Facebook Ad Engagement in the Russian Active Measures Campaign of 2016
This research provides insights into the characteristics of engaging disinformation ads, which is important for social media platforms and policymakers combating foreign interference in elections. It is an incremental contribution to understanding the IRA's tactics.
This paper analyzed 3,517 Facebook ads from Russia's Internet Research Agency (IRA) to understand the relationship between ad engagement (clicks) and 41 ad features. It found that ad expenditure, text size, ad lifetime, and sentiment were top predictors of engagement, with positive sentiment ads being more engaging. Linear SVM and Logistic Regression classifiers achieved 93.6% F-scores in predicting engagement.
This paper examines 3,517 Facebook ads created by Russia's Internet Research Agency (IRA) between June 2015 and August 2017 in its active measures disinformation campaign targeting the 2016 U.S. general election. We aimed to unearth the relationship between ad engagement (as measured by ad clicks) and 41 features related to ads' metadata, sociolinguistic structures, and sentiment. Our analysis was three-fold: (i) understand the relationship between engagement and features via correlation analysis; (ii) find the most relevant feature subsets to predict engagement via feature selection; and (iii) find the semantic topics that best characterize the dataset via topic modeling. We found that ad expenditure, text size, ad lifetime, and sentiment were the top features predicting users' engagement to the ads. Additionally, positive sentiment ads were more engaging than negative ads, and sociolinguistic features (e.g., use of religion-relevant words) were identified as highly important in the makeup of an engaging ad. Linear SVM and Logistic Regression classifiers achieved the highest mean F-scores (93.6% for both models), determining that the optimal feature subset contains 12 and 6 features, respectively. Finally, we corroborate the findings of related works that the IRA specifically targeted Americans on divisive ad topics (e.g., LGBT rights, African American reparations).