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The dominant factor of social tags for users’ decision behavior on e‐commerce websites: Color or text

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  • Chen Xu
  • Qin Zhang

Abstract

Colored Tags (abbr.Tag) as a unique type of social tags is used on e‐commerce websites (e.g., Taobao) to summarize the high‐frequency keywords extracted from users' online reviews about products they bought before. Tag is represented inked red or green according to users' personal experiences and judgments about purchased items: red for positive comments, green for negative ones. The valence of users' emotion induced by red or green is controversial. This study firstly discovers that colored tags inked in red incite users' positive emotion (evaluations) and colored tags inked in green incite negative emotion (evaluations) using an ERP experiment, which is manifested in ERP components (e.g., N170, N2c, and LPC). There are two main features of Tag: the text of Tag (abbr. Text) and the color of Tag (abbr.Color). Our study then proves that Color (red or green) is the dominant factor in users' decision behavior compared with Text under the high cognitive load condition, while users' decision behavior is influenced by Text (positive tags or negative tags) predominately rather than by Color under the low cognitive load condition with the help of Eye tracking instrument. Those findings can help to design colored tags for recommendation systems on e‐commerce websites and other online platforms.

Suggested Citation

  • Chen Xu & Qin Zhang, 2019. "The dominant factor of social tags for users’ decision behavior on e‐commerce websites: Color or text," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 70(9), pages 942-953, September.
    • Handle: RePEc:bla:jinfst:v:70:y:2019:i:9:p:942-953
    DOI: 10.1002/asi.24118
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    Cited by:

    1. Jianshan Sun & Mingyue Zhu & Yuanchun Jiang & Yezheng Liu & Le Wu, 2021. "Hierarchical attention model for personalized tag recommendation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(2), pages 173-189, February.

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