The Impact of Malicious Accounts on Political Tweet Sentiment

Twitter has been the go-to platform for political discourse, with politicians and news outlets releasing information via tweets. Since social media has become a staple of political campaigns, the spread of misinformation has greatly increased due to social bots. This study seeks to determine the effect social bots on Twitter had on public opinion of candidates during the 2016 U.S. election. To this end, we collected a tweet dataset consisting of 705,381 unique user accounts during the 2016 U.S. election cycle. Sentiment in the dataset is labeled using a convolutional neural network trained on the sentiment140 dataset. Bot accounts are identified and removed from the dataset and accounts are limited to a single tweet. Tweet volume and sentiment are examined both before and after the removal of bots to determine the effects social bots have on public opinion. When considering the Twitter platform demographic, our results show social bots significantly skew perception of candidates when using volume and sentiment as metrics.