Herding Friends in Similarity-Based Architecture of Social Networks

被引:0
|
作者
Tamas David-Barrett
机构
[1] Universidad del Desarrollo,
[2] Facultad de Gobierno,undefined
[3] CICS,undefined
[4] University of Oxford,undefined
[5] Population Research Institute,undefined
[6] Väestöliitto,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Although friendship as a social behaviour is an evolved trait that shares many similarities with kinship, there is a key difference: to choose friends, one must select few from many. Homophily, i.e., a similarity-based friendship choice heuristic, has been shown to be the main factor in selecting friends. Its function has been associated with the efficiency of collective action via synchronised mental states. Recent empirical results question the general validity of this explanation. Here I offer an alternative hypothesis: similarity-based friendship choice is an individual-level adaptive response to falling clustering coefficient of the social network typical during urbanisation, falling fertility, increased migration. The mathematical model shows how homophily as a friend-choice heuristic affects the network structure: (1) homophilic friendship choice increases the clustering coefficient; (2) network proximity-based and similarity-based friendship choices have additive effects on the clustering coefficient; and (3) societies that face falling fertility, urbanisation, and migration, are likely go through a u-shaped transition period in terms of clustering coefficient. These findings suggest that social identity can be seen as an emergent phenomenon and is the consequence, rather than the driver of, homophilic social dynamics, and offer an alternative explanation for the rise of “fake news” as a societal phenomenon.
引用
收藏
相关论文
共 50 条
  • [1] Herding Friends in Similarity-Based Architecture of Social Networks
    David-Barrett, Tamas
    [J]. SCIENTIFIC REPORTS, 2020, 10 (01)
  • [2] Attacking Similarity-Based Link Prediction in Social Networks
    Zhou, Kai
    Michalak, Tomasz P.
    Waniek, Marcin
    Rahwan, Talal
    Vorobeychik, Yevgeniy
    [J]. AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, 2019, : 305 - 313
  • [3] Similarity-Based User Identification Across Social Networks
    Zamani, Katerina
    Paliouras, Georgios
    Vogiatzis, Dimitrios
    [J]. SIMILARITY-BASED PATTERN RECOGNITION, SIMBAD 2015, 2015, 9370 : 171 - 185
  • [4] A Novel Mathematical Framework for Similarity-based Opportunistic Social Networks
    ElSherief, Mai
    Alipour, Babak
    Al Qathrady, Mimonah
    ElBatt, Tamer
    Zahran, Ahmed
    Helmy, Ahmed
    [J]. PERVASIVE AND MOBILE COMPUTING, 2017, 42 : 134 - 150
  • [5] Improving Similarity-Based Methods for Information Propagation on Social Networks
    Buccafurri, Francesco
    Lax, Gianluca
    [J]. NETWORKED DIGITAL TECHNOLOGIES, PT 1, 2010, 87 : 391 - 401
  • [6] Similarity-Based Hybrid Algorithms for Link Prediction Problem in Social Networks
    Hassen Mohamed Kerkache
    Lamia Sadeg-Belkacem
    Fatima Benbouzid-Si Tayeb
    [J]. New Generation Computing, 2023, 41 : 281 - 314
  • [7] Similarity-Based and Sybil Attack Defended Community Detection for Social Networks
    Jiang, Zhongyuan
    Li, Jing
    Ma, Jianfeng
    Yu, Philip S.
    [J]. IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS, 2020, 67 (12) : 3487 - 3491
  • [8] Similarity-Based Hybrid Algorithms for Link Prediction Problem in Social Networks
    Kerkache, Hassen Mohamed
    Sadeg-Belkacem, Lamia
    Tayeb, Fatima Benbouzid-Si
    [J]. NEW GENERATION COMPUTING, 2023, 41 (02) : 281 - 314
  • [9] Similarity-based Heterogeneous Neural Networks
    Belanche Munoz, Lluis A.
    Valdes Ramos, Julio Jose
    [J]. ENGINEERING LETTERS, 2007, 14 (02)
  • [10] Similarity-based link prediction in social networks: A path and node combined approach
    Yu, Chuanming
    Zhao, Xiaoli
    An, Lu
    Lin, Xia
    [J]. JOURNAL OF INFORMATION SCIENCE, 2017, 43 (05) : 683 - 695