Ranked Clusterability Model of Dyadic Data in Social Network

被引:0
|
作者
Hakim, R. B. Fairiya [1 ]
Subanar [2 ]
Winarko, Edi [2 ]
机构
[1] Univ Islam Indonesia, Dept Stat, Fac Math & Nat Sci, Jalan Kaliurang KM 14-5 Sleman, Yogyakarta 55584, Indonesia
[2] Univ Gadjah Mada, Dept Math, Fac Math & Nat Sci, Yogyakarta 55528, Indonesia
来源
关键词
dyad data; ranked clusterability model; social network; network actor;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
The dyads relationship as a substantial portion of triads or larger structure formed a ranked clusterability model in social network. Ranked clusterability model of dyads postulates that the hierarchical clustering process starts from the mutual dyads which occur only within clusters then stop until all of the mutual dyads grouped. The hierarchy process continues to cluster the asymmetric dyads which occur between clusters but at different levels. Then the last process is clustering the null dyads, which is clustered at the end of the hierarchy after all of asymmetric dyads grouped and occur only between clusters at the same level of the hierarchy. This paper explores a ranked clusterability model of dyads from a simple example of social network and represents it to the new sociomatrix that facilitate to view a whole network and presents the result in a dendrogram network data. This model adds a new insight to the development of science in a clustering study of emerging social network.
引用
收藏
页码:90 / +
页数:2
相关论文
共 50 条
  • [21] Personality and social network effects on romantic relationships: A dyadic approach
    Neyer, FJ
    Voigt, D
    EUROPEAN JOURNAL OF PERSONALITY, 2004, 18 (04) : 279 - 299
  • [22] Social Network Extraction and Analysis Based on Multimodal Dyadic Interaction
    Escalera, Sergio
    Baro, Xavier
    Vitria, Jordi
    Radeva, Petia
    Raducanu, Bogdan
    SENSORS, 2012, 12 (02) : 1702 - 1719
  • [23] DYADIC AND SOCIAL NETWORK INFLUENCES ON ADOLESCENT EXPOSURE TO PREGNANCY RISK
    JORGENSEN, SR
    KING, SL
    TORREY, BA
    JOURNAL OF MARRIAGE AND THE FAMILY, 1980, 42 (01): : 141 - 155
  • [24] The Social Relations Model: How to Understand Dyadic Processes
    Back, Mitja D.
    Kenny, David A.
    SOCIAL AND PERSONALITY PSYCHOLOGY COMPASS, 2010, 4 (10): : 855 - 870
  • [25] Bayesian analysis of longitudinal dyadic data with informative missing data using a dyadic shared-parameter model
    Ahn, Jaeil
    Morita, Satoshi
    Wang, Wenyi
    Yuan, Ying
    STATISTICAL METHODS IN MEDICAL RESEARCH, 2019, 28 (01) : 70 - 83
  • [26] Building the Semantic Similarity Model for Social Network Data Streams
    Petrasova, Svitlana
    Khairova, Nina
    Lewoniewski, Wlodzimierz
    2018 IEEE SECOND INTERNATIONAL CONFERENCE ON DATA STREAM MINING & PROCESSING (DSMP), 2018, : 21 - 24
  • [27] Privacy threat model for data portability in social network applications
    Weiss, Stefan
    INTERNATIONAL JOURNAL OF INFORMATION MANAGEMENT, 2009, 29 (04) : 249 - 254
  • [28] Privacy Preservation in Social Network Data using Evolutionary Model
    Srivatsan, S.
    Maheswari, N.
    MATERIALS TODAY-PROCEEDINGS, 2022, 62 : 4732 - 4737
  • [29] A Forecast Model of Tourism Demand Driven by Social Network Data
    Peng, Tao
    Chen, Jian
    Wang, Chenjie
    Cao, Yanshi
    IEEE ACCESS, 2021, 9 : 109488 - 109496
  • [30] Dyadic Assessment and Dyadic Data Analysis
    Herzberg, Philipp Y.
    PSYCHOTHERAPIE PSYCHOSOMATIK MEDIZINISCHE PSYCHOLOGIE, 2011, 61 (08) : 383 - 383