What is Populism? What is Right-Wing Populism? Much progress has been made in conceptualising populism in recent years. There is now a general consensus
How do leaders communicate during domestic crises? We provide the first global analysis of world leader communication on social media during social unrest. We develop a theory of leaders’ digital communication strategies, building on the diversionary theory of foreign policy, as well as research on the role of democratic institutions in explaining elite responsiveness. To test our theory, we construct a new dataset that characterizes leader communication through social media posts published by any head of state or government on Twitter or Facebook, employing a combination of automated translation and supervised machine learning methods. Our findings show that leaders increase their social media activity and shift the topic from domestic to foreign policy issues during moments of social unrest, which is consistent with a conscious strategy to divert public attention when their position could be at risk. These effects are larger in democracies and in particular in the run-up to elections, which we attribute to incentives created by democratic institutions. Our results demonstrate how social media provide meaningful comparative insight into leaders’ political behavior in the digital age.
Crisis escalation to war is a subject of longstanding interest. Case studies, formal models and statistical analysis offer compelling explanations for why some crises escalate to war while others do not. Much less can be said in answer to the following question: where do crises come from in the first place? In this paper, we first introduce the concept of a near crisis following the approach taken over the course of more than four decades by the International Crisis Behavior (ICB) Project. A near crisis is just below a crisis as defined by ICB with regard to intensity, as it lacks one essential condition for a crisis—higher likelihood of military hostilities. Second, we present a newly developed dataset that contains information on 86 cases in which actors perceived a threat to one or more basic values, along with an awareness of finite time for response to the value threat. We also present simple statistical models comparing (a) near crisis to crisis and (b) crisis to war that show that analyses based on the Near Crisis dataset will contribute to advancement of knowledge.
Quantitative methodology in crisis studies is a topic of substantial scope. The principal rallying point for such research is the long-standing International Crisis Behavior (ICB) Project, which from 1975 onward has produced a comprehensive and heavily accessed data set for the study of conflict processes. A prehistory of crisis studies based on statistical methods, which identified connections between and among various conflict-related events, pointed increasingly toward the need for a program of research on escalation. The potential of quantitative methodology to contribute seriously to crisis studies has been realized along multiple dimensions by the ICB Project in particular. For example, quantitative methods have been applied productively to study the effects of both global and regional organizations, along with individual states, upon the process of crisis escalation. Current research in crisis studies is based on the premise that research designs so far have covered only one of multiple relevant stages regarding the process of escalation. This is where the concept of a “near crisis” becomes relevant: a near crisis entails perception of threat and finite time, but not an increased likelihood of military hostilities. Data analysis pertaining to multiple stages of escalation is at an early stage of development, but initial results are intriguing. A further critique of quantitative research begins with the observation that it is mostly state-centered and reductionist in nature. A key question emerges: How can the concept of crisis and associated data collection be revised to include a humanistic element that would entail new and potentially more enlightening configurations of independent and dependent variables?
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