Automatic Classification of Tweets for Analyzing Communication Behavior of Museums
Nicolas Foucault, Antoine Courtin · 2016
In this paper, we present a study on tweet classification which aims to define the communication behavior of the 103 French museums that participated in 2014 in the Twitter operation: MuseumWeek.The tweets were automatically classified in four communication categories: sharing experience, promoting participation, interacting with the community, and promoting-informing about the institution.Our classification is multi-class.It combines Support Vector Machines and Naive Bayes methods and is supported by a selection of eighteen subtypes of features of four different kinds: metadata information, punctuation marks, tweet-specific and lexical features.It was tested against a corpus of 1,095 tweets manually annotated by two experts in Natural Language Processing and Information Communication and twelve Community Managers of French museums.We obtained an state-of-the-art result of F1-score of 72% by 10-fold crossvalidation.This result is very encouraging since is even better than some state-of-the-art results found in the tweet classification literature.