Papers with social problem

2 papers
Beyond Good Intentions: Reporting the Research Landscape of NLP for Social Good (2023.findings-emnlp)

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Challenge: Recent advances in natural language processing (NLP) have created a vast number of applications that are aimed at social good applications.
Approach: They propose a dataset with three tasks that can help identify NLP4SG papers and characterize the NLP landscape by: (1) identifying the papers that address a social problem, (2) mapping them to the corresponding UN Sustainable Development Goals, and (3) identifying their methods.
Outcome: The proposed dataset can help identify NLP4SG papers and characterize the NLP landscape by: (1) identifying the papers that address a social problem, (2) mapping them to the corresponding UN Sustainable Development Goals (SDGs), and (3) identifying their methods.
Interpretable Short Video Rumor Detection Based on Modality Tampering (2024.lrec-main)

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Challenge: Existing methods to detect rumors from the perspective of modality tampering are labor-intensive and time-consuming.
Approach: They propose a short video rumor detection framework that integrates modality tampering detection and inter-modal matching into a model to detect modality-tampers and interpretability mechanisms to make the results more reasonable.
Outcome: The proposed model improves on the short video rumor dataset by 4.6%-12% compared with other models and can explain whether the short clip is a rumour or not through the perspective of modality tampering.

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