  Sentiment analysis is one of the most fundamental tasks in Natural Language
Processing. Popular languages like English, Arabic, Russian, Mandarin, and also
Indian languages such as Hindi, Bengali, Tamil have seen a significant amount
of work in this area. However, the Marathi language which is the third most
popular language in India still lags behind due to the absence of proper
datasets. In this paper, we present the first major publicly available Marathi
Sentiment Analysis Dataset - L3CubeMahaSent. It is curated using tweets
extracted from various Maharashtrian personalities' Twitter accounts. Our
dataset consists of ~16,000 distinct tweets classified in three broad classes
viz. positive, negative, and neutral. We also present the guidelines using
which we annotated the tweets. Finally, we present the statistics of our
dataset and baseline classification results using CNN, LSTM, ULMFiT, and
BERT-based deep learning models.
