Social Influence Analysis for Information Diffusion in Complex Commercial Network

被引:3
作者
Saggu, Amrit Kaur [1 ]
Sinha, Adwitiya [1 ]
机构
[1] Jaypee Inst Informat Technol, Noida, India
关键词
Commercial Social Network; Complex Network; Information Diffusion; Key Influencers; Social Media; Twitter Science; ONTOLOGY; DOMAIN;
D O I
10.4018/IJKSS.2020010102
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
Social influence causes ideas to diffuse across the globe and track the rate at which awareness spans through online social communities. The users with better connectivity and higher interactivity bear greater potentials of spreading as well as perceiving the social trend. This concept has been further considered in the research to identify such prospective users in social network with high probability of influencing the opinions of others to whom they are connected. For the experimentation, Twitter profiles of 1900 followers from three major e-commerce portals, including Amazon, Snapdeal, and Flipkart, have been extracted to serve as the social network for conducting research. Acquired data is further narrowed down to yield a set of influential users in terms of central and centrally active, which are parameterized by neighborhood size and frequency of Twitter activity of individuals. Diffusion analysis is further performed on the derived set of key influencers to track the rate at which information propagates in the network.
引用
收藏
页码:22 / 59
页数:38
相关论文
共 31 条
  • [1] Abu-Salih Bilal, 2019, Web, Artificial Intelligence and Network Applications. Proceedings of the Workshops of the 33rd International Conference on Advanced Information Networking and Applications (WAINA-2019). Advances in Intelligent Systems and Computing (AISC 927), P887, DOI 10.1007/978-3-030-15035-8_87
  • [2] CredSaT: Credibility ranking of users in big social data incorporating semantic analysis and temporal factor
    Abu-Salih, Bilal
    Wongthongtham, Pornpit
    Chan, Kit Yan
    Zhu, Dengya
    [J]. JOURNAL OF INFORMATION SCIENCE, 2019, 45 (02) : 259 - 280
  • [3] Twitter mining for ontology-based domain discovery incorporating machine learning
    Abu-Salih, Bilal
    Wongthongtham, Pornpit
    Kit, Chan Yan
    [J]. JOURNAL OF KNOWLEDGE MANAGEMENT, 2018, 22 (05) : 949 - 981
  • [4] Aggarwal CharuC., 2013, MANAGING MINING SENS, P237, DOI [DOI 10.1007/978-1-4614-6309-2_9, 10.1007/978-1-4614-6309-2_9]
  • [5] Alp ZZ, 2016, PROCEEDINGS OF THE 2016 IEEE/ACM INTERNATIONAL CONFERENCE ON ADVANCES IN SOCIAL NETWORKS ANALYSIS AND MINING ASONAM 2016, P1321, DOI 10.1109/ASONAM.2016.7752407
  • [6] [Anonymous], P 3 INT C INT THINGS
  • [7] [Anonymous], KNOWLEDGE BASED PERS
  • [8] [Anonymous], WHAT REALLY INFLUENC
  • [9] [Anonymous], COMMUNICATION INNOVA
  • [10] [Anonymous], INNOVATION DIFFUSION