Building a SentiWordNet for Odia

Gaurav Mohanty, Abishek Kannan, Radhika Mamidi


Abstract
As a discipline of Natural Language Processing, Sentiment Analysis is used to extract and analyze subjective information present in natural language data. The task of Sentiment Analysis has acquired wide commercial uses including social media monitoring tasks, survey responses, review systems, etc. Languages like English have several resources which aid in the task of Sentiment Analysis. SentiWordNet and Subjectivity WordList are examples of such tools and resources. With more data being available in native vernacular, language-specific SentiWordNet(s) have become essential. For resource poor languages, creating such SentiWordNet(s) is a difficult task to achieve. One solution is to use available resources in English and translate the final source lexicon to target lexicon via machine translation. Machine translation systems for the English-Odia language pair have not yet been developed. In this paper, we discuss a method to create a SentiWordNet for Odia, which is resource-poor, by only using resources which are currently available for Indian languages. The lexicon created, would serve as a tool for Sentiment Analysis related task specific to Odia data.
Anthology ID:
W17-5219
Volume:
Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Alexandra Balahur, Saif M. Mohammad, Erik van der Goot
Venue:
WASSA
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
143–148
Language:
URL:
https://aclanthology.org/W17-5219
DOI:
10.18653/v1/W17-5219
Bibkey:
Cite (ACL):
Gaurav Mohanty, Abishek Kannan, and Radhika Mamidi. 2017. Building a SentiWordNet for Odia. In Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, pages 143–148, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Building a SentiWordNet for Odia (Mohanty et al., WASSA 2017)
Copy Citation:
PDF:
https://aclanthology.org/W17-5219.pdf