Social Intelligence Mining: Unlocking Insights from X

Hassani, H., Komendantova, N. ORCID: https://orcid.org/0000-0003-2568-6179, Rovenskaya, E. ORCID: https://orcid.org/0000-0002-2761-3443, & Yeganegi, R. (2023). Social Intelligence Mining: Unlocking Insights from X. Machine Learning and Knowledge Extraction 5 (4) 1921-1936. 10.3390/make5040093.

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Abstract

Social trend mining, situated at the confluence of data science and social research, provides a novel lens through which to examine societal dynamics and emerging trends. This paper explores the intricate landscape of social trend mining, with a specific emphasis on discerning leading and lagging trends. Within this context, our study employs social trend mining techniques to scrutinize X (formerly Twitter) data pertaining to risk management, earthquakes, and disasters. A comprehensive comprehension of how individuals perceive the significance of these pivotal facets within disaster risk management is essential for shaping policies that garner public acceptance. This paper sheds light on the intricacies of public sentiment and provides valuable insights for policymakers and researchers alike.

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