Content and Style Features for Automatic Detection of Users’ Intentions in Tweets

Helena Gómez-Adorno,Manuel Montes,Grigori Sidorov,David Pinto,Rodrigo Alfaro

doi:10.1007/978-3-319-12027-0_10

Content and Style Features for Automatic Detection of Users’ Intentions in Tweets

Helena Gómez-Adorno, Manuel Montes + Show 3 more

https://doi.org/10.1007/978-3-319-12027-0_10

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Publication Date: Jan 1, 2014

Citations: 22

Affiliation: Instituto Politécnico Nacional, National Institute of Astrophysics, Optics and Electronics, Benemérita Universidad Autónoma de Puebla, Pontificial Catholic University of Valparaiso

#Content Features #Style Features + Show 8 more

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Abstract

The aim of this paper is to evaluate the use of content and style features in automatic classification of intentions of Tweets. For this we propose different style features and evaluate them using a machine learning approach. We found that although the style features by themselves are useful for the identification of the intentions of tweets, it is better to combine such features with the content ones. We present a set of experiments, where we achieved a 9.46 % of improvement on the overall performance of the classification with the combination of content and style features as compared with the content features.

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