Author:
Kouloumpis Efthymios,Wilson Theresa,Moore Johanna
Abstract
In this paper, we investigate the utility of linguistic features for detecting the sentiment of Twitter messages. We evaluate the usefulness of existing lexical resources as well as features that capture information about the informal and creative language used in microblogging. We take a supervied approach to the problem, but leverage existing hashtags in the Twitter data for building training data.
Publisher
Association for the Advancement of Artificial Intelligence (AAAI)
Cited by
61 articles.
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