UA-ZBSA: A Headline Emotion Classification through Web Information

Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval-2007), pages 334–337, Prague, June 2007. c⃝2007 Association for Computational Linguistics UA-ZBSA: A Headline Emotion Classification through Web Information Zornitsa Kozareva, Borja Navarro, Sonia V´azquez, Andr´es Montoyo DLSI, University of Alicante Carretera de San Vicente S/N Alicante, Spain 03080 zkozareva,borja,svazquez,montoyo@dlsi.ua.es Abstract This paper presents a headline emotion clas- sification approach based on frequency and co-occurrence information collected from the World Wide Web. The content words of a headline (nouns, verbs, adverbs and adjec- tives) are extracted in order to form different bag of word pairs with the joy, disgust, fear, anger, sadness and surprise emotions. For each pair, we compute the Mutual Informa- tion Score which is obtained from the web occurrences of an emotion and the content words. Our approach is based on the hypoth- esis that group of words which co-occur to- gether across many documents with a given emotion are highly probable to express the same emotion. 1 Introduction The subjective analysis of a text is becoming impor- tant for many Natural Language Processing (NLP) applications such as Question Answering, Informa- tion Extraction, Text Categorization among others (Shanahan et al., 2006). The resolution of this prob- lem can lead to a complete, realistic and coher- ent analysis of the natural language, therefore ma- jor attention is drawn to the opinion, sentiment and emotion analysis, and to the identification of be- liefs, thoughts, feelings and judgments (Quirk et al., 1985), (Wilson and Wiebe, 2005). The aim of the Affective Text task is to clas- sify a set of news headlines into six types of emo- tions: “anger”, “disgust”, “fear”, “joy”, “sadness” and “surprise”. In order to be able to conduct such multi-category analysis, we believe that first we need a comprehensive theory of what a human emotion is, and then we need to understand how the emotion is expressed and transmitted within the nat- ural language. These aspects rise the need of syn- tactic, semantic, textual and pragmatic analysis of a text (Polanyi and Zaenen, 2006). However, some of the major drawbacks in this field are related to the manual or automatic acquisition of subjective ex- pressions, as well as to the lack of resources in terms of coverage. For this reason, our current emotion classification approach is based on frequency and co-occurrence bag of word counts collected from the World Wide Web. Our hypothesis is that words which tend to co- occur across many documents with a given emotion are highly probable to express this emotion. The rest of the paper is organized as follows. In Section 2 we review some of the related work, in Section 3 we describe our web-based emotion classi- fication approach for which we show a walk-through example in Section 4. A discussion of the obtained results can be found in Section 5 and finally we con- clude in Section 6. 2 Related work Our approach for emotion classification is based on the idea of (Hatzivassiloglou and McKeown, 1997) and is similar to …

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