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Sentiment change and negative herding: Evidence from microblogging and news

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  • Kim, Jikyung (Jeanne)
  • Dong, Hang
  • Choi, Jeonghye
  • Chang, Sue Ryung

Abstract

Companies deal with good and bad publicity daily. We study the impact of news on consumer sentiment toward a company in the presence of pre-news sentiment. We use Sina Weibo’s (the Chinese version of Twitter) microblogging data and the full list of news items published in Sina Finance between 2013 and 2014 to measure sentiment. In our study, we address the following research questions: Does negative news have a greater impact than positive news on consumer sentiment change? Does news affect sentiment change to a greater degree when pre-news sentiment matches the news valence? Does the type of company (either B2C or B2B) matter? Our empirical findings show that consumers overreact to negative news and negative pre-news sentiment intensifies such overreaction, leading to negative herding. Further, negative pre-news sentiment is even more damaging for B2B companies than for B2C companies.

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  • Kim, Jikyung (Jeanne) & Dong, Hang & Choi, Jeonghye & Chang, Sue Ryung, 2022. "Sentiment change and negative herding: Evidence from microblogging and news," Journal of Business Research, Elsevier, vol. 142(C), pages 364-376.
    • Handle: RePEc:eee:jbrese:v:142:y:2022:i:c:p:364-376
    DOI: 10.1016/j.jbusres.2021.12.055
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