Algorithm of identifying opinion leaders in BBS

Cheng, Fusuijing; Cao, Yan; Huang, Yongfeng; Zhou, Linna

doi:10.1109/ccis.2012.6664563

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…Zhiming Liu built the social network opinion leaders index system by using users influence and users activities, he used chromatography analysis method and rough set decision analysis theory to identify and analyze the opinion leaders [5]. Fusuijing Cheng et al proposed new algorithm to identify opinion leaders in BBS [6]. Shrihari A. Hudli et al presented an approach to identification of opinion leaders using the K-means clustering algorithm which does not require knowledge of the user's opinions or membership in other forums [7].…”

Section: Related Workmentioning

confidence: 99%

Research Methods on Recognizing Potential Opinion Leaders of Hot Event Based on Social Network

Qu¹,

Lian²,

Xie³

et al. 2015

Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering

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Recognizing the "opinion leaders" in advance is a new requirement in the context of social network. "From back to front" approaches do not conform to the transmission and evolution of development process of hot events. To address this problem, this paper proposes the concept of "potential opinion leaders", who is a user will become opinion leaders before the common event becoming hot. Our approach intuitively starts from the real development process of hot events, takes advantage of the "from front to back" dynamic research mode according to the propagation characteristics of hot events, and uses fan's number and identity tags as the screening criteria. We then design the analysis algorithm to recognize the "potential opinion leaders".The experimental result is compared with the traditional opinion leaders. It demonstrates that the recognition method by using "potential opinion leaders" is simpler, and guiding significance for network early warning is stronger.

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Section: Related Workmentioning

confidence: 99%

Research Methods on Recognizing Potential Opinion Leaders of Hot Event Based on Social Network

Qu¹,

Lian²,

Xie³

et al. 2015

Proceedings of the 2015 International Conference on Electrical, Automation and Mechanical Engineering

View full text Add to dashboard Cite

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Automatic opinion leader recognition in group discussions

Liu

Hsu

et al. 2016

2016 Conference on Technologies and Applications of Artificial Intelligence (TAAI)

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Identification of Opinion Leaders and Followers—A Case Study of Green Energy and Low Carbons

et al. 2020

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In recent years, with the development of Web2.0, enterprises, government agencies, and traditional news media, which have been positively influenced by opinion leaders, have been dedicated to understanding leaders’ opinions on the web in order to seek convergence. Specifically, with the increase of environmental awareness, the introduction of green energy and carbon reduction technology has become an important issue. Consequently, studies identifying opinion leaders and followers who are interested in green energy and low carbon have become important. This study aims to find a solution that can identify the characteristics of opinion leaders and followers that can be widely used, which will help certain public policies or issues to be more effectively disseminated in the future. To model the characteristics of opinion leaders and their influence on followers, this study uses a dual matrix. The interaction patterns are recognized among opinion leaders and followers, with the aim of developing public policy to promote green energy and low carbon emissions. A case is studied to validate the superiority of the proposed solution approach. With the proposed approach, a (business) organization can identify and access opinion leaders and their followers. Through communication, these organizations can absorb strain and preserve functions despite the presence of adversity. This study also clearly demonstrates its contribution and novelty through comparisons with the existing alternative method.

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Algorithm of identifying opinion leaders in BBS

Cited by 3 publications

References 2 publications

Research Methods on Recognizing Potential Opinion Leaders of Hot Event Based on Social Network

Research Methods on Recognizing Potential Opinion Leaders of Hot Event Based on Social Network

Automatic opinion leader recognition in group discussions

Identification of Opinion Leaders and Followers—A Case Study of Green Energy and Low Carbons

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