TY  - CHAP
U1  - Buchbeitrag
A1  - Wiegand, Michael
A1  - Loda, Sylvette
A1  - Ruppenhofer, Josef
ED  - Calzolari, Nicoletta
ED  - Choukri, Khalid
ED  - Cieri, Christopher
ED  - Declerck, Thierry
ED  - Goggi, Sara
ED  - Hasida, Koiti
ED  - Isahara, Hitoshi
ED  - Maegaard, Bente
ED  - Mariani, Joseph
ED  - Mazo, Hélène
ED  - Moreno, Asuncion
ED  - Odijk, Jan
ED  - Piperidis, Stelios
ED  - Tokunaga, Takenobu
T1  - Disambiguation of verbal shifters
T2  - Proceedings of the eleventh international conference on language resources and evaluation (LREC 2018), 7-12 May 2018, Miyazaki, Japan
N2  - Negation is an important contextual phenomenon that needs to be addressed in sentiment analysis. Next to common negation function words, such as not or none, there is also a considerably large class of negation content words, also referred to as shifters, such as the verbs diminish, reduce or reverse. However, many of these shifters are ambiguous. For instance, spoil as in spoil your chance reverses the polarity of the positive polar expression chance while in spoil your loved ones, no negation takes place. We present a supervised learning approach to disambiguating verbal shifters. Our approach takes into consideration various features, particularly generalization features.
KW  - sentiment analysis
KW  - negation modeling
KW  - word-sense disambiguation
KW  - Semantische Analyse
KW  - Negation
KW  - Disambiguierung
Y1  - 2018
U6  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-74836
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-74836
UR  - http://www.lrec-conf.org/proceedings/lrec2018/summaries/58.html
SN  - 979-10-95546-00-9
SB  - 979-10-95546-00-9
SP  - 608
EP  - 612
PB  - European language resources association (ELRA)
CY  - Paris, France
ER  -