A preliminary model based on a child corpusIn contrast to many LSA semantic spaces in the literature which are based on domain -specific corpora, we chose to build a general child corpus intended to model children's semantic memory (Denhière, Lemaire, Bellissens & Jhean -Larose, 2004) and to offer a layer of basic semantic associations on top of which computational models of children cognitive processes can be designed and simulated (Lemaire, Denhière, Bellissens & Jhean -Larose, to appear).
Develop m e n t al dataWe possess little direct information on the nature and the properties of
In this article, we present a set of 12 norms that characterize emotional terms in French, English, German, Spanish, Italian, and Finnish. The high correlation between the norm values in the two emotional dimensions of valence and arousal suggests an interlingual homogeneity of emotional representations and allows a significant metanorm-EMONORM-to be established with 6,383 terms characterized in valence and 4,345 terms characterized in arousal. This metanorm is a resource for creating experimental materials in studies on language and emotions. Furthermore, we perform three tests using EMONORM, with the objectives of (1) identifying basic emotions from their valence and arousal values, (2) determining the orientation of texts referring to positive and negative emotions, and (3) evaluating the intensity of emotions expressed in texts. The results are highly similar to those for human judgments. Finally, we present EMOVAL/SEMOTEX, a Web application for static and dynamic valence and arousal emotional analysis of texts using EMONORM (http://www.semotex.fr).
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