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To shut them up or to clarify: restraining the spread of rumors in online social networks

Wen,S, Jiang,J, Xiang,Y, Yu,S, Zhou,W and Jia,W 2014, To shut them up or to clarify: restraining the spread of rumors in online social networks, IEEE transactions on parallel and distributed systems, vol. 25, no. 12, pp. 3306-3316, doi: 10.1109/TPDS.2013.2297115.

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Title To shut them up or to clarify: restraining the spread of rumors in online social networks
Author(s) Wen,S
Jiang,J
Xiang,YORCID iD for Xiang,Y orcid.org/0000-0001-5252-0831
Yu,SORCID iD for Yu,S orcid.org/0000-0003-4485-6743
Zhou,WORCID iD for Zhou,W orcid.org/0000-0002-1680-2521
Jia,W
Journal name IEEE transactions on parallel and distributed systems
Volume number 25
Issue number 12
Start page 3306
End page 3316
Publisher IEEE Computer Society
Place of publication Piscataway, NJ
Publication date 2014-12-01
ISSN 1045-9219
Keyword(s) Defense
Online social network
Propagation
Rumors
Science & Technology
Technology
Computer Science, Theory & Methods
Engineering, Electrical & Electronic
Computer Science
Engineering
COMPLEX NETWORKS
WORM CONTAINMENT
Summary Restraining the spread of rumors in online social networks (OSNs) has long been an important but difficult problem to be addressed. Currently, there are mainly two types of methods 1) blocking rumors at the most influential users or community bridges, or 2) spreading truths to clarify the rumors. Each method claims the better performance among all the others according to their own considerations and environments. However, there must be one standing out of the rest. In this paper, we focus on this part of work. The difficulty is that there does not exist a universal standard to evaluate them. In order to address this problem, we carry out a series of empirical and theoretical analysis on the basis of the introduced mathematical model. Based on this mathematical platform, each method will be evaluated by using real OSN data.We have done three types of analysis in this work. First, we compare all the measures of locating important users. The results suggest that the degree and betweenness measures outperform all the others in the Facebook network. Second, we analyze the method of the truth clarification method, and find that this method has a long-term performance while the degree measure performs well only in the early stage. Third, in order to leverage these two methods, we further explore the strategy of different methods working together and their equivalence. Given a fixed budget in the real world, our analysis provides a potential solution to find out a better strategy by integrating both types of methods together. From both the academic and technical perspective, the work in this paper is an important step towards the most practical and optimal strategies of restraining rumors in OSNs.
Language eng
DOI 10.1109/TPDS.2013.2297115
Field of Research 080303 Computer System Security
Socio Economic Objective 890202 Application Tools and System Utilities
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2014, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30072054

Document type: Journal Article
Collection: School of Information Technology
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