Rhetorics of Radicalism

Abstract

What rhetorics run throughout radical discourse, and why do some gain prominence over others? The scholarship on radicalism largely portrays radical discourse as opposition to powerful ideas and enemies, but radicals often evince great interest in personal and local concerns. To shed light on how radicals use and adopt rhetoric, we analyze an original corpus of more than 23,000 pages produced by Afghan radical groups between 1979 and 2001 using a novel computational abductive approach. We first identify how radicalism not only attacks dominant ideas, actors, and institutions using a rhetoric of subversion, but also how it can use a rhetoric of reversion to urge intimate transformations in morals and behavior. Next, we find evidence that radicals’ networks of support affect the rhetorical mixture they espouse, due to social ties drawing radicals into encounters with backers’ social domains. Our study advances a relational understanding of radical discourse, while also showing how a combination of computational and abductive methods can help theorize and analyze discourses of contention.

Sociocultural mechanisms of conflict: Combining topic and stochastic actor-oriented models in an analysis of Afghanistan, 1979–2001

“…Instead, the encounter could be used as an opportunity to articulate objections rooted in aspects of the individuals' self-narratives that clash. As a result, a perception of interpersonal animosity could emerge (Mische and White 1998;White 2008;Karell and Freedman 2019). Mische and White (1998) call "situations"-are likely to occur, we argue, when power is asymmetrical.…”

“…In light of these challenges, we develop a novel analytical approach that synthesizes computational textual analysis, specifically structural topic models (STMs), and stochastic actor-oriented models (SAOMs) of longitudinal networks. Structural topic models, along with other unsupervised topic models of text, provide an opportunity to inductively or abductively define the semantic level with minimal input from researchers' biases and natural inconsistency in coding (Grimmer and Stewart 2013;Nelson 2017;Karell and Freedman 2019). They use the co-occurrence of words appearing in each document within a corpus to identify "topics" that are conceived as having formed the documents.…”

“…pages from magazines, pamphlets, speeches, and media reports. Karell and Freedman (2019) identified the topics using a computational abductive analysis. To do so, they first estimated an STM with a 10 topic solution over the entire corpus.…”

“…The analysis is guided by a novel explanatory argument drawing on the conflict studies, relational sociology, and the social movement literatures. Namely, we build on Mische and White's (1998) insight that interpersonal encounters can lead to narratives of a nity-in our case, comradeship between Blakh's militants-but not necessarily so (see also Karell and Freedman 2019). At times, these encounters can become "situations", during which contention emerges between individuals.…”

Research metrics, labor markets, and epistemic change: evidence from Britain 1970-2018

“…Taking the collection of all abstracts for each of the 4 social science, we determined four 40-topic solutions that neatly described most of the key themes covered by articles (and, ostensibly researchers' intellectual agendas) over time. The 40-topic solution was arrived at iteratively, by examining the heuristic coverage of models ranging from 15 to 70 topics (Karell and Freedman 2019). These four 40 topic solutions, corresponding to the different disciplines,…”