社交情报挖掘:从 X 中挖掘洞察力

IF 4 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Hossein Hassani, N. Komendantova, Elena Rovenskaya, M. R. Yeganegi
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引用次数: 0

摘要

社会趋势挖掘处于数据科学和社会研究的交汇点,为研究社会动态和新兴趋势提供了一个新的视角。本文探讨了社会趋势挖掘的复杂面貌,特别强调了对领先趋势和滞后趋势的辨别。在此背景下,我们的研究采用了社会趋势挖掘技术,仔细研究了与风险管理、地震和灾难相关的 X(原 Twitter)数据。全面了解个人如何看待灾害风险管理中这些关键方面的重要性,对于制定获得公众认可的政策至关重要。本文揭示了公众情绪的复杂性,为政策制定者和研究人员提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Social Intelligence Mining: Unlocking Insights from X
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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来源期刊
CiteScore
6.30
自引率
0.00%
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审稿时长
7 weeks
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