Sarcasm detection involves predicting whether a given text is sarcastic, a challenging task in sentiment analysis. While significant research has been conducted for languages like English, Czech, and Italian, limited work exists for Indian languages such as Hindi, Tamil, and Bengali. Marathi, being the third most spoken language in India, has seen little progress in sarcasm detection, mainly due to the lack of suitable datasets.

Dataset Files

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[1] Pravin Patil, Satish Kolhe, "MarathiSarc", IEEE Dataport, 2024. [Online]. Available: http://dx.doi.org/10.21227/1d55-2f63. Accessed: Mar. 18, 2025.
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doi = {10.21227/1d55-2f63},
url = {http://dx.doi.org/10.21227/1d55-2f63},
author = {Pravin Patil; Satish Kolhe },
publisher = {IEEE Dataport},
title = {MarathiSarc},
year = {2024} }
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T1 - MarathiSarc
AU - Pravin Patil; Satish Kolhe
PY - 2024
PB - IEEE Dataport
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Pravin Patil, Satish Kolhe. (2024). MarathiSarc. IEEE Dataport. http://dx.doi.org/10.21227/1d55-2f63
Pravin Patil, Satish Kolhe, 2024. MarathiSarc. Available at: http://dx.doi.org/10.21227/1d55-2f63.
Pravin Patil, Satish Kolhe. (2024). "MarathiSarc." Web.
1. Pravin Patil, Satish Kolhe. MarathiSarc [Internet]. IEEE Dataport; 2024. Available from : http://dx.doi.org/10.21227/1d55-2f63
Pravin Patil, Satish Kolhe. "MarathiSarc." doi: 10.21227/1d55-2f63