15 citations · 55 across the 12 of their papers we have counts for
5 papers · 1 filter
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,…
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…
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…
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…
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…