Konferenzbeitrag
Evaluating the Morphological Compositionality of Polarity
Unknown words are a challenge for any NLP task, including sentiment analysis. Here, we evaluate the extent to which sentiment polarity of complex words can be predicted based on their morphological make-up. We do this on German as it has very productive processes of derivation and compounding and many German hapax words, which are likely to bear sentiment, are morphologically complex. We present results of supervised classification experiments on new datasets with morphological parses and polarity annotations.
- Language
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Englisch
- Subject
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Natürliche Sprache
Computerlinguistik
Polarität
Text Mining
Automatische Sprachverarbeitung
semantische Analyse
Sprache
- Event
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Geistige Schöpfung
- (who)
-
Ruppenhofer, Josef
Steiner, Petra
Wiegand, Michael
- Event
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Veröffentlichung
- (who)
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Shoumen : Incoma Ltd.
- (when)
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2019-02-13
- URN
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urn:nbn:de:bsz:mh39-84917
- Last update
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06.03.2025, 9:00 AM CET
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
- Ruppenhofer, Josef
- Steiner, Petra
- Wiegand, Michael
- Shoumen : Incoma Ltd.
Time of origin
- 2019-02-13
Other Objects (12)
Evaluating the Morphological Compositionality of Polarity
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Automatically creating a lexicon of verbal polarity shifters: mono- and cross-lingual methods for German
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Opinion Holder and Target Extraction based on the Induction of Verbal Categories
Introducing a lexicon of verbal polarity shifters for English
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Evaluating the Morphological Compositionality of Polarity
Negation modeling for German polarity classification
Negation modeling for German polarity classification
Automatic generation of lexica for sentiment polarity shifters
Automatic generation of lexica for sentiment polarity shifters
Enhancing a Lexicon of Polarity Shifters through the Supervised Classification of Shifting Directions
Automatically creating a lexicon of verbal polarity shifters: mono- and cross-lingual methods for German
Exploiting emojis for abusive language detection
Opinion Holder and Target Extraction based on the Induction of Verbal Categories
Opinion Holder and Target Extraction based on the Induction of Verbal Categories
Introducing a lexicon of verbal polarity shifters for English
Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
Evaluating the Morphological Compositionality of Polarity
Negation modeling for German polarity classification
Negation modeling for German polarity classification
Automatic generation of lexica for sentiment polarity shifters
Automatic generation of lexica for sentiment polarity shifters
Enhancing a Lexicon of Polarity Shifters through the Supervised Classification of Shifting Directions
Automatically creating a lexicon of verbal polarity shifters: mono- and cross-lingual methods for German
Exploiting emojis for abusive language detection
Opinion Holder and Target Extraction based on the Induction of Verbal Categories
Opinion Holder and Target Extraction based on the Induction of Verbal Categories
Introducing a lexicon of verbal polarity shifters for English