Computer Science > Computation and Language
arXiv:2502.16550 (cs)
[Submitted on 23 Feb 2025]
Title:Reasoning About Persuasion: Can LLMs Enable Explainable Propaganda Detection?
Authors:Maram Hasanain,Md Arid Hasan,Mohamed Bayan Kmainasi,Elisa Sartori,Ali Ezzat Shahroor,Giovanni Da San Martino,Firoj Alam
View a PDF of the paper titled Reasoning About Persuasion: Can LLMs Enable Explainable Propaganda Detection?, by Maram Hasanain and 6 other authors
View PDFHTML (experimental)Abstract: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.
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2502.16550 [cs.CL] |
| (orarXiv:2502.16550v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2502.16550 arXiv-issued DOI via DataCite |
Full-text links:
Access Paper:
- View PDF
- HTML (experimental)
- TeX Source
- Other Formats
View a PDF of the paper titled Reasoning About Persuasion: Can LLMs Enable Explainable Propaganda Detection?, by Maram Hasanain and 6 other authors
References & Citations
Bookmark
Bibliographic and Citation Tools
Bibliographic Explorer(What is the Explorer?)
Connected Papers(What is Connected Papers?)
Litmaps(What is Litmaps?)
scite Smart Citations(What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv(What is alphaXiv?)
CatalyzeX Code Finder for Papers(What is CatalyzeX?)
DagsHub(What is DagsHub?)
Gotit.pub(What is GotitPub?)
Hugging Face(What is Huggingface?)
Papers with Code(What is Papers with Code?)
ScienceCast(What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower(What are Influence Flowers?)
CORE Recommender(What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community?Learn more about arXivLabs.