Computational Social Networks最新文献_第2页

The structure of co-publications multilayer network 合作出版物多层网络的结构

Computational Social Networks Pub Date : 2021-02-09 DOI: 10.1186/s40649-021-00089-w

Ghislain Romaric Meleu, Paulin Yonta Melatagia

引用次数: 0

Influence network design via multi-level optimization considering boundedly rational user behaviours in social media networks 考虑社交媒体网络中有限理性用户行为，通过多层次优化影响网络设计

Computational Social Networks Pub Date : 2021-02-08 DOI: 10.1186/s40649-020-00082-9

Guanxiang Yun, Q. Zheng, V. Boginski, E. Pasiliao

引用次数: 2

Discovering the maximum k-clique on social networks using bat optimization algorithm 利用蝙蝠优化算法发现社交网络上的最大k-clique

Computational Social Networks Pub Date : 2021-02-02 DOI: 10.1186/s40649-021-00087-y

Akram Khodadadi, Shahram Saeidi

引用次数: 0

Understanding social media beyond text: a reliable practice on Twitter 理解文本之外的社交媒体：推特上的可靠实践

Computational Social Networks Pub Date : 2021-01-30 DOI: 10.1186/s40649-021-00088-x

Qixuan Hou, Meng Han, Feiyang Qu, J. He

引用次数: 3

A hybrid metaheuristic for solving asymmetric distance-constrained vehicle routing problem 求解非对称距离约束车辆路径问题的混合元启发式算法

Computational Social Networks Pub Date : 2021-01-22 DOI: 10.1186/s40649-020-00084-7

H. Ban, P. Nguyen

引用次数: 2

Non-submodular model for group profit maximization problem in social networks 社会网络群体利益最大化问题的非子模块模型

Computational Social Networks Pub Date : 2021-01-07 DOI: 10.1186/s40649-020-00085-6

Jianming Zhu, Smita Ghosh, Weili Wu, Chuangen Gao

{"title":"Non-submodular model for group profit maximization problem in social networks","authors":"Jianming Zhu, Smita Ghosh, Weili Wu, Chuangen Gao","doi":"10.1186/s40649-020-00085-6","DOIUrl":"https://doi.org/10.1186/s40649-020-00085-6","url":null,"abstract":"In social networks, there exist many kinds of groups in which people may have the same interests, hobbies, or political orientation. Sometimes, group decisions are made by simply majority, which means that most of the users in this group reach an agreement, such as US Presidential Elections. A group is called activated if $$beta$$ percent of users are influenced in the group. Enterprise will gain income from all influenced groups. Simultaneously, to propagate influence, enterprise needs pay advertisement diffusion cost. Group profit maximization (GPM) problem aims to pick k seeds to maximize the expected profit that considers the benefit of influenced groups with the diffusion cost. GPM is proved to be NP-hard and the objective function is proved to be neither submodular nor supermodular. An upper bound and a lower bound which are difference of two submodular functions are designed. We propose a submodular–modular algorithm (SMA) to solve the difference of two submodular functions and SMA is shown to converge to a local optimal. We present an randomized algorithm based on weighted group coverage maximization for GPM and apply sandwich framework to get theoretical results. Our experiments verify the efficiency of our methods.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"23 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138524883","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

A review: preprocessing techniques and data augmentation for sentiment analysis 综述:情感分析的预处理技术和数据增强

Computational Social Networks Pub Date : 2021-01-06 DOI: 10.1186/s40649-020-00080-x

Huu-Thanh Duong, Tram-Anh Nguyen-Thi

引用次数: 43

A model for the co-evolution of dynamic social networks and infectious disease dynamics. 动态社会网络和传染病动态共同进化模型。

Computational Social Networks Pub Date : 2021-01-01 Epub Date: 2021-10-07 DOI: 10.1186/s40649-021-00098-9

Hendrik Nunner, Vincent Buskens, Mirjam Kretzschmar

{"title":"A model for the co-evolution of dynamic social networks and infectious disease dynamics.","authors":"Hendrik Nunner, Vincent Buskens, Mirjam Kretzschmar","doi":"10.1186/s40649-021-00098-9","DOIUrl":"10.1186/s40649-021-00098-9","url":null,"abstract":"Recent research shows an increasing interest in the interplay of social networks and infectious diseases. Many studies either neglect explicit changes in health behavior or consider networks to be static, despite empirical evidence that people seek to distance themselves from diseases in social networks. We propose an adaptable steppingstone model that integrates theories of social network formation from sociology, risk perception from health psychology, and infectious diseases from epidemiology. We argue that networking behavior in the context of infectious diseases can be described as a trade-off between the benefits, efforts, and potential harm a connection creates. Agent-based simulations of a specific model case show that: (i) high (perceived) health risks create strong social distancing, thus resulting in low epidemic sizes; (ii) small changes in health behavior can be decisive for whether the outbreak of a disease turns into an epidemic or not; (iii) high benefits for social connections create more ties per agent, providing large numbers of potential transmission routes and opportunities for the disease to travel faster, and (iv) higher costs of maintaining ties with infected others reduce final size of epidemics only when benefits of indirect ties are relatively low. These findings suggest a complex interplay between social network, health behavior, and infectious disease dynamics. Furthermore, they contribute to solving the issue that neglect of explicit health behavior in models of disease spread may create mismatches between observed transmissibility and epidemic sizes of model predictions.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"8 1","pages":"19"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8495675/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39512711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling the transmission dynamics of racism propagation with community resilience. 建立具有社区复原力的种族主义传播动态模型。

Computational Social Networks Pub Date : 2021-01-01 Epub Date: 2021-11-06 DOI: 10.1186/s40649-021-00102-2

Dejen Ketema Mamo

{"title":"Modeling the transmission dynamics of racism propagation with community resilience.","authors":"Dejen Ketema Mamo","doi":"10.1186/s40649-021-00102-2","DOIUrl":"10.1186/s40649-021-00102-2","url":null,"abstract":"Racism spreading can have a vital influence on people's lives, declining adherence, pretending political views, and recruiters' socio-economical crisis. Besides, Web 2.0 technologies have democratized the creation and propagation of racist information, which facilitated the rapid spreading of racist messages. In this research work, the impact of community resilience on the spread dynamics of racism was assessed. To investigate the effect of resilience-building, new SERDC mathematical model was formulated and analyzed. The racism spread is under control where <math> <mrow><msub><mi>R</mi> <mn>0</mn></msub> <mo><</mo> <mn>1</mn></mrow> </math> , whereas persist in the community whenever <math> <mrow><msub><mi>R</mi> <mn>0</mn></msub> <mo>></mo> <mn>1</mn></mrow> </math> . Sensitivity analysis of the parameters value of the model are conducted. The rising of transmission and racial extremeness rate provides the prevalence of racism spread. Effective community resilience decline the damages, mitigate, and eradicate racism propagation. Theoretical analysis of the model are backed up by numerical results. Despite the evidence of numerical simulations, reducing the transmission and racial extremeness rate by improving social bonds and solidarity through community resilience could control the spread of racism.","PeriodicalId":52145,"journal":{"name":"Computational Social Networks","volume":"8 1","pages":"22"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8571679/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39623758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Node-weighted centrality: a new way of centrality hybridization 节点加权中心性:一种新的中心性杂交方法

Computational Social Networks Pub Date : 2020-11-13 DOI: 10.1186/s40649-020-00081-w

Anuj Singh, Rishi Ranjan Singh, S. R. S. Iyengar

引用次数: 22