@inproceedings{
mamta2024aspectbased,
title={Aspect-Based Multimodal Mining: Unveiling Sentiments, Complaints, and Beyond in User-Generated Content},
author={Mamta Mamta and gopendra Vikram singh and Deepak Raju Kori and Asif Ekbal},
booktitle={ACM Multimedia 2024},
year={2024},
url={https://openreview.net/forum?id=PPJZV6XJL8}
}
Sentiment analysis and complaint identification are key tools in mining user preferences by measuring the polarity and breach of expectations. Recent works on complaint identification identify aspect categories and classify them into complaint or not-complaint classes. However, aspect category-based complaint identification provides high-level information about the features of products. 
In addition, it is also observed that the user sometimes does not complain about a specific aspect but expresses concern about specific aspects in a respectful way. Currently, uni-modal and multimodal studies do not differentiate between this thin line between complaint and concern. 
In this work, we propose the task of multimodal aspect term-based analysis beyond sentiments and complaints. It comprises of two sub-tasks, \textit{viz} (i) classification of the given aspect term into one of the four classes, \textit{viz.} praise, concern, complaint, and others, (ii) identification of the cause of praise, concern, and complaint classes. We propose a first benchmark explainable multimodal corpus annotated for aspect term-based complaints, praises, concerns, their corresponding causes, and sentiments. Further, we propose an effective technique for the joint learning of aspect term-based complaint/concern/praise identification and cause extraction tasks (primary tasks) where sentiment analysis is used as a secondary task to assist primary tasks and establish them as baselines for further research in this direction. Sample dataset has been made available at: \url{https://anonymous.4open.science/r/MAspectX-327E/README.md} The whole dataset will be made publicly available for research after acceptance of the paper.
Aspect-Based Multimodal Mining: Unveiling Sentiments, Complaints, and Beyond in User-Generated Content
Mamta Mamta gopendra Vikram singh Deepak Raju Kori Asif Ekbal