Sentiment Analysis with a Multilingual Pipeline
| Autor: | Bal, DM, Bal, MA, v. Bunningen, A, Hogenboom, Alexander, Hogenboom, Frederik, Frasincar, Flavius, Bouguettaya, A., Hauswirth, M., Liu, L. |
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| Přispěvatelé: | Erasmus School of Economics, Econometrics |
| Jazyk: | angličtina |
| Rok vydání: | 2011 |
| Předmět: |
Grammar
Sarcasm Machine translation business.industry Computer science media_common.quotation_subject Sentiment analysis InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL computer.software_genre Irony Negation Slang Social media Artificial intelligence InformationSystems_MISCELLANEOUS business computer Natural language processing media_common |
| Zdroj: | Web Information System Engineering, 6997, 129-142 Lecture Notes in Computer Science ISBN: 9783642244339 WISE |
| DOI: | 10.1007/978-3-642-24434-6_10 |
| Popis: | Sentiment analysis refers to retrieving an author's sentiment from a text. We analyze the differences that occur in sentiment scoring across languages. We present our experiments for the Dutch and English language based on forum, blog, news and social media texts available on the Web, where we focus on the differences in the use of a language and the effect of the grammar of a language on sentiment analysis. We propose a multilingual pipeline for evaluating how an author's sentiment is conveyed in different languages. We succeed in correctly classifying positive and negative texts with an accuracy of approximately 71% for English and 79% for Dutch. The evaluation of the results shows however that usage of common expressions, emoticons, slang language, irony, sarcasm, and cynicism, acronyms and different ways of negation in English prevent the underlying sentiment scores from being directly comparable. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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