Dynamic Logics of Diffusion and Link Changes on Social Networks

被引:0
|
作者
Baccini, Edoardo [1 ]
Christoff, Zoe [1 ]
Verbrugge, Rineke [1 ]
机构
[1] Univ Groningen, Bernoulli Inst Math Comp Sci & Artificial Intellig, Nijenborgh 9, NL-9747 AG Groningen, Netherlands
关键词
Social networks; Dynamic logic; Threshold models; Network change; Diffusion in networks; Opinion dynamics; Social epistemology; GROUP-SIZE; MODELS; TUTORIAL;
D O I
10.1007/s11225-024-10126-0
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper introduces a comprehensive logical framework to reason about threshold-driven diffusion and threshold-driven link change in social networks. It considers both monotonic dynamics, where agents can only adopt new features and create new connections, and non-monotonic dynamics, where agents may also abandon features or cut ties. Three types of operators are combined: one capturing diffusion only, one capturing link change only, and one capturing both at the same time. We first characterise the models on which diffusion of a unique feature and link change stabilise, whilst discussing salient properties of stable models with multiple spreading features. Second, we show that our operators (and any combination of them) are irreplaceable, in the sense that the sequences of model updates expressed by a combination of operators cannot always be expressed using any other operators. Finally, we analyse classes of models on which some operators can be replaced.
引用
收藏
页数:71
相关论文
共 50 条
  • [1] Dynamic Epistemic Logics of Diffusion and Prediction in Social Networks
    Alexandru Baltag
    Zoé Christoff
    Rasmus K. Rendsvig
    Sonja Smets
    [J]. Studia Logica, 2019, 107 : 489 - 531
  • [2] Dynamic Epistemic Logics of Diffusion and Prediction in Social Networks
    Baltag, Alexandru
    Christoff, Zoe
    Rendsvig, Rasmus K.
    Smets, Sonja
    [J]. STUDIA LOGICA, 2019, 107 (03) : 489 - 531
  • [3] Evaluating link prediction by diffusion processes in dynamic networks
    Vega-Oliveros, Didier A.
    Zhao, Liang
    Berton, Lilian
    [J]. SCIENTIFIC REPORTS, 2019, 9 (1)
  • [4] Evaluating link prediction by diffusion processes in dynamic networks
    Didier A. Vega-Oliveros
    Liang Zhao
    Lilian Berton
    [J]. Scientific Reports, 9
  • [5] Link Recommendation for Promoting Information Diffusion in Social Networks
    Li, Dong
    Xu, Zhiming
    Li, Sheng
    Sun, Xin
    Gupta, Anika
    Sycara, Katia
    [J]. PROCEEDINGS OF THE 22ND INTERNATIONAL CONFERENCE ON WORLD WIDE WEB (WWW'13 COMPANION), 2013, : 185 - 186
  • [6] Modeling Link Formation Behaviors in Dynamic Social Networks
    Viet-An Nguyen
    Leung, Cane Wing-Ki
    Lim, Ee-Peng
    [J]. SOCIAL COMPUTING, BEHAVIORAL-CULTURAL MODELING AND PREDICTION, 2011, 6589 : 349 - +
  • [7] Evolutionary Features for Dynamic Link Prediction in Social Networks
    Choudhury, Nazim
    Uddin, Shahadat
    [J]. APPLIED SCIENCES-BASEL, 2023, 13 (05):
  • [8] Link Prediction in Dynamic Social Networks: A Literature Review
    Marjan, Mohammad
    Zaki, Nazar
    Mohamed, Elfadil A.
    [J]. 2018 IEEE 5TH INTERNATIONAL CONGRESS ON INFORMATION SCIENCE AND TECHNOLOGY (IEEE CIST'18), 2018, : 200 - 207
  • [9] Link Prediction in Dynamic Social Networks by Integrating Community Information
    Ahmed, Nahla Mohamed
    Chen, Ling
    [J]. INTERNATIONAL ACADEMIC CONFERENCE ON THE INFORMATION SCIENCE AND COMMUNICATION ENGINEERING (ISCE 2014), 2014, : 460 - 465
  • [10] An evolutionary algorithm approach to link prediction in dynamic social networks
    Bliss, Catherine A.
    Frank, Morgan R.
    Danforth, Christopher M.
    Dodds, Peter Sheridan
    [J]. JOURNAL OF COMPUTATIONAL SCIENCE, 2014, 5 (05) : 750 - 764