Exploring Word2Vec and LSA Models for Fund Review Analysis
Danchun Yang · 2024
This study investigates the application of Word2Vec and Latent Semantic Analysis(LSA) models in the analysis of fund reviews, with the objective of revealing thematic trends among investors within financial datasets. By synthesizing these methodologies, the research establishes a comprehensive framework for deconstructing intricate financial narratives. Empirical findings demonstrate how these insights can enhance fund management strategies and marketing initiatives, thereby advancing the field of financial text analytics. Moreover, the methodologies presented are applicable across a range of sectors, broadening their relevance and utility.