TY  - CHAP
U1  - Buchbeitrag
A1  - Wiegand, Michael
A1  - Wolf, Maximilian
A1  - Ruppenhofer, Josef
T1  - Negation modeling for German polarity classification
T2  - Language technologies for the challenges of the digital age. 27th International Conference, GSCL 2017 Berlin, Germany, September 13 – 14, 2017. Proceedings
N2  - We present an approach for modeling German negation in open-domain fine grained sentiment analysis. Unlike most previous work in sentiment analysis, we assume that negation can be conveyed by many lexical units (and not only common negation words) and that different negation words have different scopes. Our approach is examined on a new dataset comprising sentences with mentions of polar expressions and various negation words. We identify different types of negation words that have the same scopes. We show that already negation modeling based on these types largely outperforms traditional negation models which assume the same scope for all negation words and which employ a window-based scope detection rather than a scope detection based on syntactic information.
T3  - Lecture Notes in Artificial Intelligence - 10713 
KW  - Deutsch
KW  - Negation
KW  - Semantische Analyse
KW  - Automatische Sprachanalyse
Y1  - 2018
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-69091
SN  - 978-3-319-73705-8
SB  - 978-3-319-73705-8
U6  - https://doi.org/10.1007/978-3-319-73706-5
DO  - https://doi.org/10.1007/978-3-319-73706-5
SP  - 95
EP  - 111
PB  - Springer
CY  - Cham, Switzerland
ER  -