Spatial analysis of Twitter sentiment and district-level housing prices


Hannum C. M. , Arslanlı K. Y. , Kalay A. F.

JOURNAL OF EUROPEAN REAL ESTATE RESEARCH, vol.12, no.2, pp.173-189, 2019 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 12 Issue: 2
  • Publication Date: 2019
  • Doi Number: 10.1108/jerer-08-2018-0036
  • Journal Name: JOURNAL OF EUROPEAN REAL ESTATE RESEARCH
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, ABI/INFORM, EconLit
  • Page Numbers: pp.173-189
  • Istanbul Technical University Affiliated: Yes

Abstract

Purpose Studies have shown a correlation and predictive impact of sentiment on asset prices, including Twitter sentiment on markets and individual stocks. This paper aims to determine whether there exists such a correlation between Twitter sentiment and property prices. Design/methodology/approach The authors construct district-level sentiment indices for every district of Istanbul using a dictionary-based polarity scoring method applied to a data set of 1.7 million original tweets that mention one or more of those districts. The authors apply a spatial lag model to estimate the relationship between Twitter sentiment regarding a district and housing prices or housing price appreciation in that district. Findings The findings indicate a significant but negative correlation between Twitter sentiment and property prices and price appreciation. However, the percentage of check-in tweets is found to be positively correlated with prices and price appreciation.