Konferenzbeitrag
Separating Actor-View from Speaker-View Opinion Expressions using Linguistic Features
We examine different features and classifiers for the categorization of opinion words into actor and speaker view. To our knowledge, this is the first comprehensive work to address sentiment views on the word level taking into consideration opinion verbs, nouns and adjectives. We consider many high-level features requiring only few labeled training data. A detailed feature analysis produces linguistic insights into the nature of sentiment views. We also examine how far global constraints between different opinion words help to increase classification performance. Finally, we show that our (prior) word-level annotation correlates with contextual sentiment views.
- Sprache
-
Englisch
- Thema
-
Propositionale Einstellung
Information Extraction
Automatische Textanalyse
Meinungsverb
Sprache
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Wiegand, Michael
Schulder, Marc
Ruppenhofer, Josef
- Ereignis
-
Veröffentlichung
- (wer)
-
San Diego (California) : Association for Computational Linguistics
- (wann)
-
2016-11-08
- URN
-
urn:nbn:de:bsz:mh39-55113
- Letzte Aktualisierung
-
06.03.2025, 09:00 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Leibniz-Institut für Deutsche Sprache - Bibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Leibniz-Institut für Deutsche Sprache - Bibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Konferenzbeitrag
Beteiligte
- Wiegand, Michael
- Schulder, Marc
- Ruppenhofer, Josef
- San Diego (California) : Association for Computational Linguistics
Entstanden
- 2016-11-08
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