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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 Trend Mining: Lead or Lag.
Big Data and Cognitive Computing 7 (4) e171. 10.3390/bdcc7040171.
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Abstract
This research underscores the profound implications of Social Intelligence Mining, notably employing open access data and Google Search engine data for trend discernment. Utilizing advanced analytical methodologies, including wavelet coherence analysis and phase difference, hidden relationships and patterns within social data were revealed. These techniques furnish an enriched comprehension of social phenomena dynamics, bolstering decision-making processes. The study’s versatility extends across myriad domains, offering insights into public sentiment and the foresight for strategic approaches. The findings suggest immense potential in Social Intelligence Mining to influence strategies, foster innovation, and add value across diverse sectors.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | social intelligence; data mining; open data; search engines; review; lead and lag |
| Research Programs: | Advancing Systems Analysis (ASA) Advancing Systems Analysis (ASA) > Cooperation and Transformative Governance (CAT) |
| Depositing User: | Luke Kirwan |
| Date Deposited: | 07 Nov 2023 08:37 |
| Last Modified: | 07 Nov 2023 08:37 |
| URI: | https://pure.iiasa.ac.at/19174 |
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