6 research outputs found
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Assessing the Relationship between Economic News Coverage and Mass Economic Attitudes
Do economic performance and economic news coverage influence public perceptions of the economy? Efforts to assess the effects are hampered by the interrelationships among the variables. In this paper, we bring to bear a more careful accounting of available economic variables than previous studies have used. We find that both media tone and economic attitudes are strongly related to actual economic performance. Moreover, after taking into account the economy itself, a substantial relationship between media tone and economic attitudes persists. Given that economic attitudes influence a wide variety of political outcomes, this finding carries important normative and political significance
Recommended from our members
Assessing the Relationship between Economic News Coverage and Mass Economic Attitudes
Do economic performance and economic news coverage influence public perceptions of the economy? Efforts to assess the effects are hampered by the interrelationships among the variables. In this paper, we bring to bear a more careful accounting of available economic variables than previous studies have used. We find that both media tone and economic attitudes are strongly related to actual economic performance. Moreover, after taking into account the economy itself, a substantial relationship between media tone and economic attitudes persists. Given that economic attitudes influence a wide variety of political outcomes, this finding carries important normative and political significance
Recommended from our members
A Negativity Bias in Reframing Shapes Political Preferences Even in Partisan Contexts
Humans evolved to attend to valence and group membership when learning about their environment. The political domain offers a unique opportunity to study the simultaneous influence of these two broad, domain-general features of human experience. We examined whether the pervasive tendency for negatively valenced frames to “stick” in the mind applies to both intergroup and intragroup political contexts. In a preregistered experiment, we tested the effects of negative-to-positive (vs. positive-to-negative) reframing on people’s candidate preferences, first in the absence of party cue information and then in two partisan contexts: an intergroup context (analogous to a U.S. general election between opposing political parties) and an intragroup context (analogous to a U.S. primary election between candidates of the same party). We observed a persistent negativity bias in reframing effects, even in the presence of party cues. The results pave the way for future research at the intersection of psychology and political science
Recommended from our members
A Negativity Bias in Reframing Shapes Political Preferences Even in Partisan Contexts
Humans evolved to attend to valence and group membership when learning about their environment. The political domain offers a unique opportunity to study the simultaneous influence of these two broad, domain-general features of human experience. We examined whether the pervasive tendency for negatively valenced frames to “stick” in the mind applies to both intergroup and intragroup political contexts. In a preregistered experiment, we tested the effects of negative-to-positive (vs. positive-to-negative) reframing on people’s candidate preferences, first in the absence of party cue information and then in two partisan contexts: an intergroup context (analogous to a U.S. general election between opposing political parties) and an intragroup context (analogous to a U.S. primary election between candidates of the same party). We observed a persistent negativity bias in reframing effects, even in the presence of party cues. The results pave the way for future research at the intersection of psychology and political science
Discovering Social Events through Online Attention
Twitter is a major social media platform in which users send and read messages ("tweets") of up to 140 characters. In recent years this communication medium has been used by those affected by crises to organize demonstrations or find relief. Because traffic on this media platform is extremely heavy, with hundreds of millions of tweets sent every day, it is difficult to differentiate between times of turmoil and times of typical discussion. In this work we present a new approach to addressing this problem. We first assess several possible "thermostats" of activity on social media for their effectiveness in finding important time periods. We compare methods commonly found in the literature with a method from economics. By combining methods from computational social science with methods from economics, we introduce an approach that can effectively locate crisis events in the mountains of data generated on Twitter. We demonstrate the strength of this method by using it to locate the social events relating to the Occupy Wall Street movement protests at the end of 2011