AI News, Twitter researchers offer clues for why Trump won

Twitter researchers offer clues for why Trump won

Luo and Wang, a dual PhD candidate in political and computer science, summarized their findings in eight papers during the course of the campaign, including these observations: “In the end, even though we chose not to make any predictions, we were not surprised at all that Donald Trump won,” says Luo.

Barack Obama’s use of social media in the 2008 presidential race helped establish Twitter and other social media platforms as powerful tools for candidates to quickly reach and receive feedback from large numbers of potential voters–and to attack their opponents.

From September 2015 through October 2016, the team began accumulating a huge data set that included: Using advanced computer vision tools, the researchers trained an artificial neural network (what’s called a convolutional neural network) to determine–with 90 percent accuracy or more–the age, gender, and race of the candidates’ followers using their Twitter photos.

(Even geotagged tweets may be sent while the sender is on vacation or attending a rally in another state.) But Twitter mining also has its advantages–enabling researchers to quickly, continually, and inexpensively sample data on a scale that far surpasses the 1,000 or so responses that pollsters increasingly struggle to gather using traditional techniques.

Unlocking big data

In 2016, Timothy Dye, a professor of public health sciences, traveled with a team to Puerto Rico to help local medical personnel deal with a Zika epidemic.

“We knew Jiebo Luo was the right person for the job.” Dye and Luo are just two of the more than 40 faculty members from across the University whose research either relies on or furthers the new and fast developing field of data science.

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