Please use this identifier to cite or link to this item:
http://hdl.handle.net/10174/20659
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Title: | Multilingual author profiling using svms and linguistic features |
Authors: | Bayot, Roy Gonçalves, Teresa |
Issue Date: | 2016 |
Publisher: | Bahri Publications |
Citation: | Roy Bayot and Teresa Gonçalves. Multilingual author profiling using svms and linguistic features. International Journal of Computational Linguistics and Applications, vol. 7, 2016 |
Abstract: | This paper describes various experiments done to investigate author profiling of tweets in 4 different languages – English, Dutch, Italian, and Spanish. Profiling consists of age and gender classification, as well as regression on 5 different person- ality dimensions – extroversion, stability, agreeableness, open- ness, and conscientiousness. Different sets of features were tested – bag-of-words, word ngrams, POS ngrams, and average of word embeddings. SVM was used as the classifier. Tfidf worked best for most English tasks while for most of the tasks from the other languages, the combination of the best features worked better. |
URI: | http://hdl.handle.net/10174/20659 |
Type: | article |
Appears in Collections: | INF - Publicações - Artigos em Revistas Internacionais Com Arbitragem Científica
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