LLM-Based Financial Sentiment Analysis in Arabic: Evidence from Saudi Markets
Researchers have developed a new framework for analyzing financial sentiment in Arabic, specifically for the Saudi market. This system integrates data from official financial news and social media to capture both institutional and public investor sentiment. The framework involves a multi-stage pipeline for data processing, including cleaning, entity linking, and sentiment annotation, utilizing transformer-based NER and a company lexicon to assign sentiment labels. AI
IMPACT Introduces a novel NLP approach to overcome linguistic challenges in Arabic financial sentiment analysis, potentially improving market insights.