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Utilizing Social Media Analytics to Detect Trends in Saudi Arabias Evolving Market

arXiv 2502.16871 ↗First posted 24 Feb 2025cs.SI cs.AIcited by 0

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Abstract (arXiv)

Saudi Arabia faced a swift economic growth and societal transformation under Vision 2030. This offers a unique opportunity to track emerging trends in the region, which will ultimately pave the way for new business and investment possibilities. This paper explores how AI and social media analytics can identify and track trends across sectors such as construction, food and beverage, tourism, technology, and entertainment thereby helping the businesses make informed decisions. By leveraging a tailored AI-driven methodology, we analyzed millions of social media posts each month, classifying discussions and calculating scores to track the trends. The approach not only uncovered the emerging trends but also shows diminishing trends. Our methodology is able to predict the emergence and growth of trends by utilizing social media data. This approach has potential for adaptation in other regions. Ultimately, our findings highlight how ongoing, AI-powered trend analysis can enable more effective, data-informed business and development strategies in an increasingly dynamic environment.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 15 references that are in the map. First posted on arXiv 24 Feb 2025.

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References · 3

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2022BERTopic: Neural topic modeling with a class-based TF-IDF procedurecited by 801
  3. 2020AraBERT: Transformer-based Model for Arabic Language Understandingcited by 362

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