  Manipulative and misleading news have become a commodity for some online news
outlets and these news have gained a significant impact on the global mindset
of people. Propaganda is a frequently employed manipulation method having as
goal to influence readers by spreading ideas meant to distort or manipulate
their opinions. This paper describes our participation in the SemEval-2020,
Task 11: Detection of Propaganda Techniques in News Articles competition. Our
approach considers specializing a pre-trained BERT model on propagandistic and
hyperpartisan news articles, enabling it to create more adequate
representations for the two subtasks, namely propaganda Span Identification
(SI) and propaganda Technique Classification (TC). Our proposed system achieved
a F1-score of 46.060% in subtask SI, ranking 5th in the leaderboard from 36
teams and a micro-averaged F1 score of 54.302% for subtask TC, ranking 19th
from 32 teams.
