Political-RAG
Using generative AI to extract political information from media content
Bibliographic Data
| ID | 6436205 |
|---|---|
| Authors | Muhammad Arslan (0000-0003-3682-7002, Laboratoire Interdisciplinaire Carnot de Bourgogne), Saba Munawar (0000-0001-6934-5857, National University of Computer and Emerging Sciences), Christophe Cruz (0000-0002-5611-9479, Laboratoire Interdisciplinaire Carnot de Bourgogne) |
| Year | 2024 |
| Volume | 22 |
| Issue | 4 |
| Pages | 479-494 |
| Publication date | 2024-10-23 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Journal of Information Technology & Politics (JOURNAL) |
| Journal identifiers | ISSN: 1933-169X • E-ISSN: 1933-1681 |
| Publisher | Routledge (PUBLISHER • GB) |
| DOI | 10.1080/19331681.2024.2417263 |
| OpenAlex | W4403692760 |
| Language | EN |
| References cited | 11 |
International audience
Data science · Event (particle physics · Generative grammar · Information extraction · Natural language · Natural Language Generation · Natural language processing · Political communication · Political science · Politics · Sentiment analysis · Social media · Task (project management · World Wide Web · Computational and Text Analysis Methods · Computer Science · Sentiment Analysis and Opinion Mining · Topic Modeling · Artificial Intelligence
Machine learning and Natural Language Processing of social media data for event detection in smart cities
Handbook of Computational Social Science for Policy
Large language models and political science
Media Monitoring by Means of Speech and Language Indexing for Political Analysis
Sentiment is Not Stance
Views to a Kill
Protest Event Analysis
| Citation velocity | historical |
|---|---|
| Highly cited | No |