Keywords: Social media, big data, sentiment analysis, and emerging technologies

Misinformation online is a serious problem, (Fung et al., 2016a; Fung et al., 2016b; Ho, McGrath, & Mattheos, 2016). Although it is not the first time that misinformation has been spread (Boczkowski, 2016) changes in the way people gather information and how information is spread has made it much easier to spread fake information. There’s plenty of statistics which show that more people were engaged with fake news than the mainstream news during the 2016 U.S. presidential election. For example, in Facebook 8.7 million were engaged in fake news stories while 7.3 were engaged with the mainstream news during the election cycle. In the current study, we examine the spread of misinformation in Twitter in the case one of the biggest fake news of the 2016 U.S. presidential election. We examined data from Sept 1 2016 to Sept 30th 2017 on pizzagate. Data was collected using Crimson Hexagon, a commercial social media analytics library and application. For each tweet, engagement metrics, provided via Crimson Hexagon, were collected. Engagement metrics included Retweet Count, Reply Count, Total Engagement (calculated as: Retweet Count + Reply Count), and Potential Impressions (calculated as: sender's number of followers + followers of all users who have retweeted that post). 
A spike analysis shows the most prominent dates/events for this fake news story. Next, we conduct network analysis with NodeXL for the first month, when the fake information was spread. Network maps are created by drawing lines between Twitter users that represent the connections they form when they follow, reply to, or mention one another. (Smith, Rainie, Shneiderman, & Himelboim, 2014). In Twitter, there are two ways to be the center of a network, either the post has been shared/liked/replied by a lot of people, or a lot of people are tagging an account at the “same time”. Each cluster is like a discussion group. Our findings from the network analysis demonstrate the accounts which were responsible for spreading the rumor about pizzagate during the first month of the news. A few of the accounts which spread the news were deleted from Twitter, while other are still active. One of the primary accounts spread the rumor that Hillary Clinton was stepping down due to the pizzagate controversy. This same information was shared by the second prominent account by “confirming” the misinformation. The fake information from both these accounts were shared widely. Further, our findings show that the account of Donald Trump was also the center at some point as many Twitter users demanded a FBI investigation of the controversy and tagged Trump. Most of those big players who helped spread this fake story still have thousands of followers on twitter, which means they can still spread misinformation.