Shades of #MAGA Social Network Analysis Textual Analysis Summary Data Provenance


The iconic slogan of Trump's presidential campaign has proved remarkably versatile, capable of being taken up by a diverse number of groups for a diverse number of purposes. Its lack of semantic precision has allowed "Make America Great Again" to act as a blank canvas for the projected hopes of Trump's followers: as journalist Conor Lynch notes, "to an evangelical Christian, it stands for making America devout and dogmatic again; to a blue-collar worker in the Rust Belt, it means making America a manufacturing powerhouse again" (2017). More often than not, however, the slogan appears to be bound up with conservative moral values rather than political or economic goals - the return to a time when inequities based on race, gender and other markers of difference were firmly entrenched. Numerous commentators across the American political spectrum have observed that white nationalists and white supremacists in particular have become more emboldened since Trump's election, lending "Make America Great Again" an insidious tenor.

"Shades of #MAGA" attemps to visualize how the slogan is interpreted and circulated through Trump's preferred communications habitat: Twitter. Although its usage on Twitter represents only one facet of how "Make America Great Again" is discursively constructed, Trump's own notorious presence on the social media platform attests to its relevance as a site of study. Analyzing textual and user data from tweets containing the hashtag #makeamericagreatagain - and its shortened version, #MAGA - the visualizations represent the relationship between the hashtags and the context of their use on social media.

The initial project was carried out as part of a course on Information Visualization and Visual Analytics in the Master of Archival Studies program at the University of British Columbia in November 2017. In January 2018, I created a new Twitter corpus from five non-consecutive days of data collection to address the truncation issue from the first iteration of the project (see "Data Provenance"), as well as improving the data cleaning methods to retain more information. I presented the updated findings at the University of British Columbia's iSchool Research Day, as summarized in the research poster. Although it's now been relegated to the status of hobby project on the side, "Shades of #MAGA" is still ongoing. Updates are posted on the "Summary" page.