2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)最新文献_第9页

ETAF: An extended trust antecedents framework for trust prediction ETAF:用于信任预测的扩展信任前因框架

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921639

G. Guo, Jie Zhang, Daniel Thalmann, N. Yorke-Smith

引用次数: 131

Efficient algorithm for ranking of nodes' importance in information dissemination 信息传播中节点重要性排序的高效算法

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921565

Zhuo Qi Lee, W. Hsu, Miao Lin

{"title":"Efficient algorithm for ranking of nodes' importance in information dissemination","authors":"Zhuo Qi Lee, W. Hsu, Miao Lin","doi":"10.1109/ASONAM.2014.6921565","DOIUrl":"https://doi.org/10.1109/ASONAM.2014.6921565","url":null,"abstract":"Identifying nodes that play important roles in network dynamics in large scale complex networks is crucial for both characterizing the network and resource management. Under the viral marketing setting, Diffusion Centrality (DC) estimates the influential power of an individual. For the transport and physics communities, a node is considered important in Markov centrality (MC) if it can be quickly reached from the other nodes. Because these networks could contain millions of nodes, any ranking algorithm must have low time requirements to be practically useful. In this paper, we show that both metrics are strongly correlated, and we present a new method to enable fast estimation of the two metrics for large scale networks. The new approach is further validated empirically by using both real and synthetic networks. Our results refined the intuition that the influential power of an individual is largely governed by the local topology, rather than the mere number of contacts (node degree) alone. This allows us to better characterize the properties of the nodes that affect the outcome of the two centrality metrics.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133730900","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

Constructing social networks from semi-structured chat-log data 从半结构化的聊天日志数据构建社交网络

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921575

Sude Tavassoli, M. Moessner, K. Zweig

引用次数: 6

The comparison study on the motivations of staffs' behaviors on public and enterprise social network: Evidence from China 员工在公共和企业社交网络上行为动机的比较研究:来自中国的证据

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921678

Miaomiao Xiong, Qing Chen, A. Zhao

引用次数: 4

Incremental solutions to online multi-unit combinatorial auctions for information feedback 增量解决方案的在线多单位组合拍卖的信息反馈

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921690

S. Ramanathan, A. Kasinathan, A. K. Sen

{"title":"Incremental solutions to online multi-unit combinatorial auctions for information feedback","authors":"S. Ramanathan, A. Kasinathan, A. K. Sen","doi":"10.1109/ASONAM.2014.6921690","DOIUrl":"https://doi.org/10.1109/ASONAM.2014.6921690","url":null,"abstract":"With the ease of carrying out an auction through internet, the electronic auction market is expanding rapidly. In online (i.e., continuous) eBay-like combinatorial auctions, bidders are allowed to join and leave the auction at any time, and in the process, bidders can repetitively bid on packages of items of their choice. In such multi-agent e-business systems, the seller is compelled to provide information feedback to the bidders after every bid on the current state of the auction to help them place more informed bids. This requires provisional winners be computed for every package of items after each bid by solving Winner Determination Problems. In multi-unit online combinatorial auctions where the number of bids can be significantly large, the paper presents for the first time dynamic programming approaches which can incrementally solve winner determination problems for every package after each new bid. We propose two dynamic programming algorithms to solve the multi-unit winner determination problem. While our first algorithm computes and stores the optimal values for all packages on arrival of a new bid traversing the packages in a reverse order, the alternative algorithm stores the optimal values only for packages that can fit into available memory but can find out the optimal solutions for every other package. We discuss the salient features of the algorithms, and demonstrate our approach through experiments. We also propose a bottom-up approach to dynamic programming for effective use of memory.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"289 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133068565","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

Online evaluation re-scoring based on review behavior analysis 基于评论行为分析的在线评估重新评分

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921558

Rong Zhang, Xiaofeng He, Aoying Zhou, Chaofeng Sha

{"title":"Online evaluation re-scoring based on review behavior analysis","authors":"Rong Zhang, Xiaofeng He, Aoying Zhou, Chaofeng Sha","doi":"10.1109/ASONAM.2014.6921558","DOIUrl":"https://doi.org/10.1109/ASONAM.2014.6921558","url":null,"abstract":"Customer reviews written at online shopping sites greatly influence the decision of potential buyers. Since existence of noise in reviews is inevitable, helping users alleviate the influence of these noisy reviews has become a fundamental issue for improving service quality in e-commerce transactions, especially for C2C (customer-to-customer) sites. In this paper, we present an approach to reduce the influence of noisy review and improve product ranking quality by using customer credibility. Customer credibility is used to measure to what degree the reviews can be trusted. A feedback strategy is designed to calculate the customer credibility, which relies on the consistency evaluation between individual reviews and overall reviews. Additionally, we provide a method to eliminate the inconsistency problem between the review comments and customer given scores, captured by the learned model on the training data that is constructed automatically. The final product scores are calculated by considering both the customer credibility and the predicted scores. The experimental results on real-world data sets show that our proposed approach provides better products ranking than baseline systems.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"31 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116419524","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: 5

Semantic crawling: An approach based on Named Entity Recognition 语义爬行:一种基于命名实体识别的方法

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921661

Giulia Di Pietro, C. Aliprandi, Antonio Ercole De Luca, Matteo Raffaelli, Tiziana Soru

{"title":"Semantic crawling: An approach based on Named Entity Recognition","authors":"Giulia Di Pietro, C. Aliprandi, Antonio Ercole De Luca, Matteo Raffaelli, Tiziana Soru","doi":"10.1109/ASONAM.2014.6921661","DOIUrl":"https://doi.org/10.1109/ASONAM.2014.6921661","url":null,"abstract":"Law Enforcement Agencies (LEAs) are increasingly more reliant on information and communication technologies and affected by a society shaped by the Internet. The richness and quantity of information available from open sources, if properly gathered and processed, can provide valuable intelligence and help in drawing inferences from existing closed source intelligence. Today the intelligence cycle is characterized by manual collection and integration of data. Named Entity Recognition (NER) plays a fundamental role in Open Source Intelligence (OSINT) solutions when fighting crime. This paper describes the implementation of a NER-based focused web crawler under the EU FP7 Security Research Project CAPER (Collaborative information, Acquisition, Processing, Exploitation and Reporting for the prevention of organized crime). The crawler allows 1. to look for documents starting from a URL until a parametric depth of levels - also specifying a keyword that has to be contained in the page and in the related links - and 2. to look for a parametric number of documents starting from a keyword (entrusting the keyword search to one of the principal search engines, thus behaving as a meta-search engine). In addition, the crawler is able to retrieve only those documents that contain the information semantically relevant to the query (in other words: the required keyword with the required sense). This is achieved through the use of NER technologies. In this paper we present the CAPER NER-based Semantic Crawler, which has been proven to be a suitable tool for focused crawling, allowing LEAs to drastically reduce data collection and integration efforts.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"218 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122396170","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

CRIMETRACER: Activity space based crime location prediction 基于活动空间的犯罪定位预测

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921628

M. A. Tayebi, M. Ester, U. Glässer, P. Brantingham

{"title":"CRIMETRACER: Activity space based crime location prediction","authors":"M. A. Tayebi, M. Ester, U. Glässer, P. Brantingham","doi":"10.1109/ASONAM.2014.6921628","DOIUrl":"https://doi.org/10.1109/ASONAM.2014.6921628","url":null,"abstract":"Crime reduction and prevention strategies are vital for policymakers and law enforcement to face inevitable increases in urban crime rates as a side effect of the projected growth of urban population by the year 2030. Studies conclude that crime does not occur uniformly across urban landscapes but concentrates in certain areas. This phenomenon has drawn attention to spatial crime analysis, primarily focusing on crime hotspots, areas with disproportionally higher crime density. In this paper we present CRIMETRACER, a personalized random walk based approach to spatial crime analysis and crime location prediction outside of hotspots. We propose a probabilistic model of spatial behavior of known offenders within their activity space. Crime Pattern Theory concludes that offenders, rather than venture into unknown territory, frequently commit opportunistic crimes and serial violent crimes by taking advantage of opportunities they encounter in places they are most familiar with as part of their activity space. Our experiments on a large real-world crime dataset show that CRIMETRACER outperforms all other methods used for location recommendation we evaluate here.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123205512","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: 31

Characterizing emotion entrainment in social media 描述社交媒体中的情感卷入

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921653

Saike He, Xiaolong Zheng, Xiuguo Bao, Hongyuan Ma, D. Zeng, Bo Xu, Changliang Li, Hongwei Hao

{"title":"Characterizing emotion entrainment in social media","authors":"Saike He, Xiaolong Zheng, Xiuguo Bao, Hongyuan Ma, D. Zeng, Bo Xu, Changliang Li, Hongwei Hao","doi":"10.1109/ASONAM.2014.6921653","DOIUrl":"https://doi.org/10.1109/ASONAM.2014.6921653","url":null,"abstract":"The sociological theory of entrainment accounts for the synchronization of human rhythmic modalities through social interactions: they coordinate in a variety of dimensions including linguistic styles, facial expressions, music pace, applause, and so on. Though highly relevant, emotion entrainment has received little attention to date. In addition, most previous studies on entrainment are done through small scale or controlled laboratory studies. In this paper, we investigate emotion entrainment in the context of online social media. To the best of our knowledge, this is the first time that emotion entrainment has been examined on a large scale, real world setting. For this purpose, we propose a framework that can model entrainment phenomenon and measure its effect. Our framework differentiates from previous research by its model-free essential and discerning in entrainment directions. These traits enable us to model entrainment dynamics under few assumptions, and distinguish emotion flow of entrainment. In our studies, we investigate entrainment patterns under different emotion states, i.e. positive, neutral and negative. We discover that entrainments under different emotions all follow a power law distribution. Besides, people are willing to entrain to others under positive emotion, and users with positive emotion are more likely to be entrained. By inspecting the interactions between entrainment and emotion, we reveal that entrainment has an effect of negotiating different emotion types toward an even distribution.","PeriodicalId":143584,"journal":{"name":"2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014)","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124909587","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

Sentiment analysis of microblog combining dictionary and rules 结合字典和规则的微博情感分析

2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2014) Pub Date : 2014-08-17 DOI: 10.1109/ASONAM.2014.6921675

Ding Yuan, Yanquan Zhou, Ruifan Li, Peng Lu

引用次数: 8