research-article

MahaEmoSen: Towards Emotion-aware Multimodal Marathi Sentiment Analysis

Authors:

Prasad Chaudhari,

Pankaj Nandeshwar,

Nagendra KumarAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 22, Issue 9

Article No.: 229, Pages 1 - 24

https://doi.org/10.1145/3618057

Published: 22 September 2023 Publication History

Abstract

With the advent of the Internet, social media platforms have witnessed an enormous increase in user-generated textual and visual content. Microblogs on platforms such as Twitter are extremely useful for comprehending how individuals feel about a specific issue through their posted texts, images, and videos. Owing to the plethora of content generated, it is necessary to derive an insight of its emotional and sentimental inclination. Individuals express themselves in a variety of languages and, lately, the number of people preferring native languages has been consistently increasing. Marathi language is predominantly spoken in the Indian state of Maharashtra. However, sentiment analysis in Marathi has rarely been addressed. In light of the above, we propose an emotion-aware multimodal Marathi sentiment analysis method (MahaEmoSen). Unlike the existing studies, we leverage emotions embedded in tweets besides assimilating the content-based information from the textual and visual modalities of social media posts to perform a sentiment classification. We mitigate the problem of small training sets by implementing data augmentation techniques. A word-level attention mechanism is applied on the textual modality for contextual inference and filtering out noisy words from tweets. Experimental outcomes on real-world social media datasets demonstrate that our proposed method outperforms the existing methods for Marathi sentiment analysis in resource-constrained circumstances.

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Cited By

Khade AYashwante PShetty D(2025)A Hybrid Sentiment and Emotion Analysis Model for Marathi Text Using Horse Herd Optimization, Bidirectional RNN, and Affective Cognitive ComputingCognitive Computing and Cyber Physical Systems10.1007/978-3-031-77081-4_2(11-24)Online publication date: 9-Feb-2025
https://doi.org/10.1007/978-3-031-77081-4_2
T V(2024)Enhancing User Experience through Emotion-Aware Interfaces: A Multimodal ApproachJournal of Innovative Image Processing10.36548/jiip.2024.1.0036:1(27-39)Online publication date: Mar-2024
https://doi.org/10.36548/jiip.2024.1.003

Index Terms

MahaEmoSen: Towards Emotion-aware Multimodal Marathi Sentiment Analysis
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22, Issue 9

September 2023

226 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3625383

Editor:
Imed Zitouni
Google, USA

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 September 2023

Online AM: 02 September 2023

Accepted: 11 August 2023

Received: 17 April 2023

Published in TALLIP Volume 22, Issue 9

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Cited By

Khade AYashwante PShetty D(2025)A Hybrid Sentiment and Emotion Analysis Model for Marathi Text Using Horse Herd Optimization, Bidirectional RNN, and Affective Cognitive ComputingCognitive Computing and Cyber Physical Systems10.1007/978-3-031-77081-4_2(11-24)Online publication date: 9-Feb-2025
https://doi.org/10.1007/978-3-031-77081-4_2
T V(2024)Enhancing User Experience through Emotion-Aware Interfaces: A Multimodal ApproachJournal of Innovative Image Processing10.36548/jiip.2024.1.0036:1(27-39)Online publication date: Mar-2024
https://doi.org/10.36548/jiip.2024.1.003

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