Crowdsourcing for Beyond Polarity Sentiment Analysis A Pure Emotion Lexicon
| Autor: | Haralabopoulos, Giannis, Simperl, Elena |
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| Rok vydání: | 2017 |
| Předmět: | |
| Druh dokumentu: | Working Paper |
| Popis: | Sentiment analysis aims to uncover emotions conveyed through information. In its simplest form, it is performed on a polarity basis, where the goal is to classify information with positive or negative emotion. Recent research has explored more nuanced ways to capture emotions that go beyond polarity. For these methods to work, they require a critical resource: a lexicon that is appropriate for the task at hand, in terms of the range of emotions it captures diversity. In the past, sentiment analysis lexicons have been created by experts, such as linguists and behavioural scientists, with strict rules. Lexicon evaluation was also performed by experts or gold standards. In our paper, we propose a crowdsourcing method for lexicon acquisition, which is scalable, cost-effective, and doesn't require experts or gold standards. We also compare crowd and expert evaluations of the lexicon, to assess the overall lexicon quality, and the evaluation capabilities of the crowd. Comment: Keywords: Beyond Polarity, Pure Sentiment, Crowdsourcing, Sentiment Analysis, Lexicon Acquisition, Reddit, Twitter, Brexit [19 pages, 6 figures, 4 tables] |
| Databáze: | arXiv |
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