Tweeting India’s Nirbhaya protest: a study of emotional dynamics in an online social movement

Abstract

Previous research has recognized the role of emotions in protests and social movements in the offline world. Despite the current scenario of ubiquitous social media and ‘Twitter revolutions,’ our knowledge about the connections between emotions and online protests still remains limited. In this study, we examine whether online protest actions follow the same emotional groundwork for supporting and nurturing a social movement as in the offline world, and how these emotions vary across various stages of the social movement. Through a computer-assisted emotion analysis of 65,613 Twitter posts (tweets), posted during the Nirbhaya social movement (movement against the Delhi gang-rape incident) in India, we identified a strong resemblance between online emotional patterns and offline protest emotions as discussed in literature. Formal statistical testing of a range of emotions (negativity, positivity, anger, sadness, anxiety, certainty, individualism, collectivism, and achievement) demonstrates that they significantly differed across stages of the social movement; as such, they influenced the course of the online protest, resonating parallels with offline events. The findings highlight the importance of anger and anxiety in stirring the collective conscience, and identify that positive emotion was pervasive during the protest event. Implications of these findings are discussed.     

朝鲜诗学上的"神韵"

本文论述了自诗坛先驱的北学派 (后四家 )始到十九世纪前半期 ,王士祯诗学的“神韵”诗在朝鲜和韩国的文论中是如何阐释的。首先探讨了“神韵”用语的渊源 ,以及王士祯神韵学说中“神韵”的基本含意 ;接着论述了王士祯神韵说在朝鲜诗坛的传播、受容与发展过程 ,并对在此过程中所表现出来的朝鲜诗学的“神韵”特征作了分析与梳理     

Bayesian Inference in Regime-Switching ARMA Models With Absorbing States: The Dynamics of the Ex-Ante Real Interest Rate Under Regime Shifts

One goal of this article is to develop an efficient Metropolis–Hastings (MH) algorithm for estimating an ARMA model with a regime-switching mean, by designing a new efficient proposal distribution for the regime-indicator variable. Unlike the existing algorithm, our algorithm can achieve reasonably fast convergence to the posterior distribution even when the latent regime-indicator variable is highly persistent or when there exist absorbing states. Another goal is to appropriately investigate the dynamics of the latent ex-ante real interest rate (EARR) in the presence of structural breaks, by employing the econometric tool developed. We show that excluding the theory-implied moving-average terms may understate the persistence of the observed EPRR dynamics. Our empirical results suggest that, even though we rule out the possibility of a unit root in the EARR, it may be more persistent and volatile than has been documented in some of the literature.