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Process / pipelineText-as-data methods

Dictionary-Based Text Analysis

Dictionary-based text analysis measures concepts in text by counting how often words belonging to predefined category lists — dictionaries — appear in each document. It is the workhorse lexicon method behind tools like LIWC and the General Inquirer, prized for its transparency and scalability: a category score is simply the share of a document's words that match the category's word list.

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Kilder

  1. Pennebaker, J. W., Mehl, M. R., & Niederhoffer, K. G. (2003). Psychological aspects of natural language use: Our words, our selves. Annual Review of Psychology, 54, 547–577. DOI: 10.1146/annurev.psych.54.101601.145041
  2. Grimmer, J., & Stewart, B. M. (2013). Text as data: The promise and pitfalls of automatic content analysis methods for political texts. Political Analysis, 21(3), 267–297. DOI: 10.1093/pan/mps028

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ScholarGate. (2026, June 22). Dictionary-Based Text Analysis in Communication. ScholarGate. https://scholargate.app/da/communication/dictionary-based-text-analysis-comm

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Refereret af

ScholarGateDictionary-Based Text Analysis (Dictionary-Based Text Analysis in Communication). Hentet 2026-06-24 fra https://scholargate.app/da/communication/dictionary-based-text-analysis-comm · Datasæt: https://doi.org/10.5281/zenodo.20539026