Zusammenfassung
Mit der zunehmenden Menge textueller Daten im Web 2.0 wächst auch die Notwendigkeit der maschinellen Auswertung dieser Daten, beispielsweise um in Texten geäußerte Meinungen aufzuspüren (Opinion Mining). Im vorliegenden Beitrag wird das Aspect-based Opinion Mining – ein Verfahren mit sehr hohem Detaillierungsgrad – für deutschsprachige Texte anhand eines Projekts für die Versicherungswirtschaft vorgestellt. Es wird gezeigt, dass in Bewertungsplattformen geäußerte Meinungen zu Produkten und Services von Versicherungen mit einer Genauigkeit von etwa 90% und einer Vollständigkeit von ca. 80% für positive und ca. 60% für negative Meinungen erkannt werden können.
This is a preview of subscription content, access via your institution.
Buying options
Preview
Unable to display preview. Download preview PDF.
Literatur
Baccianella, S./ Esuli, A./ Sebastiani, F. (2010): SentiWordNet 3.0: An Enhanced Lexical Resource for Sentiment Analysis and Opinion Mining. In: Proceedings of the 7th International Conference on Language Resources and Evaluation (LREC-2010).
Bosco, C./ Patti, V./ Bolioli, A. (2013): Developing Corpora for Sentiment Analysis: The Case of Irony and Senti-TUT. In; Intelligent Systems, IEEE, Volume: 28, Issue: 2, S. 55–63.
Carvalho, P./ Sarmento, L./ Silva, M. J./ Oliviera, E. de. (2009): Clues for Detcting Irony in User Generated Contents: Oh…!! It’s “so easy”; -). In: Proceedings of the 1st International CIKM Workshop on Topic-Sentiment Analysis for Mass Opinion Measurement (TSA-2009).
Clematide, S./ Klenner M. (2010): Evaluation and Extension of a Polarity Lexicon for German. In: Proceedings of the 1st Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA-2010).
Hu, X./ Liu, B. (2004): Mining and Summarizing Customer Reviews. In: Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2004).
Kouloumpis, E./ Wilson, T./ Moore, J. (2011): Twitter sentiment analysis: The good the bad and the omg! In: Proceedings of the 5th International AAAI Conference on Weblogs and Social Media.
Jindal, N./ Liu, B. (2006): Identifying comparative sentences in text documents. In: Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2006).
Liu, Bing (2012): Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers.
Liu, B./ Hu, M./ Cheng, J. (2005): Opinion Observer: Analyzing and Comparing Opinions on the Web. In: Proceedings of the 14th International Wolrd Wide Web Conference (WWW-2005).
Pang, B./ Lee, L./ Vaithyanathan, S. (2002): Thumbs up?: Sentiment Classification Using Machine learning Techniques. In: Proceedings of Conference on Empirical Methods in Natural Language Processing (EMNLP-2002).
Rill, S./ Drescher, J./ Reinel, D./ Scheidt, J./ Schütz, O./ Wogenstein, F./ Simon, D. (2012a): A Generic Approach to Generate Opinion Lists of Phrases for Opinion Mining Applications. In: Proceedings of the First International Workshop of Sentiment Discovery and Opinion Mining (WISDOM). ACM.
Rill, S./ Adolph, S./ Drescher, J./ Reinel, D./ Scheidt, J./ Schütz, O./ Wogenstein, F./ Zicari, R. V./ Korfiatis, N. (2012b): A Phrase-Based Opinion List for the German Language. In: Proceedings of the 1st Workshop on Practice and Theory of Opinion Mining and Sentiment Analysis (PATHOS).
Rill, S./ Drescher, J./ Reinel, D./ Scheidt, J./ Wogenstein, F. (2012c): Particular Requirements on Opinion Mining for the Insurance Business. In: Proceedings of the 2nd International Conference on Advances in Information Mining and Management (IMMM).
Takamura, H./ Inui, T./ Okumura, M. (2005): Extracting Semantic Orientations of Words using Spin Model. In: Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL-2005).
Turney, P. D. (2002): Thumbs up or thumbs down?: Semantic Orientation Applied to Unsupervised Classification of Reviews. In: Proceedings of Annual Meeting of the Association for Computational Linguistics (ACL-2002).
Waltinger, U. (2010): GermanPolarityClues: A Lexical Resource for German Sentiment Analysis. In: Proceedings of the 7th International Conference on language Resources and Evaluation (LREC-2010).
Wiebe, J./ Bruce, R. F./ O’Hara, T. P. (1999): Development and Use of a Gold-Standard Data Set for Subjectivity Classification. In: Proceedings of the Association for Computational Linguistics (ACL-1999).
Wilson, T./ Wiebe, J./ Hoffmann, P. (2005): Recognizing Contextual Polarity in Phrase- Level Sentiment Analysis. In: Proceedings of the Human Language Technology Conference (HTL-2005).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer Fachmedien Wiesbaden
About this chapter
Cite this chapter
Reinel, D., Scheidt, J. (2015). Automatische Auswertung von Kundenmeinungen – Opinion Mining am Beispiel eines Projekts für die Versicherungswirtschaft. In: Dialogmarketing Perspektiven 2014/2015. Springer Gabler, Wiesbaden. https://doi.org/10.1007/978-3-658-08876-7_6
Download citation
DOI: https://doi.org/10.1007/978-3-658-08876-7_6
Published:
Publisher Name: Springer Gabler, Wiesbaden
Print ISBN: 978-3-658-08875-0
Online ISBN: 978-3-658-08876-7
eBook Packages: Business and Economics (German Language)