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Social networks in marketing research 2001–2014: a co-word analysis

Author

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  • Zongshui Wang

    (University of Chinese Academy of Sciences)

  • Hong Zhao

    (University of Chinese Academy of Sciences)

  • Yan Wang

    (University of Chinese Academy of Sciences)

Abstract

This article aims to explore the evolution of social network in marketing research by analyzing the co-occurrence index and network structures of keywords. We find that the number of articles which subjective tittle consist of social networks within 19 marketing journals and 9 UTD (Utdallas list of top journals) management journals increase significantly and the number of keywords whose frequency are no less than two also grow dramatically since 2010, the network structures of keywords 2010–2014 become more dispersed shows as most of keywords’ centralities are between 0.32 and 0.63, and more keywords have strong relationships (Higher Cosine Index) with social networks or networks than 2001–2009. We also conclude that social network analysis has been mainly applied to study relationships, diffusion, influence, customer analysis, and enterprise management five subfields. Since mobile internet, intelligent devices, new media and digital technology are developing rapidly, social networks will be a powerful tool to study the related research fields.

Suggested Citation

  • Zongshui Wang & Hong Zhao & Yan Wang, 2015. "Social networks in marketing research 2001–2014: a co-word analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(1), pages 65-82, October.
    • Handle: RePEc:spr:scient:v:105:y:2015:i:1:d:10.1007_s11192-015-1672-9
    DOI: 10.1007/s11192-015-1672-9
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    6. Kim, Kun & Park, Oun-joung & Yun, Seunghyun & Yun, Haejung, 2017. "What makes tourists feel negatively about tourism destinations? Application of hybrid text mining methodology to smart destination management," Technological Forecasting and Social Change, Elsevier, vol. 123(C), pages 362-369.

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