Computational Social Networks最新文献_第4页

Robust communication network formation: a decentralized approach 健壮的通信网络形成:一种分散的方法

Computational Social Networks Pub Date : 2019-11-27 DOI: 10.1186/s40649-019-0072-3

Christopher Diaz, A. Nikolaev, Abhinav Perla, Alexander Veremyev, E. Pasiliao

引用次数: 0

Spheres of legislation: polarization and most influential nodes in behavioral context 立法领域:两极分化和行为语境中最具影响力的节点

Computational Social Networks Pub Date : 2019-11-25 DOI: 10.1186/s40649-021-00091-2

Andrew C. Phillips, M. Irfan, Luca Ostertag-Hill

引用次数: 1

Network robustness improvement via long-range links 通过远程链路提高网络健壮性

Computational Social Networks Pub Date : 2019-11-19 DOI: 10.1186/s40649-019-0073-2

Vincenza Carchiolo, Marco Grassia, Alessandro Longheu, Michele Malgeri, Giuseppe Mangioni

引用次数: 5

An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning 基于自学深度学习的Twitter吸毒风险行为洞察分析与检测

Computational Social Networks Pub Date : 2019-11-06 DOI: 10.1186/s40649-019-0071-4

Han Hu, NhatHai Phan, Soon A. Chun, James Geller, Huy Vo, Xinyue Ye, Ruoming Jin, Kele Ding, Deric Kenne, Dejing Dou

{"title":"An insight analysis and detection of drug-abuse risk behavior on Twitter with self-taught deep learning","authors":"Han Hu, NhatHai Phan, Soon A. Chun, James Geller, Huy Vo, Xinyue Ye, Ruoming Jin, Kele Ding, Deric Kenne, Dejing Dou","doi":"10.1186/s40649-019-0071-4","DOIUrl":"https://doi.org/10.1186/s40649-019-0071-4","url":null,"abstract":"Drug abuse continues to accelerate towards becoming the most severe public health problem in the United States. The ability to detect drug-abuse risk behavior at a population scale, such as among the population of Twitter users, can help us to monitor the trend of drug-abuse incidents. Unfortunately, traditional methods do not effectively detect drug-abuse risk behavior, given tweets. This is because: (1) tweets usually are noisy and sparse and (2) the availability of labeled data is limited. To address these challenging problems, we propose a deep self-taught learning system to detect and monitor drug-abuse risk behaviors in the Twitter sphere, by leveraging a large amount of unlabeled data. Our models automatically augment annotated data: (i) to improve the classification performance and (ii) to capture the evolving picture of drug abuse on online social media. Our extensive experiments have been conducted on three million drug-abuse-related tweets with geo-location information. Results show that our approach is highly effective in detecting drug-abuse risk behaviors.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"46 12","pages":"1-19"},"PeriodicalIF":0.0,"publicationDate":"2019-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513564","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: 17

Homophily in networked agent-based models: a method to generate homophilic attribute distributions to improve upon random distribution approaches 基于网络代理模型中的同态性:一种生成同态属性分布的方法，以改进随机分布方法

Computational Social Networks Pub Date : 2019-11-01 DOI: 10.1186/s40649-019-0070-5

M. Kapeller, Georg Jäger, M. Füllsack

引用次数: 4

Efficiently counting complex multilayer temporal motifs in large-scale networks 大规模网络中复杂多层时间基元的高效计数

Computational Social Networks Pub Date : 2019-09-14 DOI: 10.1186/s40649-019-0068-z

Hanjo D. Boekhout, Walter A. Kosters, Frank W. Takes

{"title":"Efficiently counting complex multilayer temporal motifs in large-scale networks","authors":"Hanjo D. Boekhout, Walter A. Kosters, Frank W. Takes","doi":"10.1186/s40649-019-0068-z","DOIUrl":"https://doi.org/10.1186/s40649-019-0068-z","url":null,"abstract":"This paper proposes novel algorithms for efficiently counting complex network motifs in dynamic networks that are changing over time. Network motifs are small characteristic configurations of a few nodes and edges, and have repeatedly been shown to provide insightful information for understanding the meso-level structure of a network. Here, we deal with counting more complex temporal motifs in large-scale networks that may consist of millions of nodes and edges. The first contribution is an efficient approach to count temporal motifs in multilayer networks and networks with partial timing, two prevalent aspects of many real-world complex networks. We analyze the complexity of these algorithms and empirically validate their performance on a number of real-world user communication networks extracted from online knowledge exchange platforms. Among other things, we find that the multilayer aspects provide significant insights in how complex user interaction patterns differ substantially between online platforms. The second contribution is an analysis of the viability of motif counting algorithms for motifs that are larger than the triad motifs studied in previous work. We provide a novel categorization of motifs of size four, and determine how and at what computational cost these motifs can still be counted efficiently. In doing so, we delineate the “computational frontier” of temporal motif counting algorithms.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"46 8","pages":"1-34"},"PeriodicalIF":0.0,"publicationDate":"2019-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513551","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: 16

Computational Social Networks Pub Date : 2019-08-08 DOI: 10.1186/s40649-019-0065-2

Yanxia Pang, Na Wang, Y. Zhang, Yuanyuan Jin, Wendi Ji, Wenan Tan

引用次数: 13

A privacy-preserving framework for ranked retrieval model 排序检索模型的隐私保护框架

Computational Social Networks Pub Date : 2019-07-24 DOI: 10.1186/s40649-019-0067-0

Tong Yan, Yunpeng Gao, Nan Zhang

{"title":"A privacy-preserving framework for ranked retrieval model","authors":"Tong Yan, Yunpeng Gao, Nan Zhang","doi":"10.1186/s40649-019-0067-0","DOIUrl":"https://doi.org/10.1186/s40649-019-0067-0","url":null,"abstract":"In this paper, we address privacy issues related to ranked retrieval model in web databases, each of which takes private attributes as part of input in the ranking function. Many web databases keep private attributes invisible to public and believe that the adversary is unable to reveal the private attribute values from query results. However, prior research (Rahman et al. in Proc VLDB Endow 8:1106–17, 2015) studied the problem of rank-based inference of private attributes over web databases. They found that one can infer the value of private attributes of a victim tuple by issuing well-designed queries through a top-k query interface. To address the privacy issue, in this paper, we propose a novel privacy-preserving framework. Our framework protects private attributes’ privacy not only under inference attacks but also under arbitrary attack methods. In particular, we classify adversaries into two widely existing categories: domain-ignorant and domain-expert adversaries. Then, we develop equivalent set with virtual tuples (ESVT) for domain-ignorant adversaries and equivalent set with true tuples (ESTT) for domain-expert adversaries. The ESVT and the ESTT are the primary parts of our privacy-preserving framework. To evaluate the performance, we define a measurement of privacy guarantee for private attributes and measurements for utility loss. We prove that both ESVT and ESTT achieve the privacy guarantee. We also develop heuristic algorithms for ESVT and ESTT, respectively, under the consideration of minimizing utility loss. We demonstrate the effectiveness of our techniques through theoretical analysis and extensive experiments over real-world dataset.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"46 11","pages":"1-25"},"PeriodicalIF":0.0,"publicationDate":"2019-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513565","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

Markov processes in blockchain systems 区块链系统中的马尔可夫过程

Computational Social Networks Pub Date : 2019-07-02 DOI: 10.1186/s40649-019-0066-1

Quan-Lin Li, Jing-Yu Ma, Yan-Xia Chang, Fan-Qi Ma, Hai-Bo Yu

{"title":"Markov processes in blockchain systems","authors":"Quan-Lin Li, Jing-Yu Ma, Yan-Xia Chang, Fan-Qi Ma, Hai-Bo Yu","doi":"10.1186/s40649-019-0066-1","DOIUrl":"https://doi.org/10.1186/s40649-019-0066-1","url":null,"abstract":"In this paper, we develop a more general framework of block-structured Markov processes in the queueing study of blockchain systems, which can provide analysis both for the stationary performance measures and for the sojourn time of any transaction or block. In addition, an original aim of this paper is to generalize the two-stage batch-service queueing model studied in Li et al. (Blockchain queue theory. In: International conference on computational social networks. Springer: New York; 2018. p. 25–40) both “from exponential to phase-type” service times and “from Poisson to MAP” transaction arrivals. Note that the MAP transaction arrivals and the two stages of PH service times make our blockchain queue more suitable to various practical conditions of blockchain systems with crucial factors, for example, the mining processes, the block generations, the blockchain building and so forth. For such a more general blockchain queueing model, we focus on two basic research aspects: (1) using the matrix-geometric solution, we first obtain a sufficient stable condition of the blockchain system. Then, we provide simple expressions for the average stationary number of transactions in the queueing waiting room and the average stationary number of transactions in the block. (2) However, on comparing with Li et al. (2018), analysis of the transaction–confirmation time becomes very difficult and challenging due to the complicated blockchain structure. To overcome the difficulties, we develop a computational technique of the first passage times by means of both the PH distributions of infinite sizes and the RG factorizations. Finally, we hope that the methodology and results given in this paper will open a new avenue to queueing analysis of more general blockchain systems in practice and can motivate a series of promising future research on development of blockchain technologies.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"45 2","pages":"1-28"},"PeriodicalIF":0.0,"publicationDate":"2019-07-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138513556","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: 45

Link weights recovery in heterogeneous information networks 异构信息网络中的链路权重恢复

Computational Social Networks Pub Date : 2019-06-27 DOI: 10.1186/s40649-020-00083-8

Hông-Lan Botterman, Robin Lamarche-Perrin

引用次数: 1