Textual sentiment in finance: A survey of methods and models

Colm Kearney, Sha Liu

    Research output: Contribution to journalArticleResearchpeer-review

    174 Citations (Scopus)


    We survey the textual sentiment literature, comparing and contrasting the various information sources, content analysis methods, and empirical models that have been used to date. We summarize the important and influential findings about how textual sentiment impacts on individual, firm-level and market-level behavior and performance, and vice versa. We point to what is agreed and what remains controversial. Promising directions for future research are emerging from the availability of more accurate and efficient sentiment measures resulting from increasingly sophisticated textual content analysis coupled with more extensive field-specific dictionaries. This is enabling more wide-ranging studies that use increasingly sophisticated models to help us better understand behavioral finance patterns across individuals, institutions and markets.
    Original languageEnglish
    Pages (from-to)171 - 185
    Number of pages15
    JournalInternational Review of Financial Analysis
    Publication statusPublished - 2014

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