Framing and Agenda-setting in Russian News:a Computational Analysis of Intricate Political Strategies
Таблица 6: F1 Scores for identification of all frames in a document.
['[EMPTY]', '[BOLD] Ours', '[BOLD] Baseline']
To the best of our knowledge, identifying all frames in a document is a new task that was not attempted in prior work. Thus, we use a logistic regression model with bag-of-word features as a standard baseline. As above, we evaluate using 10-fold cross validation on the ‘‘Immigration’’ subset of the MFC. We note that the poorest performing frames, ‘‘External Regulation and Reputation’’ and ‘‘Morality’’ are the frames which are least common in this subset of the data – each frame occurs in fewer than 500 articles. When we run the same 10-fold cross validation evaluation on the ‘‘Samesex’’ subsection of the MFC, where the ‘‘Morality’’ frame occurs in over 1000 articles, we achieve a higher F1 score (0.65).