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In this paper, we describe one of the approaches of the participation of Universidade de Évora. Our approach is similar to usual methods where text is preprocessed, features are extracted, and then used in SVMs with cross validation. The main difference is that features used come from averages of word embeddings, specifically word2vec vectors. Using PAN… (More)
In this paper, we focused on profiling authors on age, gender, and five personality traits. The corpus consists of anonymized twitter posts categorized into 4 different languages. Our proposed approach was to use a combination of tfidf, function words, stylistic features, and text bigrams, and used an SVM for each task.
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… (More)