TY - CHAP U1 - Konferenzveröffentlichung A1 - Wiegand, Michael A1 - Klakow, Dietrich ED - Calzolari, Nicoletta ED - Choukri, Khalid ED - Maegaard, Bente ED - Mariani, Joseph ED - Odijk, Jan ED - Piperidis, Stelios ED - Rosner, Mike ED - Tapias, Daniel T1 - Predictive Features for Detecting Indefinite Polar Sentences T2 - Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), May 17-23, 2010, Valletta, Malta N2 - In recent years, text classification in sentiment analysis has mostly focused on two types of classification, the distinction between objective and subjective text, i.e. subjectivity detection, and the distinction between positive and negative subjective text, i.e. polarity classification. So far, there has been little work examining the distinction between definite polar subjectivity and indefinite polar subjectivity. While the former are utterances which can be categorized as either positive or negative, the latter cannot be categorized as either of these two categories. This paper presents a small set of domain independent features to detect indefinite polar sentences. The features reflect the linguistic structure underlying these types of utterances. We give evidence for the effectiveness of these features by incorporating them into an unsupervised rule-based classifier for sentence-level analysis and compare its performance with supervised machine learning classifiers, i.e. Support Vector Machines (SVMs) and Nearest Neighbor Classifier (kNN). The data used for the experiments are web-reviews collected from three different domains. KW - Computerlinguistik KW - Information Extraction KW - Polarität KW - Natürliche Sprache KW - Maschinelles Lernen KW - Document Classification KW - Semantics KW - Information Extraction KW - Information Retrieval KW - Text Categorisation Y1 - 2010 U6 - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-85052 UN - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-85052 UR - https://aclanthology.info/papers/L10-1250/l10-1250 SN - 2-9517408-6-7 SB - 2-9517408-6-7 SP - 3092 EP - 3096 PB - European Language Resources Association CY - Paris ER -