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Title: Multilingual author profiling using word embedding averages and svms
Authors: Bayot, Roy
Gonçalves, Teresa
Issue Date: 2016
Publisher: IEEE Xplore
Citation: Roy Bayot and Teresa Gonçalves. Multilingual author profiling using word embedding averages and svms. In SKIMA’2016 – 10th International Conference on Software, Knowledge, Information Management and Applications, Chengdu, CN, December 2016. IEEE Xplore.
Abstract: This paper describes an experiment done to investigate author profiling of tweets in English and Spanish, particularly for cross genre evaluation. Profiling consists of age and gender classification. The training sets were taken from tweets while genres for evaluation come from blogs, hotel reviews, other tweets collected in a different time, as well as other social media. Comparisons were done between tfidf as a baseline and average of word vectors, using a Support Vector Machine algorithm. Results show that using average of word vectors outperforms tfidf in most cross genre problems for age and gender.
Type: article
Appears in Collections:INF - Artigos em Livros de Actas/Proceedings

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