EmoTag: Automated Mark Up of Affective Information in Texts
نویسندگان
چکیده
This paper presents an approach to automated mark up of affective information in texts. The approach considers in parallel two possible representations of emotions: as emotional categories and emotional dimensions. For each representation, a corpus of example texts previously annotated by human evaluators is mined for an initial assignment of emotional features to words. This results in a List of Emotional Words (LEW) which becomes a useful resource for later automated mark up. EmoTag employs for the actual assignment of emotional features a combination of the LEW resource, the ANEW word list, WordNet for knowledge-based expansion of words not occurring in either and an ontology of emotional categories.
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