ArticlePloS one2018
A lexicon based method to search for extreme opinions.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Political uses of the ancient past on social media are predominantly negative and extreme.PloS one · 2024Article
- Feature extraction from customer reviews using enhanced rules.PeerJ. Computer science · 2024Article
- Article
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Authors and funding
2 authors.
Funding
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Abstract
Studies in sentiment analysis and opinion mining have been focused on many aspects related to opinions, namely polarity classification by making use of positive, negative or neutral values. However, most studies have overlooked the identification of extreme opinions (most negative and most positive opinions) in spite of their vast significance in many applications. We use an unsupervised approach to search for extreme opinions, which is based on the automatic construction of a new lexicon containing the most negative and most positive words.
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Registered trials
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