Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features
- 1. Spoken Language Systems, Saarland University
- 2. Institute for German Language, Mannheim
- 3. Center for Information and Language Processing, LMU Munich
Description
We present a major step towards the creation of the first high-coverage lexicon of polarity shifters. In this work, we bootstrap a lexicon of verbs by exploiting various linguistic features. Polarity shifters, such as “abandon”, are similar to negations (e.g. “not”) in that they move the polarity of a phrase towards its inverse, as in “abandon all hope”. While there exist lists of negation words, creating comprehensive lists of polarity shifters is far more challenging due to their sheer number. On a sample of manually annotated verbs we examine a variety of linguistic features for this task. Then we build a supervised classifier to increase coverage. We show that this approach drastically reduces the annotation effort while ensuring a high-precision lexicon. We also show that our acquired knowledge of verbal polarity shifters improves phrase-level sentiment analysis.
Supplementary Data
- Verbal Shifter Lexicon: doi:10.5281/zenodo.3364812
- Sentiment Verb Phrases: doi:10.5281/zenodo.3364812
- Word Embedding: doi:10.5281/zenodo.3370051
Notes
Files
Schulder, Wiegand, Ruppenhofer, Roth (2017). Towards Bootstrapping a Polarity Shifter Lexicon using Linguistic Features. Proceedings of IJCNLP.pdf
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Additional details
Related works
- Is identical to
- Conference paper: https://www.aclweb.org/anthology/I17-1063 (URL)
- Is supplemented by
- Dataset: 10.5281/zenodo.3364812 (DOI)
- Dataset: 10.5281/zenodo.3370051 (DOI)