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Coreference Resolution for Measuring Sentiment in Financial News

SSRN Electronic Journal
2022
  • 0
    Citations
  • 770
    Usage
  • 1
    Captures
  • 0
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Usage
    770
    • Abstract Views
      644
    • Downloads
      126
  • Captures
    1
    • Readers
      1
      • SSRN
        1
  • Ratings
    • Download Rank
      454,944

Article Description

We adopt a machine learning-based algorithm to identify direct and indirect company mentions in newspaper articles. We identify the importance of properly matching text segments to their respective companies when estimating human-perceived newspaper sentiment. Previous research has developed methods for measuring text sentiment and has revealed its relation to company returns. We further establish that knowing whether a text segment refers to a particular company is as important for estimating sentiment as the choice of the sentiment measure. Incorporating our methods into finance sentiment measures will significantly improve how accurately news sentiment both explains current and predicts future returns.

Bibliographic Details

Rasa Karapandza; Frederik Wisser

Elsevier BV

Textual analysis; News media; Language; Bag-of-words; Coreference resolution; Sentiment analysis; Word lists

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