mlsanityData to 14 Oct 2026

Characterizing Financial Market Coverage using Artificial Intelligence

arXiv 2302.03694 ↗First posted 7 Feb 2023q-fin.ST cs.AI cs.CLcited by 1

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Abstract (arXiv)

This paper scrutinizes a database of over 4900 YouTube videos to characterize financial market coverage. Financial market coverage generates a large number of videos. Therefore, watching these videos to derive actionable insights could be challenging and complex. In this paper, we leverage Whisper, a speech-to-text model from OpenAI, to generate a text corpus of market coverage videos from Bloomberg and Yahoo Finance. We employ natural language processing to extract insights regarding language use from the market coverage. Moreover, we examine the prominent presence of trending topics and their evolution over time, and the impacts that some individuals and organizations have on the financial market. Our characterization highlights the dynamics of the financial market coverage and provides valuable insights reflecting broad discussions regarding recent financial events and the world economy.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 11 of its 43 references that are in the map. First posted on arXiv 7 Feb 2023.

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11 of 43 references.

References · 11

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Citing papers per year: 2023: 1.

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  1. 2023Identifying depression-related topics in smartphone-collected free-response speech recordings using an automatic speech recognition system and a deep learning topic modelcited by 2