Argumentation theory | Communication and Mass Media | Research Starters | EBSCO Research

Persuasion Index: A Theory-Guided Framework for Persuasion Analysis

Identifying persuasive rhetorical cues is critical across domains, from detecting information manipulation and improving AI safety to advancing public health communication. We propose Persuasion...

Most arguments scatter across papers, posts, and threads — and evaporate. A claim tree gives them a stable structure to gather against, the way a cathedral gathers centuries of work into a single, standing thing.

Hegel’s Dialectics

“Dialectics” is a term used to describe a method ofphilosophical argument that involves some sort of contradictoryprocess between opposing sides. In what is perhaps the most classicversion of “dialectics”, the ancient Greek philosopher,Plato (see entry on Plato), for instance, presented his philosophical argument as aback-and-forth dialogue or debate, generally between the character ofSocrates, on one side, and some person or group of people to whomSocrates was talking (his interlocutors), on the other. In the courseof the dialogues, Socrates’ interlocutors propose definitions ofphilosophical concepts or express views that Socrates challenges oropposes. The back-and-forth debate between opposing sides produces akind of linear progression or evolution in philosophical views orpositions: as the dialogues go along, Socrates’ interlocutorschange or refine their views in response to Socrates’ challengesand come to adopt more sophisticated views. The back-and-forthdialectic between Socrates and his interlocutors thus becomesPlato’s way of arguing against the earlier, less sophisticatedviews or positions and for the more sophisticated ones later.

ViewSift

The web's evidence-based discussion platform. Built on ATProto!

ViewSift

The web's evidence-based discussion platform. Built on ATProto!

fenc.es — be wrong on the internet, productively

Trace the map of reasonable disagreement. Break arguments into statements, rate confidence and importance, and find the crux.

Reflexive discourse analysis: A methodology for the practice of reflexivity

How to implement reflexivity in practice? Can the knowledge we produce be emancipatory when our discourses recursively originate in the world we aim to challenge? Critical International Relations (IR) scholars have successfully put reflexivity on the agenda based on the theoretical premise that discourse and knowledge play a socio-political role. However, academics often find themselves at a loss when it comes to implementing reflexivity due to the lack of adapted methodological and pedagogical material. This article shifts reflexivity from meta-reflections on the situatedness of research into a distinctive practice of research and writing that can be learned and taught alongside other research practices. To do so, I develop a methodology based on discourse: reflexive discourse analysis (RDA). Based on the discourse analysis of our own discourse and self-resocialisation, RDA aims to reflexively assess and transform our socio-discursive engagement with the world, so as to render it consistent with our intentional socio-political objectives. RDA builds upon a theoretical framework integrating discourse theory to Bourdieu’s conceptual apparatus for reflexivity and practices illustrated in the works of Comte and La Boétie. To illustrate this methodology, I used this very article as a recursive performance. I show how RDA enabled me to identify implicit discriminative mechanisms within my discourse and transform them into an alternative based on love, to produce an article more in line with my socio-political objectives. Overall, this article turns reflexivity into a critical methodology for social change and demonstrates how to integrate criticality methodologically into research and writing.

Debate Maps — The Society Library

While The Society Library is dedicated to enabling access to information through our libraries, we recognize the difficult and tricky work of organizing that content into formal deliberation. There are hundreds of cognitive biases and logical pitfalls that can get in our way as human beings. Therefore, as a part of our service, The Society Library endeavors to map the knowledge we collect into “debate maps,” which essentially means we are organizing the arguments, claims, evidence, and opinions from all points of view into a formal debate - and effectively enabling “societal-scale debate.” A feat which may be otherwise impossible to organize in comparable levels of comprehensiveness with the existing limits of media, language, and human bandwidth to which we are confined.

Rational Silence and False Polarization: How Viewpoint Organizations and Recommender Systems Distort the Expression of Public Opinion

Social media platforms are one of the most important domains in which artificial intelligence (AI) has already transformed the nature of economic and social interaction. AI enables the massive scale and highly personalized nature of online information sharing that we now take for granted. Extensive attention has been devoted to the polarization that social media platforms appear to facilitate. However, a key implication of the transformation we are experiencing due to these AI-powered platforms has received much less attention: how platforms impact what observers of online discourse come to believe about community views. These observers include policymakers and legislators, who look to social media to gauge the prospects for policy and legislative change, as well as developers of AI models trained on large-scale internet data, whose outputs may similarly reflect a distorted view of public opinion. In this paper, we present a nested game-theoretic model to show how observed online opinion is produced by the interaction of the decisions made by users about whether and with what rhetorical intensity to share their opinions on a platform, the efforts of viewpoint organizations (such as traditional media and advocacy organizations) that seek to encourage or discourage opinion-sharing online, and the operation of AI-powered recommender systems controlled by social media platforms. We show that signals from ideological viewpoint organizations encourage an increase in rhetorical intensity, leading to the rational silence of moderate users. This, in turn, creates a polarized impression of where average opinions lie. We also show that this observed polarization can also be amplified by recommender systems that, pursuant to a platform’s incentive to maximize engagement, encourage the formation of viewpoint communities online that end up seeing a skewed sample of opinion. Unlike existing models, these well-known online phenomena are not here attributed to distortion in the formation of opinions nor to the seeking out of like-minded others, but rather to the interaction of the incentives of users, viewpoint organizations, and platforms implementing recommender systems. In addition to showing how these interactions can play out in simulations, we also identify practical strategies platforms can implement, such as reducing exposure to signals from ideological viewpoint organizations and a tailored approach to content moderation.

Relevant answers to polar questions

People often provide answers that go beyond what a question literally asks, but it has been difficult to pin down what makes some answers more relevant than others. Here, we introduce Pragmatic Reasoning In Overinformative Responses to Polar Questions (PRIOR-PQ), a probabilistic cognitive model formalizing how people use theory of mind (ToM) to produce and interpret relevantly overinformative answers to yes–no questions. Specifically, PRIOR-PQ grounds the pragmatics of question answering in inferences about the underlying goal that motivated the questioner to ask the given question as opposed to a different question. We evaluate our probabilistic model against human answering behaviour elicited in three case studies of increasing complexity, demonstrating its ability to predict nuanced patterns of relevance better than existing models, including state-of-the-art large language models. We also show how the goal-sensitive reasoning instantiated in our probabilistic model motivates a novel chain-of-thought prompting method allowing language models to approach more human-like performance. This work illuminates the mechanistic role of ToM in the pragmatics of question–answer exchanges, bridging formal semantics, cognitive science and artificial intelligence. Our findings have implications for developing more socially grounded dialogue systems and highlight the importance of integrating explanatory cognitive models with machine learning approaches. This article is part of the theme issue ‘At the heart of human communication: new views on the complex relationship between pragmatics and Theory of Mind’.

The social media discourse of engaged partisans is toxic even when politics are irrelevant

Abstract Prevailing theories of partisan incivility on social media suggest that it derives from disagreement about political issues or from status competition between groups. This study—which analyzes the commenting behavior of Reddit users across diverse cultural contexts (subreddits)—tests the alternative hypothesis that such incivility derives in large part from a selection effect: Toxic people are especially likely to opt into discourse in partisan contexts. First, we examined commenting behavior across over 9,000 unique cultural contexts (subreddits) and confirmed that discourse is indeed more toxic in partisan (e.g. r/progressive, r/conservatives) than in nonpartisan contexts (e.g. r/movies, r/programming). Next, we analyzed hundreds of millions of comments from over 6.3 million users and found robust evidence that: (i) the discourse of people whose behavior is especially toxic in partisan contexts is also especially toxic in nonpartisan contexts (i.e. people are not politics-only toxicity specialists); and (ii) when considering only nonpartisan contexts, the discourse of people who also comment in partisan contexts is more toxic than the discourse of people who do not. These effects were not driven by socialization processes whereby people overgeneralized toxic behavioral norms they had learned in partisan contexts. In contrast to speculation about the need for partisans to engage beyond their echo chambers, toxicity in nonpartisan contexts was higher among people who also comment in both left-wing and right-wing contexts (bilaterally engaged users) than among people who also comment in only left-wing or right-wing contexts (unilaterally engaged users). The discussion considers implications for democratic functioning and theories of polarization.

Maite Taboada

Maite Taboada. Professor. Department of Linguistics, Simon Fraser University. Research: discourse analysis, computational linguistics

ECHO CHAMBERS AND EPISTEMIC BUBBLES

Discussion of the phenomena of post-truth and fake news often implicates the closed epistemic networks of social media. The recent conversation has, however, blurred two distinct social epistemic phenomena. An epistemic bubble is a social epistemic structure in which other relevant voices have been left out, perhaps accidentally. An echo chamber is a social epistemic structure from which other relevant voices have been actively excluded and discredited. Members of epistemic bubbles lack exposure to relevant information and arguments. Members of echo chambers, on the other hand, have been brought to systematically distrust all outside sources. In epistemic bubbles, other voices are not heard; in echo chambers, other voices are actively undermined. It is crucial to keep these phenomena distinct. First, echo chambers can explain the post-truth phenomena in a way that epistemic bubbles cannot. Second, each type of structure requires a distinct intervention. Mere exposure to evidence can shatter an epistemic bubble, but may actually reinforce an echo chamber. Finally, echo chambers are much harder to escape. Once in their grip, an agent may act with epistemic virtue, but social context will pervert those actions. Escape from an echo chamber may require a radical rebooting of one's belief system.

Generative AI for Pro-Democracy Platforms · From Novel Chemicals to Opera

Online discourse faces challenges in facilitating substantive and productive political conversations. Recent technologies have explored the potential of generative AI to promote civil discourse, encourage the development of mutual understanding in a discussion, produce . . .

We argue badly, and nothing accumulates. How could we do better? | Reason Commons — Issue Trees & Logical Thinking Process

Millions of people argue every day about the things that matter most — climate change, what to do about AI, how we might build a better world. Some of it is sharp, even insightful. And almost none of it accumulates.