2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)最新文献_第2页

Five Shades of Untruth: Finer-Grained Classification of Fake News 不真实的五种色调:假新闻的细粒度分类

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508256

Liqiang Wang, Yafang Wang, Gerard de Melo, G. Weikum

引用次数: 15

Social-EOC: Serviceability Model to Rank Social Media Requests for Emergency Operation Centers Social- eoc:对紧急行动中心的社交媒体请求进行排序的可服务性模型

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508709

Hemant Purohit, C. Castillo, Muhammad Imran, Rahul Pandey

{"title":"Social-EOC: Serviceability Model to Rank Social Media Requests for Emergency Operation Centers","authors":"Hemant Purohit, C. Castillo, Muhammad Imran, Rahul Pandey","doi":"10.1109/ASONAM.2018.8508709","DOIUrl":"https://doi.org/10.1109/ASONAM.2018.8508709","url":null,"abstract":"The public expects a prompt response from emergency services to address requests for help posted on social media. However, the information overload of social media experienced by these organizations, coupled with their limited human resources, challenges them to timely identify and prioritize critical requests. This is particularly acute in crisis situations where any delay may have a severe impact on the effectiveness of the response. While social media has been extensively studied during crises, there is limited work on formally characterizing serviceable help requests and automatically prioritizing them for a timely response. In this paper, we present a formal model of serviceability called Social-EOC (Social Emergency Operations Center), which describes the elements of a serviceable message posted in social media that can be expressed as a request. We also describe a system for the discovery and ranking of highly serviceable requests, based on the proposed serviceability model. We validate the model for emergency services, by performing an evaluation based on real-world data from six crises, with ground truth provided by emergency management practitioners. Our experiments demonstrate that features based on the serviceability model improve the performance of discovering and ranking (nDCG up to 25%) service requests over different baselines. In the light of these experiments, the application of the serviceability model could reduce the cognitive load on emergency operation center personnel, in filtering and ranking public requests at scale.","PeriodicalId":135949,"journal":{"name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126215328","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: 33

Local Detection of Critical Nodes in Active Graphs 活动图中关键节点的局部检测

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508323

M. Özkaya, Ahmet Erdem Sanyuce, A. Pınar, Ümit V. Çatalyürek

{"title":"Local Detection of Critical Nodes in Active Graphs","authors":"M. Özkaya, Ahmet Erdem Sanyuce, A. Pınar, Ümit V. Çatalyürek","doi":"10.1109/ASONAM.2018.8508323","DOIUrl":"https://doi.org/10.1109/ASONAM.2018.8508323","url":null,"abstract":"The identification of critical nodes in a graph is a fundamental task in network analysis. Centrality measures are commonly used for this purpose. These methods rely on two assumptions that restrict their applicability. First, they only depend on the topology of the network and do not consider the activity over the network. Second, they assume the entire network is available. However, in many applications, it is the underlying activity of the network such as interactions and communications that makes a node critical, and it is hard to collect the entire network topology, when the network is vast and autonomous. We propose a new measure, Active Betweenness Cardinality, where the importance of the nodes are based not on the static structure, but the active utilization of the network. We show how this metric can be computed efficiently by only local information for a given node and how we can locate the critical nodes by using only a few nodes. We also show how this metric can be used to monitor a network and identify node failures. We evaluate our metric and algorithms on real-world networks and show the effectiveness of the proposed methods.","PeriodicalId":135949,"journal":{"name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"319 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115836598","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: 1

Unknown Landscape Identification with CNN Transfer Learning 基于CNN迁移学习的未知景观识别

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508357

Edoardo Serra, Ashish Sharma, Mikel Joaristi, O. Korzh

引用次数: 12

Influencing Information Spreading Processes in Complex Networks with Probability Spraying 用概率喷涂法影响复杂网络中的信息传播过程

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508637

Artur Karczmarczyk, Kamil Bortko, Piotr Bartków, Patryk Pazura, Jarosław Jankowski

引用次数: 4

Emergence of Leader-Follower Hierarchy Among Players in an On-Line Experiment 在线实验中参与者中领导者-追随者等级的出现

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508278

Bálint J. Tóth, G. Palla, Enys Mones, Gergo Havadi, Nóra Páll, P. Pollner, T. Vicsek

{"title":"Emergence of Leader-Follower Hierarchy Among Players in an On-Line Experiment","authors":"Bálint J. Tóth, G. Palla, Enys Mones, Gergo Havadi, Nóra Páll, P. Pollner, T. Vicsek","doi":"10.1109/ASONAM.2018.8508278","DOIUrl":"https://doi.org/10.1109/ASONAM.2018.8508278","url":null,"abstract":"Hierarchical networks are prevalent in nature and society, corresponding to groups of actors - animals, humans or even robots - organized according to a pyramidal structure with decision makers at the top and followers at the bottom. While this phenomenon is seemingly universal, the underlying governing principles are poorly understood. Here we study the emergence of hierarchies in groups of people playing a simple dot guessing game in controlled experiments, lasting for about 40 rounds, conducted over the Internet. During the games, the players had the possibility to look at the answer of a limited number of other players of their choice. This act of asking for advice defines a directed connection between the involved players, and according to our analysis, the initial random configuration of the emerging networks became more structured over time, showing signs of hierarchy towards the end of the game. In addition, the achieved score of the players appeared to be correlated with their position in the hierarchy. These results indicate that under certain conditions imitation and limited knowledge about the performance of other actors is sufficient for the emergence of hierarchy in a social group.","PeriodicalId":135949,"journal":{"name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115731801","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

Cyberbullying Detection on Instagram with Optimal Online Feature Selection 基于最优在线特征选择的Instagram网络欺凌检测

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508329

Mengfan Yao, C. Chelmis, Daphney-Stavroula Zois

{"title":"Cyberbullying Detection on Instagram with Optimal Online Feature Selection","authors":"Mengfan Yao, C. Chelmis, Daphney-Stavroula Zois","doi":"10.1109/ASONAM.2018.8508329","DOIUrl":"https://doi.org/10.1109/ASONAM.2018.8508329","url":null,"abstract":"Cyberbullying has emerged as a large-scale societal problem that demands accurate methods for its detection in an effort to mitigate its detrimental consequences. While automated, data-driven techniques for analyzing and detecting cyberbullying incidents have been developed, the scalability of existing approaches has largely been ignored. At the same time, the complexities underlying cyberbullying behavior (e.g., social context and changing language) make the automatic identification of “the best subset of features” to use challenging. We address this gap by formulating cyberbullying detection as a sequential hypothesis testing problem. Based on this formulation, we propose a novel algorithm to drastically reduce the number of features used in classification. We demonstrate the utility, scalability and responsiveness of our approach using a real-world dataset from Instagram, the online social media platform with the highest percentage of users reporting experiencing cyberbullying. Our approach improves recall by a staggering 700%, while at the same time reducing the average number of features by up to 99.82% compared to state-of-the-art supervised cyberbullying detection methods, learning approaches that require weak supervision, and traditional offline feature selection and dimensionality reduction techniques.","PeriodicalId":135949,"journal":{"name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"161 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114608261","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: 25

A Study of Reddit-User's Response to Rape reddit用户对强奸的反应研究

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508855

N. Kamarudin, Vineeth Rakesh, Ghazaleh Beigi, L. Manikonda, Huan Liu

{"title":"A Study of Reddit-User's Response to Rape","authors":"N. Kamarudin, Vineeth Rakesh, Ghazaleh Beigi, L. Manikonda, Huan Liu","doi":"10.1109/ASONAM.2018.8508855","DOIUrl":"https://doi.org/10.1109/ASONAM.2018.8508855","url":null,"abstract":"The growth of social media has created an open web where people freely share their opinion and even discuss sensitive subjects in online forums. Forums such as Reddit help support seekers by serving as a portal for open discussions for various stigmatized subjects such as rape. This paper investigates the potential roles of online forums and if such forums provide intended resources to the people who seek support. Specifically, the open nature of forums allows us to study how online users respond to seeker's queries or needs; through their response, we attempt to assess the range of topics covered by responders in regards to the issues, concerns and, obstacles faced by the victims of rape and sexual abuse, using rape-related posts from Reddit. We employ natural language processing techniques to extract topics of responses, examine how diverse these topics are to answer research questions such as whether responses are limited to emotional support; if not, what other topics are; what the diversity of topics manifests; and how online response differs from traditional response found in a physical world.","PeriodicalId":135949,"journal":{"name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123579208","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: 7

A Social Trust Metric For Scholarly Reputation Mining 学术声誉挖掘的社会信任度量

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508251

Ramy Hanafy, S. Makady, A. Elkorany

{"title":"A Social Trust Metric For Scholarly Reputation Mining","authors":"Ramy Hanafy, S. Makady, A. Elkorany","doi":"10.1109/ASONAM.2018.8508251","DOIUrl":"https://doi.org/10.1109/ASONAM.2018.8508251","url":null,"abstract":"Trust has been described as an intrinsic component of any social relation. Trust mainly refers to a measure of confidence on an entity that would behave in an expected manner. Academic social networking sites enable researchers to communicate, and share publications. This paper aims to rank both researchers and their productivity in terms of their scientific paper they are publishing. A trust model is proposed that utilizes the metadata of researchers and their papers, extracted from academic social networks, in order to produce two trust values, one for a researcher and another for a scientific paper. The utilized metadata for the researchers includes (total publication, total work citation, followers, h-index). Propagation of trust score using top co-authors is also considered for authors. The metadata of papers are: calculated author score, paper citation, and references citation. Each of those individual factors is assigned a specific weight based on user preference and AHP ranking method is applied. Individual metadata are aggregated to a collective one by considering aggregation weights for each feature and applying AHP ranking method. Experimental show that the proposed model provide a high accuracy value when compared using ground truth data from Google Scholar and global H-index.","PeriodicalId":135949,"journal":{"name":"2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122026462","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: 1

Discovering and Leveraging Communities in Dark Multi-Layered Networks for Network Disruption 在网络中断的黑暗多层网络中发现和利用社区

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Pub Date : 2018-08-01 DOI: 10.1109/ASONAM.2018.8508309

Ryan Miller, Ralucca Gera, A. Saxena, Tanmoy Chakraborty

引用次数: 4