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 tr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-12-01
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| Series: | Machine Learning and Knowledge Extraction |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-4990/5/4/93 |
| _version_ | 1797380244204683264 |
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| author | Hossein Hassani Nadejda Komendantova Elena Rovenskaya Mohammad Reza Yeganegi |
| author_facet | Hossein Hassani Nadejda Komendantova Elena Rovenskaya Mohammad Reza Yeganegi |
| author_sort | Hossein Hassani |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-08T20:34:36Z |
| format | Article |
| id | doaj.art-2a8d4aaecabe46f78a0cc751885c6a1b |
| institution | Directory Open Access Journal |
| issn | 2504-4990 |
| language | English |
| last_indexed | 2024-03-08T20:34:36Z |
| publishDate | 2023-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Machine Learning and Knowledge Extraction |
| spelling | doaj.art-2a8d4aaecabe46f78a0cc751885c6a1b2023-12-22T14:22:15ZengMDPI AGMachine Learning and Knowledge Extraction2504-49902023-12-01541921193610.3390/make5040093Social Intelligence Mining: Unlocking Insights from XHossein Hassani0Nadejda Komendantova1Elena Rovenskaya2Mohammad Reza Yeganegi3The International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaThe International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaThe International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaThe International Institute for Applied Systems Analysis (IIASA), 2361 Laxenburg, AustriaSocial 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.https://www.mdpi.com/2504-4990/5/4/93social trend mininganalyticsdisaster risk managementX (Twitter) datasentiment analysistrend analysis |
| spellingShingle | Hossein Hassani Nadejda Komendantova Elena Rovenskaya Mohammad Reza Yeganegi Social Intelligence Mining: Unlocking Insights from X Machine Learning and Knowledge Extraction social trend mining analytics disaster risk management X (Twitter) data sentiment analysis trend analysis |
| title | Social Intelligence Mining: Unlocking Insights from X |
| title_full | Social Intelligence Mining: Unlocking Insights from X |
| title_fullStr | Social Intelligence Mining: Unlocking Insights from X |
| title_full_unstemmed | Social Intelligence Mining: Unlocking Insights from X |
| title_short | Social Intelligence Mining: Unlocking Insights from X |
| title_sort | social intelligence mining unlocking insights from x |
| topic | social trend mining analytics disaster risk management X (Twitter) data sentiment analysis trend analysis |
| url | https://www.mdpi.com/2504-4990/5/4/93 |
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