The Spread of Information in Virtual Communities
Joint Authors
Zhang, Zhen
Du, Jin
Meng, Qingchun
Rong, Xiaoxia
Fan, Xiaodan
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-26
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
With the growth of online commerce, companies have created virtual communities (VCs) where users can create posts and reply to posts about the company’s products.
VCs can be represented as networks, with users as nodes and relationships between users as edges.
Information propagates through edges.
In VC studies, it is important to know how the number of topics concerning the product grows over time and what network features make a user more influential than others in the information-spreading process.
The existing literature has not provided a quantitative method with which to determine key points during the topic emergence process.
Also, few researchers have considered the link between multilayer physical features and the nodes’ spreading influence.
In this paper, we present two new ideas to enrich network theory as applied to VCs: a novel application of an adjusted coefficient of determination to topic growth and an adjustment to the Jaccard coefficient to measure the connection between two users.
A two-layer network model was first used to study the spread of topics through a VC.
A random forest method was then applied to rank various factors that might determine an individual user’s importance in topic spreading through a VC.
Our research provides insightful ways for enterprises to mine information from VCs.
American Psychological Association (APA)
Zhang, Zhen& Du, Jin& Meng, Qingchun& Rong, Xiaoxia& Fan, Xiaodan. 2020. The Spread of Information in Virtual Communities. Complexity،Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1143077
Modern Language Association (MLA)
Zhang, Zhen…[et al.]. The Spread of Information in Virtual Communities. Complexity No. 2020 (2020), pp.1-15.
https://search.emarefa.net/detail/BIM-1143077
American Medical Association (AMA)
Zhang, Zhen& Du, Jin& Meng, Qingchun& Rong, Xiaoxia& Fan, Xiaodan. The Spread of Information in Virtual Communities. Complexity. 2020. Vol. 2020, no. 2020, pp.1-15.
https://search.emarefa.net/detail/BIM-1143077
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1143077