Process / pipeline

Lexicon-Based Sentiment Analysis

Lexicon-based sentiment analysis computes sentiment at the word level using prebuilt sentiment dictionaries such as AFINN (Nielsen, 2011), SentiWordNet, VADER (Hutto & Gilbert, 2014), and the NRC Emotion Lexicon. It scores text by looking words up in a dictionary of charged terms, so it requires no labelled training data.

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Sources

  1. Nielsen, F.Å. (2011). A New ANEW: Evaluation of a Word List for Sentiment Analysis in Microblogs. Proceedings of the ESWC Workshop on 'Making Sense of Microposts'. link
  2. Hutto, C.J. & Gilbert, E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Proceedings of the International AAAI Conference on Web and Social Media (ICWSM), 8(1), 216-225. DOI: 10.1609/icwsm.v8i1.14550

Related methods

ScholarGateLexicon-Based Sentiment Analysis (Lexicon-Based Sentiment Analysis). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/lexicon-based-sentiment