A study on the competitive dissemination of disinformation and knowledge on social media
| Date | 07 February 2023 |
| Pages | 153-169 |
| DOI | https://doi.org/10.1108/AJIM-03-2022-0163 |
| Published date | 07 February 2023 |
| Subject Matter | Library & information science,Information behaviour & retrieval,Information & knowledge management,Information management & governance,Information management |
| Author | YiShu Wu,Dandan Wang,Feicheng Ma |
A study on the competitive
dissemination of disinformation
and knowledge on social media
YiShu Wu
School of Information Management, Wuhan University, Wuhan, China and
Center for Studies of Information Resources, Wuhan University, Wuhan, China
Dandan Wang
School of Information Management, Wuhan University, Wuhan, China;
Center for Studies of Information Resources, Wuhan University, Wuhan, China;
Big Data Institute, Wuhan University, Wuhan, China and
School of Data Science, City University of Hong Kong, Hong Kong, China, and
Feicheng Ma
School of Information Management, Wuhan University, Wuhan, China;
Center for Studies of Information Resources, Wuhan University, Wuhan, China and
Big Data Institute, Wuhan University, Wuhan, China
Abstract
Purpose–The purpose of this study is to explore the evolutionary path and stable strategy for the competitive
dissemination between disinformation and knowledgeon social media to provide effective solutions to curb the
dissemination of disinformation and promote the spread of knowledge.
Design/methodology/approach –Based on the social capital (SC) theory, the benefit matrix is constructed
and an evolutional game model is established in this paper. Through model solving and Matrix Laboratory
(MATLAB) simulation, the factors that influence disinformation-believing users (DUs) and knowledge-
believing users (KUs) to choose different strategies are analyzed.
Findings –The initial dissemination willingness, the disinformation infection probability, the knowledge
infection probability and the knowledge penetration probability are proved tobe crucial factors influencing the
game equilibrium in the competitive dissemination process of disinformation and knowledge. Moreover, some
countermeasures and recommendations for the governance of disinformation are proposed.
Originality/value –Currently most research interest lies in the disinformation dissemination model but
ignores the interaction between disinformation and knowledge in the diffusion process. This study revealsthe
Disinformation
and knowledge
on social media
153
This research was funded by the National Natural Science Foundation of China (No: 71420107026) and by the
National Key Research and Development Program of China (No: 2018YFC0806904-03).
The authors confirm that the manuscript has been read and approved by all named authors and that there
are no other persons who satisfied the criteria for authorship but are not listed. The authors further confirm
that the order of authors listed in the manuscript has been approved by all of us.
The authors confirm that we have given due consideration to the protection of intellectual property
associated with this work and that there are no impediments to publication, including the timing of
publication, with respect to intellectual property. In so doing, the authors confirm that we have followed the
regulations of our institutions concerning intellectual property.
The authors understand that the Corresponding Author is the sole contact for the Editorial process
(including Editorial Manager and direct communications with the office). He/she is responsible for
communicating with the other authors about progress, submissions of revisions and final approval of proofs.
The authors confirm that the authors have provided a current, correct email address which is accessible by the
Corresponding Author and which has been configured to accept email from fchma@whu.edu.cn.
Conflict of interest statement: The authors wish to draw the attention of the Editor to the following facts
that may be considered as potential conflicts of interestand to significant financial contributions to this work.
The current issue and full text archive of this journal is available on Emerald Insight at:
https://www.emerald.com/insight/2050-3806.htm
Received 30 March 2022
Revised 23 June 2022
27 September 2022
26 October 2022
Accepted 13 November 2022
Aslib Journal of Information
Management
Vol. 76 No. 1, 2024
pp. 153-169
© Emerald Publishing Limited
2050-3806
DOI 10.1108/AJIM-03-2022-0163
dynamic mechanism of social media users disseminating disinformation and knowledge and is expected to
promote the formation of cleaner cyberspace.
Keywords Disinformation dissemination, Knowledge dissemination, Evolutionary game, Competitive
information, Analog simulation, Dissemination willingness
Paper type Research paper
1. Introduction
In the era of big data, social media has become the most important way for people to obtain
information because of its convenience, timeliness and higher user value (Ma, 2020). However, as
the social media continuously develops, the disinformation on social media has increased
exponentially since people can obtain or send any information as they like at any time (Zhang
and Xu, 2021). Disinformation will bring great harm to the healthy development of social media and
social public safety, i.e. infringing on the public’s right to know, fostering the spread of panic and
even leading to social disorder. Moreover, disinformation will damage the credibility of social media
as an information acquisition channel, thus weakening its function of public opinion guidance.
In social networks, disinformation and knowledge disseminate in competition (Liu et al.,
2019), resultingin users being frequently exposed to multi-polarization information in various
controversialsocial events (Alon et al.,2011;Liu et al.,2016;Affleck and Giuliano,2013). Due to
the differentinformation literacy,there exist two types of users:disinformation-believing users
(DUs) and knowledge-believing users (KUs), both of which can choose to disseminate or not
disseminatethe information. Underspecific conditions, thetwo parties interact witheach other
to maximize their own profits. Considering the interactions between the two parties, game
theoryis a powerful means to study how to effectivelycurb the disseminationof disinformation
and promote the spread of knowledge (Zhang and Zhang, 2014).
To date, a number of studies have been conducted on the disinformation dissemination
model and dissemination of competitive information. However, existing studies mainly focus
on disinformation but ignore the influence of knowledge. In this paper, we take the interaction
between disinformation and knowledge into account and aim at revealing how to promote
social media users to disseminate knowledge and resist disinformation. In this regard, this
study intends to answer the following questions:
RQ1. What are the evolutionary path and results of competitive dissemination of
disinformation and knowledge on social media?
RQ2. How do disinformation and knowledge interact with each other in the process of
competitive dissemination?
RQ3. What factors influence the game equilibrium of disinformation and knowledge
disseminating on social media?
2. Literature review
2.1 Disinformation and disinformation dissemination model
On social media, rumors, misinformation and disinformation are all called false information,
but they have different meanings. Rumors are unconfirmed at the time of transmission and
are widely circulated (Buckner, 1965). Misinformation pertains to information that is
misleading (Lewandowsky et al., 2012), while disinformation refers to false, inaccurate
information (Bennett, 2018). The accuracy of rumors and misinformation is unknown.
However, as to disinformation, there must be correct descriptions against it owing to its false
nature. Therefore, we take disinformation as our research object in this paper. Knowledge is
defined as accurate information (Huang et al., 2021). Disinformation and knowledge are
different expressions of the same event. Over a certain period, they coexist and compete with
each other and thus can be regarded as “competitive information,”Through text analysis,
AJIM
76,1
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