Women Were 56% More Likely to Read About Trump Than Clinton Online In Weeks Leading Up To Election
In the three weeks leading up to the election, women were 56% more likely to see content about Donald Trump than Hillary Clinton, indicating higher awareness of Trump when they were online. Wealthier and poorer women had higher exposure to Trump online relative to middle-income women. African-American women had the lowest exposure to Trump content, seeing 10 fewer articles or ads on average about Trump than any other racial group.
Women on average read about Trump or were exposed to content or ads about him 32 times over the three weeks before the election compared to 21 times of online exposure to Clinton.
The rate of exposure and consumption of content online was pulled from tracking users’ desktop and mobile browsing data and Facebook data, including exposure to ads on the Facebook newsfeed. While the webpages we tracked can mention both Clinton and Trump — as most news stories would — there is a greater number of web pages, i.e. content, that only referenced Trump.
In other words, users often read singularly about Trump in an online story without contrasting him to Clinton.
When looking at exposure by demographics, the wealthiest and poorest women in our sample had the highest exposure to Trump. Women with incomes over $115K and under $35K were more likely to read about Trump.
African American women had the lowest exposure to Trump online, viewing 10 fewer articles or ads on average about Trump than their White, Latino and Asian counterparts.
The contrast in greater coverage and exposure to Trump online is underscored by the lack of statistical difference when looking at references to the political parties. There was no statistical difference between content consumption or exposure to Democrats versus Republicans in articles i.e. most articles equally referenced both parties.
OpenUp incentivizes users to share their browsing data via the OpenUp browser extension and scrapes web pages, meta tags and urls with help of the IBM Watson API to surface relevant topics. Over 5MM pages of desktop and mobile browsing data was used for this analysis. Users also share demographic data including age, race, gender and income. The sample in this study included 521 American women. Our sample is younger and wealthier than the U.S. Census, with 60% between the ages of 18–34 and 12% with incomes over $115K per year. Users were tracked from October 17th through November 8th 2016.
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Analysis contributed by Bryan Sim — follow him @fluxandcadence
Writing contributed by Ashwini Anburajan — follow me @anburajan