Using data mining to track the information spreading on social media about the COVID-19 outbreak

Xing, Yunfei; He, Wu; Cao, Gaohui; Li, Yuhai

doi:10.1108/el-04-2021-0086

Cited by 13 publications

(4 citation statements)

References 75 publications

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“…Topic modelling and text regression were applied to online app reviews of five music streaming services, finding that customers comment on factors related to usage environment, price plans and content. Xing et al (2022) analyzed the evolution of user interactions and network structure through social network analysis. Text clustering methods were used for differential assessments of evolving topics and visualization to show characteristics of a user interaction network and public opinion in different periods.…”

Section: Literature Reviewmentioning

confidence: 99%

Data mining analytics investigate WeChat users’ behaviours: online social media and social commerce development

Liao

Widowati

Lin

2023

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Purpose As of December 2021, WeChat had more than 1.2 billion active users worldwide, making it the most active online social media in mainland China. The term social commerce is used to describe new online sales through a mix of social networks and/or peer-to-peer communication or marketing strategies in terms of allowing consumers to satisfy their shopping behaviour through online social media. Thus, given the numerous active users, the development of online social media and social commerce on WeChat is a critical issue of internet research. Design/methodology/approach This empirical study takes WeChat as the online social media research object. Questionnaires for WeChat users in China were designed and distributed. All items are designed as nominal and ordinal scales (not Likert scale). The obtained data was put into a relational database (N = 2,342), and different meaningful patterns and rules were examined through data mining analytics, including clustering analysis and association rules, to explore the role of WeChat in the development of online social media and social commerce. Findings Practical implications are presented according to the research findings of meaningful patterns and rules. In addition, alternatives to WeChat in terms of further development are also proposed according to the investigation findings of WeChat users’ behaviour and preferences in China. Originality/value This study concludes that online social media, such as WeChat, will be able to transcend the current development pattern of most online social media and make good use of investigating users’ behaviour and preferences, not only to stimulate the interaction of users in the social network, but also to create social commerce value in social sciences.

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Section: Literature Reviewmentioning

confidence: 99%

Data mining analytics investigate WeChat users’ behaviours: online social media and social commerce development

Liao

Widowati

Lin

2023

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“…Moreover, the pro-and anti-vaccination groups were total opposites, barely communicating with each other. In the COVID-19 context, Xing et al (2021) incorporated SNA and the text clustering method to categorise people's opinions on COVID-19-related topics, which are based on various themes. The findings showed how user interaction networks and public opinions changed over time during the pandemic.…”

Section: Social Network Analysis On Social Mediamentioning

confidence: 99%

Twitter use by the dementia community during COVID-19: a user classification and social network analysis

Alhayan

Pennington

Ayouni

2022

OIR

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PurposeThe study aimed to examine how different communities concerned with dementia engage and interact on Twitter.Design/methodology/approachA dataset was sampled from 8,400 user profile descriptions, which was labelled into five categories and subjected to multiple machine learning (ML) classification experiments based on text features to classify user categories. Social network analysis (SNA) was used to identify influential communities via graph-based metrics on user categories. The relationship between bot score and network metrics in these groups was also explored.FindingsClassification accuracy values were achieved at 82% using support vector machine (SVM). The SNA revealed influential behaviour on both the category and node levels. About 2.19% suspected social bots contributed to the coronavirus disease 2019 (COVID-19) dementia discussions in different communities.Originality/valueThe study is a unique attempt to apply SNA to examine the most influential groups of Twitter users in the dementia community. The findings also highlight the capability of ML methods for efficient multi-category classification in a crisis, considering the fast-paced generation of data.Peer reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2021-0208.

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“…), meaningless words (i.e. “转发微博” (repost Weibo), “网页链接” (web links) and “收起” (collapse full text) (Xing et al , 2021). The interference information is eliminated by python’s regularization module.…”

Section: Research Frameworkmentioning

confidence: 99%

Using data mining technology to analyse the spatiotemporal public opinion of COVID-19 vaccine on social media

Zeng²,

Sun³

et al. 2022

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Purpose The deployment of vaccines is the primary task in curbing the COVID-19 pandemic. The purpose of this paper is to understand the public’s opinions on vaccines and then design effective interventions to promote vaccination coverage. Design/methodology/approach This paper proposes a research framework based on the spatiotemporal perspective to analyse the public opinion evolution towards COVID-19 vaccine in China. The framework first obtains data through crawler tools. Then, with the help of data mining technologies, such as emotion computing and topic extraction, the evolution characteristics of discussion volume, emotions and topics are explored from spatiotemporal perspectives. Findings In the temporal perspective, the public emotion declines in the later stage, but overall emotion performance is positive and stabilizing. This decline in emotion is mainly associated with ambiguous information about the COVID-19 vaccine. The research progress of vaccines and the schedule of vaccination have driven the evolution of public discussion topics. In the spatial perspective, the public emotion tends to be positive in 31 regions, whereas local emotion increases and decreases in different stages. The dissemination of distinctive information and the local epidemic prevention and control status may be potential drivers of topic evolution in local regions. Originality/value The analysis results of media information can assist decision-makers to accurately grasp the subjective thoughts and emotional expressions of the public in terms of spatiotemporal perspective and provide decision support for macro-control response strategies and risk communication.

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Using data mining to track the information spreading on social media about the COVID-19 outbreak

Cited by 13 publications

References 75 publications

Data mining analytics investigate WeChat users’ behaviours: online social media and social commerce development

Data mining analytics investigate WeChat users’ behaviours: online social media and social commerce development

Twitter use by the dementia community during COVID-19: a user classification and social network analysis

Using data mining technology to analyse the spatiotemporal public opinion of COVID-19 vaccine on social media

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