Detection of Propaganda Using Logistic Regression
LI Jin-fen, Zhihao Ye, Lu Xiao · 2019
Various propaganda techniques are used to manipulate peoples perspectives in order to foster a predetermined agenda such as by the use of logical fallacies or appealing to the emotions of the audience.In this paper, we develop a Logistic Regression-based tool that automatically classifies whether a sentence is propagandistic or not.We utilize features like TF-IDF, BERT vector, sentence length, readability grade level, emotion feature, LIWC feature and emphatic content feature to help us differentiate these two categories.The linguistic and semantic features combination results in 66.16% of F1 score, which outperforms the baseline hugely.