DIPROMATS 2024: Propaganda Characterization

In this task, the systems were required to categorize a tweet into three different groups of propaganda techniques, in addition to a negative class: Group 0: Non-propaganda, Group 1: Appeal to community, Group 2: Discrediting the opponent, and Group 3: Loaded language.

Publication
Moral et al. (2024). Overview of DIPROMATS 2024: Detection, Characterization and Tracking of Propaganda in Messages from Diplomats and Authorities of World Powers. Procesamiento del Lenguaje Natural, Revista, 73: 347-358.
Competition
DIPROMATS: Automatic Detection and Characterization of Propaganda Techniques and Narratives from Diplomats of Major Powers
Language
Spanish
English
URL Task
https://sites.google.com/view/dipromats2024
NLP topic
text classification
Dataset
DIPROMATS
Year
2024
Publication link
http://journal.sepln.org/sepl…
Ranking metric
ICM

Task results

System ICM
DSHacker 0.5222
Victor Vectors 0.5066
UMUTeam 0.4759
UC3M-LCPM 0.3293

If you have published a result better than those on the list, send a message to odesia-comunicacion@lsi.uned.es indicating the result and the DOI of the article, along with a copy of it if it is not published openly.