PropXplain: Can LLMs Enable Explainable Propaganda Detection?
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arXiv
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| Hauptverfasser: | , , , , , , |
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| Format: | Preprint |
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2025
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| author | Hasanain, Maram Hasan, Md Arid Kmainasi, Mohamed Bayan Sartori, Elisa Shahroor, Ali Ezzat Martino, Giovanni Da San Alam, Firoj |
| author_facet | Hasanain, Maram Hasan, Md Arid Kmainasi, Mohamed Bayan Sartori, Elisa Shahroor, Ali Ezzat Martino, Giovanni Da San Alam, Firoj |
| contents | There has been significant research on propagandistic content detection across different modalities and languages. However, most studies have primarily focused on detection, with little attention given to explanations justifying the predicted label. This is largely due to the lack of resources that provide explanations alongside annotated labels. To address this issue, we propose a multilingual (i.e., Arabic and English) explanation-enhanced dataset, the first of its kind. Additionally, we introduce an explanation-enhanced LLM for both label detection and rationale-based explanation generation. Our findings indicate that the model performs comparably while also generating explanations. We will make the dataset and experimental resources publicly available for the research community (https://github.com/firojalam/PropXplain). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_16550 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | PropXplain: Can LLMs Enable Explainable Propaganda Detection? Hasanain, Maram Hasan, Md Arid Kmainasi, Mohamed Bayan Sartori, Elisa Shahroor, Ali Ezzat Martino, Giovanni Da San Alam, Firoj Computation and Language 68T50 F.2.2; I.2.7 There has been significant research on propagandistic content detection across different modalities and languages. However, most studies have primarily focused on detection, with little attention given to explanations justifying the predicted label. This is largely due to the lack of resources that provide explanations alongside annotated labels. To address this issue, we propose a multilingual (i.e., Arabic and English) explanation-enhanced dataset, the first of its kind. Additionally, we introduce an explanation-enhanced LLM for both label detection and rationale-based explanation generation. Our findings indicate that the model performs comparably while also generating explanations. We will make the dataset and experimental resources publicly available for the research community (https://github.com/firojalam/PropXplain). |
| title | PropXplain: Can LLMs Enable Explainable Propaganda Detection? |
| topic | Computation and Language 68T50 F.2.2; I.2.7 |
| url | https://arxiv.org/abs/2502.16550 |