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CS698 / ENGL795 | Rhetoric, Argument and Machines Winter 2017

CS698 / ENGL795 Rhetoric, Argument and Machines

Course Coordinator: Chrysanne Di Marco
Meeting Time: Mondays 12:00-2:30 (starting January 9)
Location: DC1316

The first hour of the CS698 / ENGL795 meetings will be held with the Gamification for Mental Health Working Group. Persuasive health technologies will be a key theme of the course but participants are welcome to choose widely for their course project. This first hour will focus on various topics in persuasive health technologies, including health rhetoric, narrative-for-health, and gamification.

Readings will be available online, DC Library reserve, or from the course coordinator.

Course Overview

The course will survey current theories of Rhetoric and Argumentation that are being applied to analyze and generate persuasive language in various forms of online communication. The course will also investigate how such theories are presently being used in computational algorithms for artificial intelligence systems.

Selected topics will include:

Rhetoric and Argumentation are intrinsic to human intelligence and reasoning, not only in formal situations like understanding chains of reasoning in scientific articles or legal texts, but in everyday life, where we constantly express our own, and evaluate others', sentiments and opinions, interpret media, judge politicians, and so forth, in order to understand situations and make appropriate decisions.

Studies of Computational Rhetoric and Argumentation—and how these subjects may be applied in persuasive language technologies—are bringing together researchers and practitioners from many disciplines, including Philosophy, Logic, Linguistics, Argumentation Theory, Computational Linguistics, Computer Science, Cognitive Science, Artificial Intelligence, and Machine Learning.

In this course we aim to develop a multidisciplinary approach through the interaction of participants from both the Humanities and the Computational Sciences. While the end goal for all course projects will be an artifact illustrating some aspect of a persuasive language technology, the artifact itself may be as varied as a model, a design, a prototype, or an actual implementation.

Course Requirements

Nature of the readings

Topics will include: rhetorical theory; formal models of argumentation; informal logic; computational argumentation; models of health communication; computational models of narrative; persuasion in social media; digital rhetoric; rhetoric of technology; persuasive games.

What is expected of participants

Participants will be expected to read widely and in-depth. There are no formal requirements other than interest in the topics and ability to read and analyze technical material, to present oral summaries, and to take part in group discussions.

Note: It is understood that course participants will be given the opportunity to focus their writings, presentations, and project on material suited to their academic background.

Method of Evaluation

Theoretical (35%)

Practicum (65%)

Session 1: Organizational Meeting/Prologue

Monday January 9, 12:00-2:30, DC1316


Background reading (interest only—no specific assigned readings)

Jay Heinrichs, Thank you for arguing: What Aristotle, Lincoln, and Homer Simpson can teach us about the art of persuasion, Three Rivers Press, revised edition, 2013

All participants in the course will receive a copy of Thank you for arguing

Sessions 2 and 3: Rhetorical Models of Argumentation

Monday January 16, 12:00-2:30, DC1316
Monday January 23, 12:00-2:30, DC1316

Judy Z. Segal, Health and the rhetoric of medicine, Southern Illinois University Press, 2008


Introduction: The What, Why, and How of a Rhetoric of Medicine
Chapter 1: A Kairology of Biomedicine
Chapter 5: A Rhetoric of Death and Dying
(for interest only) Chapter 7: The Problem of Patience "Non-Compliance": Paternalism, Expertise, and the Ethos of the Physician

Jeanne Fahnestock, Rhetorical style: The uses of language in persuasion, Oxford University Press, 2011


Chapter 6: Figures of Word Choice
Chapter 13: Speaker and Audience Construction
Chapter 14: Incorporating Other Voices

Sessions 4 and 5: Classical and Computational Models of Rhetoric and Argumentation

Monday January 30, 12:00-2:30, DC1316
Monday February 6, 12:00-2:30, DC1316

Jerome Groopman, How doctors think, Mariner Books, 2008


Chapter: Flesh-and-Blood Decision-Making
Chapter: Marketing, Money, and Medical Decisions

Christopher W. Tindale, Acts of arguing: A rhetorical model of argument, State University of New York Press, 1999


Introduction: The Case for Rhetorical Argumentation
Chapter 5: Case Studies in Rhetorical Argumentation (5.1)

Stephen E. Toulmin, The uses of argument, Cambridge University Press, second edition, 2003


Chapter III The Layout of Arguments

Jeanne Fahnestock, Rhetorical figures in science, Oxford University Press, 1999


Chapter 2 Antithesis
Chapter 5 Ploche and Polyptoton

Douglas Walton and Christopher Reed, Argumentation schemes, Cambridge University Press, 2008


Chapter 1: Basic Tools in the State of the Art
Chapter 8: The History of Schemes (review only)
Chapter 9: A User's Compendium of Schemes (reference only)
Chapter 12: Schemes in Computer Systems

Sessions 6 / 7: Rhetoric & Argumentation Theory Meet Artificial Intelligence

Monday February 13, 12:00-2:30, DC1316
Monday February 27, 12:00-2:30, DC1316


Session 6 Monday February 13

Guest Speaker

Randy Harris, "Cognitive and Computational Rhetoric "

"Computing Figures/Figuring Computers II: A Workshop on Computational Rhetoric"

In August 2016, the Department of English and Literature and the Cheriton School of Computer Science presented the second Workshop on the intersection of computers and rhetorical figures.

The Workshop brought together scholars from a variety of fields in the Humanities and Computational Sciences. A major outcome of the Workshop will be a Special Issue of the journal Argument and Computation on Rhetorical Figures in Computational Argument Studies.

Ruan, Sebastian; DiMarco, Chrysanne; and Harris, Randy, "Rhetorical figure annotation with XML", Computational Models of Natural Argumentation (CMNA)16, A Workshop at the 2016 International Joint Conference on Artificial Intelligence (IJCAI), New York, July 2016.

"Argumentation Machines"

Chris Reed and Timothy J. Norman (eds.), Argumentation machines, Springer, 2004

A landmark Workshop in 2004 brought together researchers in Argumentation Theory and Artificial Intelligence to explore interdisciplinary collaborations in Computational Rhetoric and Argumentation—the Workshop laid the foundation for the field of Computational Argumentation

Session 7 Monday February 27

Topic: Creating Corpora for Argumentation Mining

Discussion leaders: Brittany, Onie

Nancy L. Green, "Argumentation for scientific claims in a biomedical research article", Workshop on Frontiers and Connections between Argumentation Theory and Natural Language Processing (ArgNLP 2014), Forli-Cesena, Italy, July 21-25, 2014


Topic: Computational Methods for Analyzing Trust in NLP and AI

Discussion leaders: Salman, Ahmad

Srijan Kumar, Robert West, and Jure Leskovec, "Disinformation on the Web: Impact, characteristics, and detection of Wikipedia hoaxes", WWW 2016, April 11–15, 2016, Montréal
Discussion leader (primary): Salman


Iyad Rahwan and Kate Larson, "Logical mechanism design", The Knowledge Engineering Review, Vol. 26:1, 61-69, 2011
Discussion leader (primary): Ahmad


Optional: Background only

S. Parsons, K. Atkinson, Z. Li, P. McBurney, E. Sklar, M. Singh, K. Haigh, K. Levitt, J. Rowe, "Argument schemes for reasoning about trust", Argument & Computation, 2014, 5(2-3), 160-190


***NEW*** Session 8: Project Proposal Workshop

Monday March 6, 12:00-2:30, DC1316

12:00-1:30 Discussion of Project Proposals

1:00-2:00 Remaining Course Readings: Selections, Discussion Leaders

2:00 Finishing up: Rahwan and Larson paper

Discussion leader: Ahmad

Session 9: Argumentation and Narrative-as-Persuasion

Monday March 13, 12:00-2:30, DC1316

Topic: Narrative-as-argumentation

Discussion leaders: Diana, Hari

Floris Bex and Trevor Bench-Capon, "Understanding narratives with argumentation", Computational models of argument, S.Parsons et al. (eds.), IOS Press, 2014


Appraisal Framework: Appraisal and Journalistic Discourse


Topic: Narrative-as-persuasion

Discussion leaders: George, Stephanie

Lewis Mehl-Madrona, Healing the mind through the power of story: The promise of narrative psychiatry, Bear & Company, 2010.


Introduction (read)
Chapter 2: Good Stories and Mental Health (skim)

Copies are available from course coordinator

Topic: Neuroscience of narrative

Discussion leader: Chrysanne

(skim only) Raymond A. Mar, "The neuropsychology of narrative: Story comprehension, story production and their interrelation", Neuropsychologia, 42, 1414-1434, 2004


From the Abstract and Introduction

"Stories are used extensively for human communication; both the comprehension and production of oral and written narratives constitute a fundamental part of our experience. ...Story comprehension appears to entail a network of frontal, temporal and cingulate areas that support working-memory and theory-of-mind processes. ...Storytelling is thus not only a native element of our social interactions, from a health standpoint there is evidence to suggest it may also be a necessary one."

Optional: For interest only

Michael White, Maps of narrative practice, W.W. Norton & Company, 2007

Lewis Mehl-Madrona and Barbara Mainguy, Remapping your mind: The neuroscience of self-transformation through story, Bear & Company, 2015


"Applying the latest neuroscience research on memory, brain mapping, and brain plasticity to the field of narrative therapy, Lewis Mehl-Madrona and Barbara Mainguy explain how the brain is specialized in the art of story-making and story-telling. They detail mind-mapping and narrative therapy techniques that use story to change behavior patterns in ourselves, our relationships, and our communities. They explore studies that reveal how memory works through story, how the brain recalls things in narrative rather than lists, and how our stories modify our physiology and facilitate health or disease."

Copies of both texts are available from course coordinator

Sessions 10 and 11: Rhetoric and the Digital Humanities

Monday March 20, 12:00-2:30, DC1316
Monday March 27, 12:00-2:30, DC1316

SELECTIONS TBA: Jim Ridolfo and William Hart-Davidson, Rhetoric and the digital humanities, University of Chicago Press, 2015

SELECTIONS TBA: Douglas Eyman, Digital rhetoric: Theory, method, practice, Digital Humanities Series, U of M Digital Culture Books, 2015

FINAL Session 12: Rhetoric of Technology

Monday April 3, 12:00-2:30, DC1316

SELECTIONS TBA: Readings from Stanford University course PWR 1SB: "Machine Dreams, The rhetoric of technology":

From the course website:

"The course focuses on arguments we make about technology, the arguments various technologies produce about us, and, finally, the ways in which rhetoric itself might be productively viewed as a technology for producing arguments."

Readings from Ian Bogost, Persuasive games: The expressive power of videogames, The MIT Press, 2010

Guest Speaker

Douglas Guilbeault, "Growing bot security: An ecological view of bot agency", International Journal of Communication 10, 5003-5012, 2016

D. Guilbeault and S. Woolley, "How Twitter bots are shaping the election", The Atlantic, Nov 2, 2016

"Between the first two presidential debates, a third of pro-Trump tweets and nearly a fifth of pro-Clinton tweets came from automated accounts"

Epilogue: "W(h)ither Human Argumentation??"

Nicholas Carr, "Is Google making us stupid?, The Atlantic, 2008 available at:

Nicholas Carr, The shallows: What the Internet is doing to our brains, W.W. Norton & Co., 2011

Artur S. d'Avila Garcez, Dov M. Gabbay, Luis C. Lamb, "A neural cognitive model of argumentation with application to legal inference and decision making", Journal of Applied Logic, 2014, 12(2), pp109-127

From the Abstract:

"Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. ... [Our] approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data)."