2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)最新文献_第2页

Controlling Internal Structure of Communities on Graph Generator 基于图生成器的群体内部结构控制

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381439

Hiroto Yamaguchi, Yuya Ogawa, Seiji Maekawa, Yuya Sasaki, Makoto Onizuka

引用次数: 3

User Preference Translation Model for Recommendation System with Item Influence Diffusion Embedding 项目影响扩散嵌入推荐系统的用户偏好翻译模型

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381410

Hao-Shang Ma, Jen-Wei Huang

引用次数: 0

Identity Linkage Across Diverse Social Networks 跨越不同社会网络的身份联系

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381445

Youcef Benkhedda, F. Azouaou, Sofiane Abbar

{"title":"Identity Linkage Across Diverse Social Networks","authors":"Youcef Benkhedda, F. Azouaou, Sofiane Abbar","doi":"10.1109/ASONAM49781.2020.9381445","DOIUrl":"https://doi.org/10.1109/ASONAM49781.2020.9381445","url":null,"abstract":"User identity linkage across online social networks has gained a significant interest in the last few years in diverse applications such as data fusion, de-duplication, personalized advertisement, user profiling, and expert recommendation. Existing techniques investigated the use of personal discrete attributes such as user name, gender, location, and email which are not always available. Other techniques explored the use of network relations. In our proposal, we attempt to design a generic framework for user identity linkage across diverse social networks based exclusively on the widely available textual user generated content. We intentionally selected two social networks, Twitter and Quora, which have different contribution models and serve different purposes, and explore different supervised and unsupervised techniques for matching profiles as well as different language models ranging from simple tf*idf vectorization to more sophisticated BERT embeddings. We discuss the limits of different choices and present some encouraging preliminary results. For example, we find that prolific users can be identified with 84% accuracy. We also present a framework we designed to create the largest publicly available annotated dataset for profile linkage in social networks.","PeriodicalId":196317,"journal":{"name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133887813","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

Online feelings and sentiments across Italy during pandemic: investigating the influence of socio-economic and epidemiological variables 大流行期间意大利各地的在线感受和情绪:调查社会经济和流行病学变量的影响

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381463

Francesco Scotti, Davide Magnanimi, V. M. Urbano, Francesco Pierri

{"title":"Online feelings and sentiments across Italy during pandemic: investigating the influence of socio-economic and epidemiological variables","authors":"Francesco Scotti, Davide Magnanimi, V. M. Urbano, Francesco Pierri","doi":"10.1109/ASONAM49781.2020.9381463","DOIUrl":"https://doi.org/10.1109/ASONAM49781.2020.9381463","url":null,"abstract":"During the on-going COVID-19 pandemic, online social media have been extensively used by policy makers and health authorities to quickly disseminate useful information and respond to public concerns in a timely fashion. Notwithstanding the huge amount of literature on analyzing positive and negative emotions conveyed by social media users, researchers have not widely investigated the main determinants of online sentiment during crises. To fill this gap, in this paper we analyse a large-scale dataset of over 1.7 M tweets in order to understand whether online feelings, expressed by Italian individuals on Twitter during the pandemic, have been affected by socio-economic and epidemiological variables. Leveraging both panel models and cross-section regressions at different geographical levels, we find that more pessimistic feelings are communicated by users located in areas where the virus hit more severely, with a higher mortality rate and a larger fraction of infected individuals with respect to the local population. Finally, we show that administrative units exhibiting the most positive emotions are those characterized by lower income per capita and larger socio-economic deprivation, suggesting that sentiments in online conversations could be driven by epidemiological factors and by the fear of economic backlashes in wealthier areas of Italy.","PeriodicalId":196317,"journal":{"name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129370671","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

An Investigation into the Sensitivity of Social Opinion Networks to Heterogeneous Goals and Preferences 社会舆论网络对异质目标和偏好的敏感性研究

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381380

Patrick Shepherd, Mia Weaver, J. Goldsmith

引用次数: 2

International Symposium on Foundations and Applications of Big Data Analytics (FAB 2020) FAB 2020 Symposium Organizing Committee 大数据分析基础与应用国际研讨会(FAB 2020

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/asonam49781.2020.9381464

Mehmet Kaya, Aditya Tulsyan, A. Abraham, B. Javadi, Chao-Tung Yang, H. Mcheick, Hao-peng Chen, H. Mouratidis, Hasan Jamil, H. Ltaief, Kaust Haziq Jeelani, Haziq Jeelani, H. Ramalhinho, H. Hallal, Ioannis Partalas, Iraklis Varlamis, J. Pokorný, J. Darmont, Jinjun Chen, L. Lhotská, Lijun Chang, Linchuan Chen, Liqiang Wang, Simón Bolívar, M. Damiani, M. Berzins, M. Bakhouya, M. Nadif, Mustafa Canim, P. Sutra, Qi Yu, Rafael Tolosana-Calasanz, U. Zaragoza, Rajdeep Bhowmik, Robert C. H. Hsu, Chung-lin Hua, Roberto Di, Pietro Bell, S. Chiusano

{"title":"International Symposium on Foundations and Applications of Big Data Analytics (FAB 2020) FAB 2020 Symposium Organizing Committee","authors":"Mehmet Kaya, Aditya Tulsyan, A. Abraham, B. Javadi, Chao-Tung Yang, H. Mcheick, Hao-peng Chen, H. Mouratidis, Hasan Jamil, H. Ltaief, Kaust Haziq Jeelani, Haziq Jeelani, H. Ramalhinho, H. Hallal, Ioannis Partalas, Iraklis Varlamis, J. Pokorný, J. Darmont, Jinjun Chen, L. Lhotská, Lijun Chang, Linchuan Chen, Liqiang Wang, Simón Bolívar, M. Damiani, M. Berzins, M. Bakhouya, M. Nadif, Mustafa Canim, P. Sutra, Qi Yu, Rafael Tolosana-Calasanz, U. Zaragoza, Rajdeep Bhowmik, Robert C. H. Hsu, Chung-lin Hua, Roberto Di, Pietro Bell, S. Chiusano","doi":"10.1109/asonam49781.2020.9381464","DOIUrl":"https://doi.org/10.1109/asonam49781.2020.9381464","url":null,"abstract":"Bulent Tavli, TOBB University of Science and Economy, Turkey Program Committee Rafael Tolosana-Calasanz, Universidad de Zaragoza Carson Leung, University of Manitoba Christoph Schommer, University of Luxembourg Claudio Sartori, University of Bologna Haopeng Chen, Shanghai Jiao Tong University Fatma Betul Atalay, TOBB University of Economics and Technology Carlos Henggeler Antunes, University of Coimbra Kamen Kanev, Shizuoka University Dana Petcu, West University of Timisoara Brad Malin, Vanderbilt University Paolo Garza, Politecnico di Torino Bahman Javadi, Western Sydney University Weifeng Liu, China University of Petroleum (East China) Antonio Badia, University of Louisville Abdullah Uz Tansel tansel@baruch.cuny.edu City University of New York Aris Gkoulalas-Divanis, IBM Watson Health, Cambridge, MA Aniruddha Bhattacharjya, Tsinghua University, Beijing Xiang Zhao, National University of Defense Technology Zbigniew Ras ras@uncc.edu UNC Charlotte Chao-Tung Yang, Department of Computer Science, Tunghai University Vana Kalogeraki, Athens University of Economics and Business","PeriodicalId":196317,"journal":{"name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115528116","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

Assessing temporal and spatial features in detecting disruptive users on Reddit 评估在Reddit上检测破坏性用户的时间和空间特征

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381426

James R. Ashford, Liam D. Turner, R. Whitaker, A. Preece, Diane H Felmlee

{"title":"Assessing temporal and spatial features in detecting disruptive users on Reddit","authors":"James R. Ashford, Liam D. Turner, R. Whitaker, A. Preece, Diane H Felmlee","doi":"10.1109/ASONAM49781.2020.9381426","DOIUrl":"https://doi.org/10.1109/ASONAM49781.2020.9381426","url":null,"abstract":"Trolling, echo chambers and general suspicious behaviour online are a serious cause of concern due to their potential disruptive effects beyond social media. This motivates a better understanding of the characteristics of disruptive behaviour on the internet and methods of detection. In this work we focus on Reddit which provides a rich social media platform for community focused interactions. Using network representations of user activity alongside temporal statistics and other features we assess the behaviour of a sample of potentially disruptive users, based on their assigned comment karma (an aggregate of a user's comment up-votes), relative to the wider population. We explore how these signals contribute to the accurate prediction of disruptive users, and note that this is achieved without requiring any semantic analysis. Our results show that it is possible to detect signs of disruptive behaviour with good accuracy using limited inputs that are primarily based on the reply patterns that users generate. This is of potential value for large-scale detection problems and operation across different languages.","PeriodicalId":196317,"journal":{"name":"2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124328201","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

Dynamic Analysis of the Global Financial Network 全球金融网络的动态分析

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381345

Sergey Shvydun

引用次数: 0

Analysing Digital Banking Reviews Using Text Mining 使用文本挖掘分析数字银行评论

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381429

L. Cheng, Legaspi Rhea Sharmayne

引用次数: 5

Hot Topics Detection by Using 2-Layers Keywords Extraction 基于两层关键词提取的热点话题检测

2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2020-12-07 DOI: 10.1109/ASONAM49781.2020.9381308

I. Ting, SungMin Yang, Chia-Sung Yen, Tsung-Hsing Tsai

引用次数: 2