WordNet: a lexical database for English
Communications of the ACM
An algorithm for suffix stripping
Readings in information retrieval
A model of textual affect sensing using real-world knowledge
Proceedings of the 8th international conference on Intelligent user interfaces
Describing the emotional states that are expressed in speech
Speech Communication - Special issue on speech and emotion
From once upon a time to happily ever after: Tracking emotions in mail and books
Decision Support Systems
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
EmoTales: creating a corpus of folk tales with emotional annotations
Language Resources and Evaluation
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This paper presents an approach to automated marking up of texts with emotional labels 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 The proposed algorithm for automated mark up of text mirrors closely the steps taken during feature extraction, employing for the actual assignment of emotional features a combination of the LEW resource, the ANEW word list, and WordNet for knowledge-based expansion of words not occurring in either The algorithm for automated mark up is tested and the results are discussed with respect to three main issues: relative adequacy of each one of the representations used, correctness and coverage of the proposed algorithm, and additional techniques and solutions that may be employed to improve the results.