Bounded Confidence-based Opinion Formation for Opinion Leaders and Opinion Followers on Social Networks

Zhao, Yiyi; Kou, Gang

doi:10.24846/v23i2y201403

Cited by 17 publications

(14 citation statements)

References 14 publications

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“…5 show that increasing the appeal of both the leaders makes it easier for the normal agents to achieve consensus (i.e. it lowers the consensus threshold), which confirms the findings in 21 , because they are more likely to be influenced by both leaders which makes them achieve consensus roughly at the average opinion of the leaders. There is a common pattern for most of the appeal values in Fig.…”

Section: Impact Of Stubbornness On Opinion Dynamicssupporting

confidence: 75%

“…It was also suggested 17 that opinion leaders should maintain invariable opinions in the process of opinion dynamics, which is sometimes called stubbornness 19,20 . More recently, Zhao and Kou 21 proposed an opinion leader-follower model which divides the whole group into two sub-groups, i.e., a leader sub-group and a follower sub-group, and the information / influence transition is based on the principle of a two-step flow model where the opinion update is based on a bounded confidence model, the Hegselmann-Krause (HK) model 22,23 . Their results showed that the opinion followers are strongly influenced by the leaders if they have higher confidence levels and trust degrees in the leaders.…”

Section: Introductionmentioning

confidence: 99%

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Characteristics of successful opinion leaders in a bounded confidence model

Chen

Glass

McCartney

2016

Physica A: Statistical Mechanics and its Applications

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This paper analyses the impact of competing opinion leaders on attracting followers in a social group based on a bounded confidence model in terms of four characteristics: reputation, stubbornness, appeal and extremeness. In the model, reputation differs among leaders and normal agents based on the weights assigned to them, stubbornness of leaders is reflected by their confidence towards normal agents, appeal of the leaders is represented by the confidence of followers towards them, and extremeness is captured by the opinion values of leaders. Simulations show that increasing reputation, stubbornness or extremeness make it more difficult for the group to achieve consensus, but increasing the appeal will make it easier. The results demonstrate that successful opinion leaders should generally be less stubborn, have greater appeal and be less extreme in order to attract more followers in a competing environment. Furthermore, the number of followers can be very sensitive to small changes in these characteristics. On the other hand, reputation has a more complicated impact: higher reputation helps the leader to attract more followers when the group bound of confidence is high, but can hinder the leader from attracting followers when the group bound of confidence is low.

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Section: Impact Of Stubbornness On Opinion Dynamicssupporting

confidence: 75%

Section: Introductionmentioning

confidence: 99%

Characteristics of successful opinion leaders in a bounded confidence model

Chen

Glass

McCartney

2016

Physica A: Statistical Mechanics and its Applications

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“…It is clear that most studies indicated that opinion leaders played an important role in information propagation. In many cases, opinion leaders may transfer the information to the neighboring agents unconsciously [48]. However, in some NIMBY conflict cases, opinion leaders hoped to guide the neighbors to an expected opinion for a purpose, such as panic boycott.…”

Section: Related Workmentioning

confidence: 99%

“…The group scale has a significant impact on the activity as one of elements of collective behavior in 52 mass incidents occurred in China during 2007-2011 [55], as well as collective opinion evolution [48]; these can show that formation and evolution of any public opinion need a considerable number of participants. Meanwhile, the average scale of these 52 mass incidents was within the interval [100, 900], so in our simulation the size of the considered network is selected as n = 500.…”

Section: Parameter Interpretationmentioning

confidence: 99%

Structure Reversal of Online Public Opinion for the Heterogeneous Health Concerns under NIMBY Conflict Environmental Mass Events in China

Hou

Xiao

2020

Healthcare

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Public opinions play an important role in the formation of Not in My Back Yard (NIMBY) conflict environmental mass events. Due to the continual interactions between affected groups and the corresponding government responses surrounding the public interests related to health, online public opinion structure reversal arises frequently in NIMBY conflict events, which pose a serious threat to social public security. To explore the underlying mechanism, this paper introduces an improved dynamic model which considers multiple heterogeneities in health concerns and social power of individuals and in government’s ability. The experimental results indicate that the proposed model can provide an accurate description of the entire process of online public opinion structure reversal in NIMBY conflict environmental mass incidents on the Internet. In particular, the proportion of the individual agents without health interest appeals will delay the online public opinion structure reversal, and the upper threshold remains within regulatory limits from 0.4 to 0.5. Unlike some previous results that show that the guiding powers of the opinion leaders varied over its ratio in a fixed-sized group, our results suggest that the impact of opinion leaders is of no significant difference for the time of structure reversal after it increased to about 6%. Furthermore, a double threshold effect of online structure reversal during the government’s response process was observed. The findings are beneficial for understanding and explaining the process of online public opinion structure reversal in NIMBY conflict environmental mass incidents, and provides theoretical and practical implications for guiding public or personal health opinions on the Internet and for a governments’ effective response to them.

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“…Meanwhile, the concept of opinion leadership can be used to categorize social media users into two groups: opinion leaders and opinion followers [14]. The former commands a greater fan following, and is more popular in the online community than the latter.…”

Section: Introductionmentioning

confidence: 99%

Rumors and rumor corrections on Twitter: Studying message characteristics and opinion leadership

Chua

Banerjee

2018

2018 4th International Conference on Information Management (ICIM)

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As rumors often ripple across the cyberspace, posting rumor corrections on social media can bring about social good by spreading the truth. However, rumors and rumor corrections are not easily distinguishable from one another. Therefore, this paper investigates how three message characteristics, namely, the use of emotions, clarity and credible source attribution, can predict message veracity on social media. Message veracity denotes whether a message is a rumor or a rumor correction. In addition, the paper further examines the extent to which opinion leadership moderates the relation between message characteristics and message veracity. Set against the context of the death hoax of Singapore's first Prime Minister Lee Kuan Yew in March 2015, data for this paper came from Twitter. Analysis involved binary logistic regression. All the three message characteristics predicted veracity. Rumor corrections were characterized by lower use of emotions, higher clarity, and higher credible source attribution compared with rumors. Furthermore, opinion leadership moderated the relation between the use of emotions and message veracity as well as that between credible source attribution and message veracity.

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Bounded Confidence-based Opinion Formation for Opinion Leaders and Opinion Followers on Social Networks

Cited by 17 publications

References 14 publications

Characteristics of successful opinion leaders in a bounded confidence model

Characteristics of successful opinion leaders in a bounded confidence model

Structure Reversal of Online Public Opinion for the Heterogeneous Health Concerns under NIMBY Conflict Environmental Mass Events in China

Rumors and rumor corrections on Twitter: Studying message characteristics and opinion leadership

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