Social media influencers: literature review, trends and research agenda

Anshika Singh Tanwar, Harish Chaudhry, Manish Kumar Srivastava
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Abstract

Purpose

This study aims to provide a holistic review of social media influencers (SMIs) research based on a unique approach of bibliometric analysis and content analysis between 2011 and 2020. The review examines the main influential aspects, themes and research streams to identify research directions for the future.

Design/methodology/approach

The sample selection and data collection were done from the Scopus database. The sample dataset was refined based on the inclusion and exclusion criteria to determine the final dataset of 183 articles. The dataset was exported in the BibTeX format and then imported into the BiblioShiny app for bibliometric analysis. The content analysis was done following the theory-context-methodology framework.

Findings

The several findings of this study include (1) Co-word analysis of most used keywords; (2) Longitudinal thematic evolution; (3) The focus of the research papers as per the theory-context-methodology review protocol are persuasion knowledge model, fashion and beauty industries, Instagram and content analysis, respectively; and (4) The network analysis of the research studies is known as the co-citation analysis and depicts the intellectual structure in the domain. This analysis resulted in four clusters of the research streams from the literature and two emergent themes (Chen et al., 2010)

Originality/value

In general, the previous reviews in the area are either domain, method or theory-based. Thus, this study aims to complement and extend the existing literature by presenting the overall picture of the SMI research with the help of a unique combined approach and further highlighting the trends and future research directions based on the findings of this study.

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社交媒体影响者:文献综述、趋势和研究议程
目的 本研究旨在采用独特的文献计量分析和内容分析方法,对 2011 年至 2020 年期间的社交媒体影响者(SMIs)研究进行全面综述。本综述探讨了具有影响力的主要方面、主题和研究流,以确定未来的研究方向。根据纳入和排除标准对样本数据集进行了改进,最终确定了 183 篇文章的数据集。数据集以 BibTeX 格式导出,然后导入 BiblioShiny 应用程序进行文献计量分析。本研究的几项发现包括:(1) 对使用最多的关键词进行共词分析;(2) 纵向主题演变;(3) 根据理论-语境-方法审查协议,研究论文的重点分别是说服知识模型、时尚和美容行业、Instagram 和内容分析;(4) 研究报告的网络分析被称为共引分析,描绘了该领域的知识结构。这一分析产生了四个文献研究流集群和两个新兴主题(Chen et al.因此,本研究旨在补充和扩展现有文献,通过独特的综合方法展示 SMI 研究的全貌,并在本研究结果的基础上进一步强调趋势和未来研究方向。
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来源期刊
CiteScore
6.50
自引率
3.20%
发文量
30
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