Naslov
Debunking Sentiment Lexicons: A Case of Domain-Specific Sentiment Classification for Croatian

Autori
Gombar, Paula ; Medić, Zoran ; Alagić, Domagoj ; Šnajder, Jan

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing / - , 2017, 54-59

ISBN
978-1-945626-45-6

Skup
The 6th Workshop on Balto-Slavic Natural Language Processing

Mjesto i datum
Valencia, Španjolska, 04.04.2017

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Lexical semantics ; Sentiment analysis ; Sentiment lexicons ; Croatian ; Natural language processing

Sažetak
Sentiment lexicons are widely used as an intuitive and inexpensive way of tackling sentiment classification, often within a simple lexicon word-counting approach or as part of a supervised model. However, it is an open question whether these approaches can compete with supervised models that use only word- representation features. We address this question in the context of domain- specific sentiment classification for Croatian. We experiment with the graph- based acquisition of sentiment lexicons, analyze their quality, and investigate how effectively they can be used in sentiment classification. Our results indicate that, even with as few as 500 labeled instances, a supervised model substantially outperforms a word-counting model. We also observe that adding lexicon-based features does not significantly improve supervised sentiment classification.

Izvorni jezik
Engleski

Znanstvena područja
Računarstvo, Informacijske i komunikacijske znanosti

POVEZANOST RADA