NITS-Hinglish-SentiMix at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using an Ensemble Model

Subhra Jyoti Baroi, Nivedita Singh, Ringki Das, Thoudam Doren Singh

Abstract
Sentiment Analysis refers to the process of interpreting what a sentence emotes and classifying them as positive, negative, or neutral. The widespread popularity of social media has led to the generation of a lot of text data and specifically, in the Indian social media scenario, the code-mixed Hinglish text i.e, the words of Hindi language, written in the Roman script along with other English words is a common sight. The ability to effectively understand the sentiments in these texts is much needed. This paper proposes a system titled NITS-Hinglish to effectively carry out the sentiment analysis of such code-mixed Hinglish text. The system has fared well with a final F-Score of 0.617 on the test data.
Anthology ID:
2020.semeval-1.175
Volume:
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Month:
December
Year:
2020
Address:
Barcelona (online)
Venue:
SemEval
SIGs:
SIGLEX | SIGSEM
Publisher:
International Committee for Computational Linguistics
Note:
Pages:
1298–1303
Language:
URL:
https://aclanthology.org/2020.semeval-1.175
DOI:
10.18653/v1/2020.semeval-1.175
Bibkey:
Cite (ACL):
Subhra Jyoti Baroi, Nivedita Singh, Ringki Das, and Thoudam Doren Singh. 2020. NITS-Hinglish-SentiMix at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using an Ensemble Model. In Proceedings of the Fourteenth Workshop on Semantic Evaluation, pages 1298–1303, Barcelona (online). International Committee for Computational Linguistics.
Cite (Informal):
NITS-Hinglish-SentiMix at SemEval-2020 Task 9: Sentiment Analysis for Code-Mixed Social Media Text Using an Ensemble Model (Baroi et al., SemEval 2020)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.semeval-1.175.pdf
Data
SentiMix
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