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Effects of sentiment on recommendations in social network

Author

Listed:
  • Ping-Yu Hsu

    (National Central University)

  • Hong-Tsuen Lei

    (National Central University)

  • Shih-Hsiang Huang

    (National Central University)

  • Teng Hao Liao

    (National Central University)

  • Yao-Chung Lo

    (National Central University)

  • Chin-Chun Lo

    (Taroko Software)

Abstract

This study adopted a sentiment word database to extract sentiment-related data from microblog posts. These data were then used to investigate the effect of different types of sentiment-related words on product recommendations. The results indicate that posts containing strong sentiments received more clicks than posts containing neutral sentiments. Posts containing more than one positive sentiment word generate more effective recommendations than posts containing only one positive sentiment word. This study also demonstrated that posts with a negative polarity classification received more clicks than those with a positive polarity classification. Additionally, the microblog posts containing implicit sentiment words received more clicks than those containing explicit sentiment words. The findings presented here could assist product or service marketers who use Plurk or similar microblogging platforms better focus their limited financial resources on potential online customers to achieve maximum sale revenue.

Suggested Citation

  • Ping-Yu Hsu & Hong-Tsuen Lei & Shih-Hsiang Huang & Teng Hao Liao & Yao-Chung Lo & Chin-Chun Lo, 2019. "Effects of sentiment on recommendations in social network," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 253-262, June.
    • Handle: RePEc:spr:elmark:v:29:y:2019:i:2:d:10.1007_s12525-018-0314-5
    DOI: 10.1007/s12525-018-0314-5
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    References listed on IDEAS

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    Cited by:

    1. Yin Zhang & Haider Abbas & Yi Sun, 2019. "Smart e-commerce integration with recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 29(2), pages 219-220, June.
    2. Kwansoo Kim & Sang-Yong Tom Lee & Robert J. Kauffman, 2023. "Social informedness and investor sentiment in the GameStop short squeeze," Electronic Markets, Springer;IIM University of St. Gallen, vol. 33(1), pages 1-24, December.
    3. Huang, Jin & Sena, Vania & Li, Jun & Ozdemir, Sena, 2021. "Message framing in P2P lending relationships," Journal of Business Research, Elsevier, vol. 122(C), pages 761-773.
    4. Erik Ernesto Vazquez, 2021. "Effect of an e-retailer’s product category and social media platform selection on perceived quality of e-retail products," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(1), pages 139-157, March.
    5. Payam Hanafizadeh & Mahdi Barkhordari Firouzabadi & Khuong Minh Vu, 2021. "Insight monetization intermediary platform using recommender systems," Electronic Markets, Springer;IIM University of St. Gallen, vol. 31(2), pages 269-293, June.

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    More about this item

    Keywords

    Social networking site; Social commerce; Microblog; Sentiment word; Plurk;
    All these keywords.

    JEL classification:

    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

    Statistics

    Access and download statistics

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