  The fifty-eighth American presidential election in 2016 still arouse fierce
controversyat present. A portion of politicians as well as medium and voters
believe that theRussian government interfered with the election of 2016 by
controlling malicioussocial media accounts on twitter, such as trolls and bots
accounts. Both of them willbroadcast fake news, derail the conversations about
election, and mislead people.Therefore, this paper will focus on analysing some
of the twitter dataset about theelection of 2016 by using NLP methods and
looking for some interesting patterns ofwhether the Russian government
interfered with the election or not. We apply topicmodel on the given twitter
dataset to extract some interesting topics and analysethe meaning, then we
implement supervised topic model to retrieve the relationshipbetween topics to
category which is left troll or right troll, and analyse the
pattern.Additionally, we will do sentiment analysis to analyse the attitude of
the tweet. Afterextracting typical tweets from interesting topic, sentiment
analysis offers the ability toknow whether the tweet supports this topic or
not. Based on comprehensive analysisand evaluation, we find interesting
patterns of the dataset as well as some meaningfultopics.
