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20152026
most citedDeciphering the 2016 U.S. Presidential Campaign in the Twitter Sphere: A Comparison of the Trumpists and Clintonists

48 citations · 263 across the 22 of their papers we have counts for

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Showing 2016Show all

8 papers · 1 filter

cs.SI2016★ 1 cited

Tactics and Tallies: Inferring Voter Preferences in the 2016 U.S. Presidential Primaries Using Sparse Learning

Yu Wang, Yang Feng, Xiyang Zhang +1

In this paper, we propose a web-centered framework to infer voter preferences for the 2016 U.S. presidential primaries. Using Twitter data collected from Sept. 2015 to March 2016,…

cs.SI2016★ 1 cited

Gender Politics in the 2016 U.S. Presidential Election: A Computer Vision Approach

Yu Wang, Yang Feng, Xiyang Zhang +1

Gender is playing an important role in the 2016 U.S. presidential election, especially with Hillary Clinton becoming the first female presidential nominee and Donald Trump being fr…

cs.CV2016★ 11 cited

Do They All Look the Same? Deciphering Chinese, Japanese and Koreans by Fine-Grained Deep Learning

Yu Wang, Haofu Liao, Yang Feng +2

We study to what extend Chinese, Japanese and Korean faces can be classified and which facial attributes offer the most important cues. First, we propose a novel way of obtaining l…

cs.SI2016★ 1 cited

Will Sanders Supporters Jump Ship for Trump? Fine-grained Analysis of Twitter Followers

Yu Wang, Yang Feng, Xiyang Zhang +2

In this paper, we study the likelihood of Bernie Sanders supporters voting for Donald Trump instead of Hillary Clinton. Building from a unique time-series dataset of the three cand…

cs.SI2016★ 4 cited

Voting with Feet: Who are Leaving Hillary Clinton and Donald Trump?

Yu Wang, Yuncheng Li, Quanzeng You +3

From a crowded field with 17 candidates, Hillary Clinton and Donald Trump have emerged as the two front-runners in the 2016 U.S. presidential campaign. The two candidates each boas…

cs.SI2016★ 16 cited

To Follow or Not to Follow: Analyzing the Growth Patterns of the Trumpists on Twitter

Yu Wang, Jiebo Luo, Richard Niemi +1

In this paper, we analyze the growth patterns of Donald Trump's followers (Trumpists, henceforth) on Twitter. We first construct a random walk model with a time trend to study the…