Illuminating 2016

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OVERVIEW

Illuminating 2016 is a computational journalism project that will empower journalists covering the 2016 presidential campaign. Political reporters must cover not only stump speeches, campaign events, and TV ads, but also what is happening on social media. Covering it increases transparency and accountability of the campaigns, and is a way to take the pulse of the electorate. The sheer volume of information that flows through social media, however, makes it challenging to report accurately and comprehensively. Our goal is to help journalists in that important work by providing a useable yet comprehensive summary of the content and sentiment—that goes beyond counting likes or retweets. Illuminating 2016 will enable political journalists an insightful yet accessible summation of the important political conversation online.

This project is supported by the Knight Foundation, the Tow Center for Digital Journalism at Columbia University, the Center for Computational and Data Sciences and the BITS Lab at the School of Information Studies at Syracuse University

RESEARCH QUESTIONS AND METHODS

The Illuminating 2016 project has several goals. First, as a research project we seek to understand what indicators on social media can be used to determine support for presidential candidates. Journalists tend to look at the most easily observable metrics, such as followership rates. Yet, there are likely better indicators that determine electoral success. Second, as an applied project, we seek to understand what political journalists need to best report on elections, factoring in the complex social media landscape. That is, we have the opportunity to work with journalists through the primaries, conventions, and general election to provide analysis and data visualizations most useful to their reporting.

To achieve these objectives, we are collecting the Facebook and Twitter messages and images of major party presidential candidates. We are also collecting Facebook comments, and retweets and mentions on Twitter. We are building an automated system to tag the types, topics, and sentiment of candidate messages, and will do the same for the public’s conversation. Critical for this work is to interview and observe about 30 political journalists to understand their needs for reporting. Interviews will inform the design of a website we will build in the spring to provide data visualizations and automated reports.