Rumor Identification with Maximum Entropy in MicroNet
Joint Authors
Yu, Suisheng
Li, Mingcai
Liu, Fengming
Source
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-09-28
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
The widely used applications of Microblog, WeChat, and other social networking platforms (that we call MicroNet) shorten the period of information dissemination and expand the range of information dissemination, which allows rumors to cause greater harm and have more influence.
A hot topic in the information dissemination field is how to identify and block rumors.
Based on the maximum entropy model, this paper constructs the recognition mechanism of rumor information in the micronetwork environment.
First, based on the information entropy theory, we obtained the characteristics of rumor information using the maximum entropy model.
Next, we optimized the original classifier training set and the feature function to divide the information into rumors and nonrumors.
Finally, the experimental simulation results show that the rumor identification results using this method are better than the original classifier and other related classification methods.
American Psychological Association (APA)
Yu, Suisheng& Li, Mingcai& Liu, Fengming. 2017. Rumor Identification with Maximum Entropy in MicroNet. Complexity،Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1142557
Modern Language Association (MLA)
Yu, Suisheng…[et al.]. Rumor Identification with Maximum Entropy in MicroNet. Complexity No. 2017 (2017), pp.1-8.
https://search.emarefa.net/detail/BIM-1142557
American Medical Association (AMA)
Yu, Suisheng& Li, Mingcai& Liu, Fengming. Rumor Identification with Maximum Entropy in MicroNet. Complexity. 2017. Vol. 2017, no. 2017, pp.1-8.
https://search.emarefa.net/detail/BIM-1142557
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1142557