Südwestdeutscher Verlag für Hochschulschriften Opinion mining and lexical affect sensing: Computer-aided analysis of opinions and emotions in texts

Product Description This dissertation describes an interdisciplinary study that considers linguistic and psychological findings to perform computer-aided categorization of opinions and emotions in texts. It discusses various emotional corpora (movie reviews, weblogs, product reviews, and natural-language dialogues) and describes different approaches to affect classification of their texts: a statistical approach that utilizes lexical, deictic, stylometric, and grammatical information; a semantic approach that relies on emotional dictionaries and on deep grammatical analysis; a hybrid approach that combines the statistical approach and the semantic approach. Furthermore, this thesis explores affect sensing using multimodal fusion that utilizes lexical and acoustic data. In conclusion, the thesis discusses significant contributions and describes future work. Review The thesis presents approaches to emotion recognition from texts belonging to several emotional corpora. Four approaches are experimented and discussed in detail, namely (1) the statistical approach based on data mining techniques; (2) the semantic approach leveraging on semantic features and grammatical interdependencies; (3)  the hybrid approach that combines the statistical approach and the semantic approach; and finally (4) the multimodal-fusion that builds upon the linguistic modality and acoustic modality.The importance of automatically detecting emotions is motivated by the benefits that emotionally-intelligent technical artifacts would bring to humans (p. 4)The PhD thesis ” Opinion mining and lexical affect sensing ” is a valuable contribution to automatic emotion identification. It has a broad experimental scope since four main approaches with several variants are presented, discussed and assessed by the authors in terms of performance and potential. The author, Alexander Osherenko, has successfully capitalized on this research work by founding his own company, Socioware (socioware.de). Dr Marina Santini About the Author Alexander Osherenko graduated from University of Applied Sciences, Hamburg with the B.Sc. degree in computer science. He obtained his M. Sc. degree in computer science from Humboldt University, Berlin and the PhD degree from University of Augsburg, Germany.