SemEval 2020 Task 11
As a further effort to develop/foster a community around the topic of propaganda detection, we are organising a shared task at SemEval 2020.
Developing tools to help readers detect the use of propaganda and analysing how propaganda and extremely-biased articles spread online.
Invited Talk @CNR Pisa - Giovanni presented the work on the propaganda techniques at CNR Pisa, Italy. (Dec, 2019)
Invited Talk @Facebook London - Giovanni presented Proppy and the work on fine-grained propaganda detection. Slides available. (Oct. 2019)
Accepted Poster @Truth and Trust Online Conference 2019 - Giovanni and Preslav presented the work on fine-grained propaganda detection. Poster available. (Oct. 2019)
Proppy at "Notte dei Ricercatori" - Notte dei ricercatori (night of researchers) is an annual event in which researchers organise meetings and demonstrations to explain their research to the general public. Alberto showcased Proppy.
Slides in Italian available. (Sep. 2019)
Propagandist messages are conveyed through a number of rethorical and psychological techniques.
We annotated news articles at the fragment level with 18 persuasion techniques and developed our own machine learning model to automatically detect them [3];
Code and Data are available. You can also try a demo of our model.
We are currently organising a shared task at SemEval 2020. After the task is over, we will keep a live leaderboard for the users to compare the performances of their systems and to keep track of the state of the art.
Proppy is a system that organizes news articles into events and, for each event, shows articles according to their level of propagandistic content. We aim at raising awareness into individual readers as well as providing tools for organizations to monitor large amounts of news articles.
Among all persuasion techniques defined in the literature, we have selected the ones that can be found in news articles and the ones that can be spotted intrinsically, i.e., just by reading the article, without resorting to external knowledge. The final list consists of 18 techniques.
Currently, we have annotated 550 articles in collaboration with A Data Pro. The annotation process is described here and in Publication 3 below. The articles publicly available at the moment can be found here.
For our experiments with Proppy, we collected 51k propagandist and non-propagandist articles, labelled using distant supervision according to the labels of the sources provided by Media Bias/Fact Check. The corpus is available for download here.
Sep. 2019 - Mar. 2020
As a further effort to develop/foster a community around the topic of propaganda detection, we are organising a shared task at SemEval 2020.
11-13 Jul. 2020
The tutorial will feature a session on propaganda detection. See you in Yokohama!
24-28 Aug. 2020
The RUSSIR summer school will include our course on online disinformation detection. Lectures on propaganda detection will be part of the course. The school will be held in Moscow.
3 Nov. 2020
The tutorial will feature a session on propaganda detection.
G. Da San Martino, S. Cresci, A. Barrón-Cedeño, S. Yu, R. Di Pietro, P. Nakov, "A Survey on Computational Propaganda Detection", to appear in Proceedings of 29th International Joint Conference on Artificial Intelligence and the 17th Pacific Rim International Conference on Artificial Intelligence (IJCAI-PRICAI2020), Yokohama, Japan, July 11-17, 2020.
Bibtex (link to the paper will be provided after its publication in the IJCAI proceedings)
G. Da San Martino, S. Shaar, Y. Zhang, S. Yu, A. Barrón-Cedeño, P. Nakov, "Prta: A System to Support the Analysis of Propaganda Techniques in the News", to appear in Proceedings of the 2020 Annual Conference of the Association for Computational Linguistics (ACL 2020), Seattle, Washington, USA, July 5-10, 2020.
Bibtex - Link to the demo
G. Da San Martino, S. Yu, A. Barrón-Cedeño, R. Petrov, P. Nakov, "Fine-Grained Analysis of Propaganda in News Articles", in Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP 2019), Hong Kong, China, November 3-7, 2019.
Bibtex - Code and Data
A. Barrón-Cedeño, I. Jaradat, G. Da San Martino, P. Nakov, “Proppy: Organizing News Coverage on the Basis of Their Propagandistic Content”, Information Processing and Management, 2019. DOI:10.1016/j.ipm.2019.03.005.
Bibtex
A. Barrón-Cedeño, G. Da San Martino, I. Jaradat, and P. Nakov, “Proppy: A System to Unmask Propaganda in Online News”, in Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence (AAAI’19), Honolulu, HI, USA, 2019.
Bibtex - Online Demo
Giovanni
Da San Martino
Scientist
QCRI, HBKU
Alberto
Barrón-Cedeño
Research Assistant
Università di Bologna
Preslav
Nakov
Principal Scientist
QCRI, HBKU
Seunghak
Yu
Joint Post-doc
QCRI - MIT CSAIL
Israa
Jaradat
PhD Student
University of Texas at Arlington