Votes on twitter: Assessing candidate preferences and topics of discussion during the 2016 US presidential election
Social media offers scholars new and innovative ways of understanding public opinion,
including citizens' prospective votes in elections and referenda. We classify social media
users' preferences over the two US presidential candidates in the 2016 election using
Twitter data and explore the topics of conversation among proClinton and proTrump
supporters. We take advantage of hashtags that signaled users' vote preferences to train our
machine learning model which employs a novel classifier—a Topic-Based Naive Bayes …
including citizens' prospective votes in elections and referenda. We classify social media
users' preferences over the two US presidential candidates in the 2016 election using
Twitter data and explore the topics of conversation among proClinton and proTrump
supporters. We take advantage of hashtags that signaled users' vote preferences to train our
machine learning model which employs a novel classifier—a Topic-Based Naive Bayes …
