Semi-automatic Building Method for a Multidimensional Affect Dictionary for a New Language

Detecting the tone or emotive content of a text message is increasingly important in many natural language processing applications. Examples of such applications are rating new books or movies or products, judging the mood of a customer e-mail and routing it accordingly, measuring reputation that a person or a product has in the blogosphere. While for the English language there exists a number of affect, emotive, opinion, or affect computer-usable lexicons for automatically processing text, other languages rarely possess these primary resources. Here we present a semi-automatic technique for quickly building a multidimensional affect lexicon for a new language. Most of the work consists of defining 44 paired affect directions (e.g. love-hate, courage-fear, . . . ) and choosing a small number of seed words for each dimension. From this initial investment, we show how a first pass affect lexicon can be created for new language, using a SVM classifier trained on a feature space produced ...

• Type: Conference
• Year: 2008
• Where: LREC
• Authors: Guillaume Pitel, Gregory Grefenstette
• Keywords: Affect Lexicon, Education, LREC 2008, Multidimensional Affect Lexicon, Pass Affect Lexicon