Abstract
Even though considerable attention has been given to the polarity of words (positive and negative) and the creation of large polarity lexicons, research in emotion analysis has had to rely on limited and small emotion lexicons. In this paper, we show how the combined strength and wisdom of the crowds can be used to generate a large, high‐quality, word–emotion and word–polarity association lexicon quickly and inexpensively. We enumerate the challenges in emotion annotation in a crowdsourcing scenario and propose solutions to address them. Most notably, in addition to questions about emotions associated with terms, we show how the inclusion of a word choice question can discourage malicious data entry, help to…
Citation impact
2,560
total citations
- FWCI
- 55.71
- Percentile
- 100%
- References
- 101
Citations per year
Authors
2Topics & keywords
Topics
Keywords
- Lexicon
- Crowdsourcing
- Computer science
- Annotation
- Word (group theory)
- Natural language processing
- Polarity (international relations)
- Term (time)
UN Sustainable Development Goals
- Reduced inequalities
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