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By Joseph Barrell

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For instance, emotions have been studied with respect to facial expressions [13], action tendencies [17], physiological activity [4], or subjective experience [36]. Annotating and Identifying Emotions in Text 23 On the other hand, one of the most convenient ways to access emotional content is through the use and analysis of language, and thus a number of previous efforts have been concentrated on the development of affective lexical resources. One the first studies dealing with the referential structure of an affective lexicon is that of [29], consisting of an analysis of 500 words taken form the literature on emotions.

Aylett, R. ) Animating expressive characters for social interactions, pp. 123–141. John Benjamins Publ. : Negotiated collusion: modelling social language and its relationship effects in intelligent agents. : Social Attitude Towards a Conversational Character. In: Proceedings of the 15th IEEE International Symposium on Robot and Human Interactive Communication, RO-MAN 2006, pp. : A Bayesian method for the induction of probabilistic networks from data. : Interpretation of User’s Feedback in Human-Robot Interaction.

Prec. Rec. 27 CLaC: This team submitted two systems [3] to the competition: an unsupervised knowledge-based system (CLaC) and a supervised corpus-based system (CLaCNB). Both systems were used for assigning positive/negative and neutral valence to headlines on the scale [-100,100]. CLaC: The CLaC system relies on a knowledge-based domain-independent unsupervised approach to headline valence detection and scoring. The system uses three main kinds of knowledge: a list of sentiment-bearing words, a list of valence shifters and a set of rules that define the scope and the result of the combination of sentimentbearing words and valence shifters.

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