Please use this identifier to cite or link to this item: http://hdl.handle.net/10174/20659

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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