Quantifying Political Legitimacy from Twitter

Abstract

We present a method to quantify the political legitimacy of a populace using public Twitter data. First, we represent the notion of legitimacy with respect to k-dimensional probabilistic topics, automatically culled from the politically oriented corpus. The short tweets are then converted to a feature vector in k-dimensional topic space. Leveraging sentiment analysis, we also consider the polarity of each tweet. Finally, we aggregate a large number of tweets into a final legitimacy score (i.e., L-score) for a populace. To validate our proposal, we conduct an empirical analysis on eight sample countries using related public tweets, and find that some of our proposed methods yield L-scores strongly correlated with those reported by political scientists.

Part of the work was done while Dongwon Lee visited the Air Force Research Lab (AFRL) at Rome, NY, in 2013, as a summer faculty fellow. Authors thank John Salerno at AFRL for the thoughful feedback on the idea and draft. This research was also in part supported by NSF awards of DUE-0817376, DUE-0937891, and SBIR-1214331.