Motamot: A Dataset for Revealing the Supremacy of Large Language Models over Transformer Models in Bengali Political Sentiment Analysis

Published: 13 May 2024| Version 1 | DOI: 10.17632/hdhnrrwdz2.1
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Description

The dataset "Motamot" containing 7,058 data points labeled with Positive and Negative sentiments, tailored specifically for Political Sentiment Analysis in the Bengali language. The dataset comprises 4,132 instances labeled as Positive and 2,926 instances labeled as Negative sentiments. Specifics of the Core Data: —------------------------------- Train 5647, Test 706, Validation 705 Train : —------------------------------- Positive: 3306 Negative: 2341 Test : —------------------------------- Positive: 413 Negative: 293 Validation : —------------------------------- Positive: 413 Negative: 292

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Institutions

Ahsanullah University of Science and Technology

Categories

Politics, Natural Language Processing, Public Sentiment, Sentiment Analysis

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