Konferenzbeitrag
The Role of Knowledge-based Features in Polarity Classification at Sentence Level
Though polarity classification has been extensively explored at document level, there has been little work investigating feature design at sentence level. Due to the small number of words within a sentence, polarity classification at sentence level differs substantially from document-level classification in that resulting bag-of-words feature vectors tend to be very sparse resulting in a lower classification accuracy. In this paper, we show that performance can be improved by adding features specifically designed for sentence-level polarity classification. We consider both explicit polarity information and various linguistic features. A great proportion of the improvement that can be obtained by using polarity information can also be achieved by using a set of simple domain-independent linguistic features.
- Language
-
Englisch
- Subject
-
Computerlinguistik
Text Mining
Polarität
Natürliche Sprache
Sprache
- Event
-
Geistige Schöpfung
- (who)
-
Wiegand, Michael
Klakow, Dietrich
- Event
-
Veröffentlichung
- (who)
-
Menlo Park, CA : AAAI Press
- (when)
-
2019-01-23
- URN
-
urn:nbn:de:bsz:mh39-84390
- Last update
-
2025-03-06T09:00:16+0100
Data provider
This object is provided by:
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the data provider.
Leibniz-Institut für Deutsche Sprache - Bibliothek. If you have any questions about the object, please contact the data provider.
Object type
- Konferenzbeitrag
Associated
- Wiegand, Michael
- Klakow, Dietrich
- Menlo Park, CA : AAAI Press
Time of origin
- 2019-01-23
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Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Evaluating the Morphological Compositionality of Polarity
The Role of Knowledge-based Features in Polarity Classification at Sentence Level
Predictive Features in Semi-Supervised Learning for Polarity Classification and the Role of Adjectives
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Hybrid Approaches for Sentiment Analysis
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Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification
Bootstrapping Supervised Machine-learning Polarity Classifiers with Rule-based Classification