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Autor*innen: Ma, Zheng; Nam, Jinseok; Weihe, Karsten
Titel: Improve sentiment analysis of citations with author modelling
Aus: Association for Computational Linguistics (Hrsg.): Proceedings of the 7th workshop on computational approaches to subjectivity, sentiment and Social media analysis (WASSA 2016) held in conjunction with NAACL 2016, Stroudsburg; PA: Association for Computational Linguistics, 2016 , S. 122-127
URL: http://www.aclweb.org/anthology/W16-0420
Dokumenttyp: 4. Beiträge in Sammelbänden; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Schlagwörter: Automatisierung; Autor; Bibliometrie; Modell; Text; Textanalyse; Zitat
Abstract (english): In this paper, we introduce a novel approach to sentiment polarity classification of citations, which integrates data about the authors' reputation. More specifically, our method extends the h-index with citation polarities and utilizes it in sentiment classification of citation sentences. Our computational results show that our method yields significant improvement in terms of classification performance. (DIPF/Orig.)
DIPF-Abteilung: Informationszentrum Bildung