SentiUrdu-1M: A large-scale tweet dataset for Urdu text sentiment analysis using weakly supervised learning.

ABSTRACT: Low-resource languages are gaining much-needed attention with the advent of deep learning models and pre-trained word embedding. Though spoken by more than 230 million people worldwide, Urdu is one such low-resource language that has recently gained popularity online and is attracting a lot of attention and support from the research community. One challenge faced by such resource-constrained languages is the scarcity of publicly available large-scale datasets for conducting any meaningful study. In this paper, we address this challenge by collecting the first-ever large-scale Urdu Tweet Dataset for sentiment analysis and emotion recognition. The dataset consists of a staggering number of 1, 140, 821 tweets in the Urdu language. Obviously, manual labeling of such a large number of tweets wo

SUBMITTER: Ghafoor A 

PROVIDER: S-EPMC10468080 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature