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The relationship between social media sentiment and house prices in China: Evidence from text mining and wavelet analysis

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  • Shao, Jin
  • Hong, Jingke
  • Wang, Xianzhu
  • Yan, Xiaochen

Abstract

This study explores the dynamic relationship between house prices and social media sentiment in China, a housing sentiment index is constructed from social media reviews based on natural language processing techniques, and wavelet analysis is used to investigate the causal correlations from a new time-frequency perspective. We find that the sentiment index is negatively correlated with the fluctuation of house prices during the whole period, house prices and sentiment have bidirectional causality at the long-term timescale, and house prices causally affect sentiment at the short-term timescale. Furthermore, the sentiment significantly affects house prices in third-tier cities and the western regions.

Suggested Citation

  • Shao, Jin & Hong, Jingke & Wang, Xianzhu & Yan, Xiaochen, 2023. "The relationship between social media sentiment and house prices in China: Evidence from text mining and wavelet analysis," Finance Research Letters, Elsevier, vol. 57(C).
    • Handle: RePEc:eee:finlet:v:57:y:2023:i:c:s1544612323005846
    DOI: 10.1016/j.frl.2023.104212
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    References listed on IDEAS

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