inference that people use different social network for different purposes and single social network analysis is not enough to build a comprehensive virtual identity of a person.","PeriodicalId":371988,"journal":{"name":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134214511","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

Finding the right social media site for questions 找到适合提问的社交媒体网站

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809391

Zhen Yang, Isaac Jones, Xia Hu, Huan Liu

引用次数: 7

Networking in child exploitation — Assessing disruption strategies using registrant information 儿童剥削中的网络-利用注册者信息评估破坏策略

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809297

Russell Allsup, E. Thomas, Bryan Monk, Richard Frank, M. Bouchard

{"title":"Networking in child exploitation — Assessing disruption strategies using registrant information","authors":"Russell Allsup, E. Thomas, Bryan Monk, Richard Frank, M. Bouchard","doi":"10.1145/2808797.2809297","DOIUrl":"https://doi.org/10.1145/2808797.2809297","url":null,"abstract":"This research utilizes social network analysis to determine the success of three different disruption strategies on a child exploitation network extracted from the public internet. Using a custom-written web-crawler called LECEN, data from a set of hyperlinked child-exploitation websites was collected from the Internet. From these data, two types of networks were coded: the nodes of the first network consisted of only website domains, while the nodes of the second were generated using the registrant data, where the nodes represented the legal owners of those same domains. Three attack scenarios were carried out on these two networks: two types of hub attacks (one focused on in-degree and one focused on out-degree) and a bridge attack. Using these disruption strategies, it was found that bridge attacks were more suitable for disrupting the domain networks, while both hub-attacks could be favored when disrupting the network of registrants. These findings have implications for law enforcement, as it provides real-world applications to disruption where registrants may be targeted directly.","PeriodicalId":371988,"journal":{"name":"2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"511 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123904843","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

Time evolution of the importance of nodes in dynamic networks 动态网络中节点重要性的时间演化

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809322

Clémence Magnien, Fabien Tarissan

引用次数: 24

Privacy preservation in social networks through alpha — Anonymization techniques 通过alpha -匿名化技术保护社交网络中的隐私

2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2015-08-25 DOI: 10.1145/2808797.2809354

Saptarshi Chakraborty, B. Tripathy

引用次数: 3