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

2020/07/23 by Subhra Jyoti Baroi, Nivedita Singh, Baroi, Subhra Jyoti +5
Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Sentiment Analysis and Opinion Mining #Topic Modeling

paper · pdf · doi:10.48550/arxiv.2007.12081

openalex publication_date 2020/07/23 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

Sentiment Analysis is the process of deciphering what a sentence emotes and\nclassifying them as either positive, negative, or neutral. In recent times,\nIndia has seen a huge influx in the number of active social media users and\nthis has led to a plethora of unstructured text data. Since the Indian\npopulation is generally fluent in both Hindi and English, they end up\ngenerating code-mixed Hinglish social media text i.e. the expressions of Hindi\nlanguage, written in the Roman script alongside other English words. The\nability to adequately comprehend the notions in these texts is truly necessary.\nOur team, rns2020 participated in Task 9 at SemEval2020 intending to design a\nsystem to carry out the sentiment analysis of code-mixed social media text.\nThis work proposes a system named NITS-Hinglish-SentiMix to viably complete the\nsentiment analysis of such code-mixed Hinglish text. The proposed framework has\nrecorded an F-Score of 0.617 on the test data.\n

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