Librarians Facilitate Computational Analysis of Social Media Data

With all of the attention paid to the impact of social media on the 2016 presidential election, it’s no surprise that research on it has emerged across a wide variety of fields. However, as accessible as that data may seem, acquiring it requires technical skills beyond most researchers.

It was that research dilemma that led to the creation of Social Feed Manager (SFM), open source software developed by GW Libraries and Academic Innovation to harvest social media data and web resources from Twitter, Tumblr, Flickr, and Sina Weibo, a Chinese micro-blogging site. SFM allows users to specify what to collect, manage the collection process, and then export the data. Behind the scenes, SFM handles the complexity of interacting with the social media platform, scheduling harvests, and storing the results.

Funded by grants from the Institute of Museum and Library Services, the Council on East Asian Libraries, and the National Archives’ National Historical Publications and Records Commission, SFM is used by GW faculty and students to generate social media data sets ranging from an investigation of gender bias among political reporters to an analysis of the Iranian presidential election using a data set in both Farsi and English. One of the largest data sets collected with SFM documents the 2016 U.S. presidential election and comprises 280 million tweets.

Although the grant work is recently completed, the support for social media research is ongoing. To learn more, please visit