On the impact of seed words on sentiment polarity lexicon induction

Dame Jovanoski, Veno Pachovski, Preslav Nakov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Sentiment polarity lexicons are key resources for sentiment analysis, and researchers have invested a lot of efforts in their manual creation. However, there has been a recent shift towards automatically extracted lexicons, which are orders of magnitude larger and perform much better. These lexicons are typically mined using bootstrapping, starting from very few seed words whose polarity is given, e.g., 50-60 words, and sometimes even just 5-6. Here we demonstrate that much higher-quality lexicons can be built by starting with hundreds of words and phrases as seeds, especially when they are in-domain. Thus, we combine (f) mid-sized high-quality manually crafted lexicons as seeds and (if) bootstrapping, in order to build large-scale lexicons.

Original languageEnglish
Title of host publicationCOLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016
Subtitle of host publicationTechnical Papers
PublisherAssociation for Computational Linguistics, ACL Anthology
Pages1557-1567
Number of pages11
ISBN (Print)9784879747020
Publication statusPublished - 1 Jan 2016
Event26th International Conference on Computational Linguistics, COLING 2016 - Osaka, Japan
Duration: 11 Dec 201616 Dec 2016

Other

Other26th International Conference on Computational Linguistics, COLING 2016
CountryJapan
CityOsaka
Period11/12/1616/12/16

    Fingerprint

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Language and Linguistics
  • Linguistics and Language

Cite this

Jovanoski, D., Pachovski, V., & Nakov, P. (2016). On the impact of seed words on sentiment polarity lexicon induction. In COLING 2016 - 26th International Conference on Computational Linguistics, Proceedings of COLING 2016: Technical Papers (pp. 1557-1567). Association for Computational Linguistics, ACL Anthology.