Computational Argumentation for the Automatic Analysis of Argumentative Discourse and Human Persuasion

Tesis por compendio[ES] La argumentación computacional es el área de investigación que estudia y analiza el uso de distintas técnicas y algoritmos que aproximan el razonamiento argumentativo humano desde un punto de vista computacional. En esta tesis doctoral se estudia el uso de distintas técnicas propuestas bajo el marco de la argumentación computacional para realizar un análisis automático del discurso argumentativo, y para desarrollar técnicas de persuasión computacional basadas en argumentos. Con estos objetivos, en primer lugar se presenta una completa revisión del estado del arte y se propone una clasificación de los trabajos existentes en el área de la argumentación computacional. Esta revisión nos permite contextualizar y entender la investigación previa de forma más clara desde la perspectiva humana del razonamiento argumentativo, así como identificar las principales limitaciones y futuras tendencias de la investigación realizada en argumentación computacional. En segundo lugar, con el objetivo de solucionar algunas de estas limitaciones, se ha creado y descrito un nuevo conjunto de datos que permite abordar nuevos retos y investigar problemas previamente inabordables (e.g., evaluación automática de debates orales). Conjuntamente con estos datos, se propone un nuevo sistema para la extracción automática de argumentos y se realiza el análisis comparativo de distintas técnicas para esta misma tarea. Además, se propone un nuevo algoritmo para la evaluación automática de debates argumentativos y se prueba con debates humanos reales. Finalmente, en tercer lugar se presentan una serie de estudios y propuestas para mejorar la capacidad persuasiva de sistemas de argumentación computacionales en la interacción con usuarios humanos. De esta forma, en esta tesis se presentan avances en cada una de las partes principales del proceso de argumentación computacional (i.e., extracción automática de argumentos, representación del conocimiento y razonamiento basados en argumentos, e interacción humano-computador basada en argumentos), así como se proponen algunos de los cimientos esenciales para el análisis automático completo de discursos argumentativos en lenguaje natural.[CA] L'argumentació computacional és l'àrea de recerca que estudia i analitza l'ús de distintes tècniques i algoritmes que aproximen el raonament argumentatiu humà des d'un punt de vista computacional. En aquesta tesi doctoral s'estudia l'ús de distintes tècniques proposades sota el marc de l'argumentació computacional per a realitzar una anàlisi automàtic del discurs argumentatiu, i per a desenvolupar tècniques de persuasió computacional basades en arguments. Amb aquestos objectius, en primer lloc es presenta una completa revisió de l'estat de l'art i es proposa una classificació dels treballs existents en l'àrea de l'argumentació computacional. Aquesta revisió permet contextualitzar i entendre la investigació previa de forma més clara des de la perspectiva humana del raonament argumentatiu, així com identificar les principals limitacions i futures tendències de la investigació realitzada en argumentació computacional. En segon lloc, amb l'objectiu de sol$\cdot$lucionar algunes d'aquestes limitacions, hem creat i descrit un nou conjunt de dades que ens permet abordar nous reptes i investigar problemes prèviament inabordables (e.g., avaluació automàtica de debats orals). Conjuntament amb aquestes dades, es proposa un nou sistema per a l'extracció d'arguments i es realitza l'anàlisi comparativa de distintes tècniques per a aquesta mateixa tasca. A més a més, es proposa un nou algoritme per a l'avaluació automàtica de debats argumentatius i es prova amb debats humans reals. Finalment, en tercer lloc es presenten una sèrie d'estudis i propostes per a millorar la capacitat persuasiva de sistemes d'argumentació computacionals en la interacció amb usuaris humans. D'aquesta forma, en aquesta tesi es presenten avanços en cada una de les parts principals del procés d'argumentació computacional (i.e., l'extracció automàtica d'arguments, la representació del coneixement i raonament basats en arguments, i la interacció humà-computador basada en arguments), així com es proposen alguns dels fonaments essencials per a l'anàlisi automàtica completa de discursos argumentatius en llenguatge natural.[EN] Computational argumentation is the area of research that studies and analyses the use of different techniques and algorithms that approximate human argumentative reasoning from a computational viewpoint. In this doctoral thesis we study the use of different techniques proposed under the framework of computational argumentation to perform an automatic analysis of argumentative discourse, and to develop argument-based computational persuasion techniques. With these objectives in mind, we first present a complete review of the state of the art and propose a classification of existing works in the area of computational argumentation. This review allows us to contextualise and understand the previous research more clearly from the human perspective of argumentative reasoning, and to identify the main limitations and future trends of the research done in computational argumentation. Secondly, to overcome some of these limitations, we create and describe a new corpus that allows us to address new challenges and investigate on previously unexplored problems (e.g., automatic evaluation of spoken debates). In conjunction with this data, a new system for argument mining is proposed and a comparative analysis of different techniques for this same task is carried out. In addition, we propose a new algorithm for the automatic evaluation of argumentative debates and we evaluate it with real human debates. Thirdly, a series of studies and proposals are presented to improve the persuasiveness of computational argumentation systems in the interaction with human users. In this way, this thesis presents advances in each of the main parts of the computational argumentation process (i.e., argument mining, argument-based knowledge representation and reasoning, and argument-based human-computer interaction), and proposes some of the essential foundations for the complete automatic analysis of natural language argumentative discourses.This thesis has been partially supported by the Generalitat Valenciana project PROME- TEO/2018/002 and by the Spanish Government projects TIN2017-89156-R and PID2020- 113416RB-I00.Ruiz Dolz, R. (2023). Computational Argumentation for the Automatic Analysis of Argumentative Discourse and Human Persuasion [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/194806Compendi

Rethinking network governance: new forms of analysis and the implications for IGR/MLG

Our position is that network governance can be understood as a communicative arena. Networks, then, are not defined by frequency of interactions between actors but by sharing of and contest between different clusters of ideas, theories and normative orientations (discourses) in relation to the specific context within which actors operate. A discourse comprises an ensemble of ideas, concepts and causal theories that give meaning to and reproduce ways of understanding the world (Chouliaraki and Fairclough 1999). Consequently, network governance can be understood as the inherently political process through which discourses are produced, reproduced and transformed. Democratic network governance thus becomes the study of the way in which the core challenges of democratic practice are addressed – how is legitimacy awarded, by what mechanisms are decisions reached, and how is accountability enabled. Three approaches to the discursive analysis of democracy in network governance are considered - argumentation analysis, inter-subjectivity, and critical discourse analysis – and their implications for the study of intergovernmental relations and multi-level governance (IGR/MLG) are discussed. Case examples are provided. We conclude that the value for the study of MLG/IGR is to complement existing forms of analysis by opening up the communicative and ideational aspects of interactions between levels of government and other actors

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: NL

Proceedings ICPW'07: 2nd International Conference on the Pragmatic Web, 22-23 Oct. 2007, Tilburg: N

Reasoning in criminal intelligence analysis through an argumentation theory-based framework

This thesis provides an in-depth analysis of criminal intelligence analysts’ analytical reasoning process and offers an argumentation theory-based framework as a means to support that reasoning process in software applications. Researchers have extensively researched specific areas of criminal intelligence analysts’ sensemaking and reasoning processes over the decades. However, the research is fractured across different research studies and those research studies often have high-level descriptions of how criminal intelligence analysts formulate their rationale (argument). This thesis addresses this gap by offering low level descriptions on how the reasoning-formulation process takes place. It is presented as a single framework, with supporting templates, to inform the software implementation process. Knowledge from nine experienced criminal intelligence analysts from West Midlands Police and Belgium’s Local and Federal Police forces were elicited through a semi-structured interview for study 1 and the Critical Decision Method (CDM), as part of the Cognitive Task Analysis (CTA) approach, was used for study 2 and study 3. The data analysis for study 1 made use of the Qualitative Conventional Content Analysis approach. The data analysis for study 2 made use of a mixed method approach, consisting out of Qualitative Directed Content Analysis and the Emerging Theme Approach. The data analysis for study 3 made use of the Qualitative Directed Content Analysis approach. The results from the three studies along with the concepts from the existing literature informed the construction of the argumentation theory-based framework. The evaluation study for the framework’s components made use of Paper Prototype Testing as a participatory design method over an electronic medium. The low-fidelity prototype was constructed by turning the frameworks’ components into software widgets that resembled widgets on a software application’s toolbar. Eight experienced criminal intelligence analysts from West Midlands Police and Belgium’s Local and Federal Police forces took part in the evaluation study. Participants had to construct their rationale using the available components as part of a simulated robbery crime scenario, which used real anonymised crime data from West Midlands Police force. The evaluation study made use of a Likert scale questionnaire to capture the participant’s views on how the frameworks’ components aided participants with; understanding what was going on in the analysis, lines-of-enquiry and; the changes in their level of confidence pertaining to their rationale. A non-parametric, one sample z-test was used for reporting the statistical results. The significance is at 5% (α=0.05) against a median of 3 for the z-test, where μ =3 represents neutral. The participants reported a positive experience with the framework’s components and results show that the framework’s components aided them with formulating their rationale and understanding how confident they were during different phases of constructing their rationale

Reflective Argumentation

Theories of argumentation usually focus on arguments as means of persuasion, finding consensus, or justifying knowledge claims. However, the construction and visualization of arguments can also be used to clarify one's own thinking and to stimulate change of this thinking if gaps, unjustified assumptions, contradictions, or open questions can be identified. This is what I call "reflective argumentation." The objective of this paper is, first, to clarify the conditions of reflective argumentation and, second, to discuss the possibilities of argument visualization methods in supporting reflection and cognitive change. After a discussion of the cognitive problems we are facing in conflicts--obviously the area where cognitive change is hardest--the second part will, based on this, determine a set of requirements argument visualization tools should fulfill if their main purpose is stimulating reflection and cognitive change. In the third part, I will evaluate available argument visualization methods with regard to these requirements and talk about their limitations. The fourth part, then, introduces a new method of argument visualization which I call Logical Argument Mapping (LAM). LAM has specifically been designed to support reflective argumentation. Since it uses primarily deductively valid argument schemes, this design decision has to be justified with regard to goals of reflective argumentation. The fifth part, finally, provides an example of how Logical Argument Mapping could be used as a method of reflective argumentation in a political controversy

A study of different representation conventions during investigatory sensemaking

Background: During the process of conducting investigations, users structure information externally to help them make sense of what they know, and what they need to know. Software-based visual representations may be a natural place for doing this, but there are a number of types of information structuring that might be supported and hence designed for. Further, there might be important differences in how well different representational conventions support sensemaking. There are questions about what type of representational support might allow these users to be more effective when interacting with information. Aim: To explore the impact that different types of external representational structuring have on performance and user experience during intelligence type investigations. Intelligence analysis represents a difficult example domain were sensemaking is needed. We have a particular interest in the role that timeline representations might play given evidence that people are naturally predisposed to make sense of complex social scenarios by constructing narratives. From this we attempt to quantify possible benefits of timeline representation during investigatory sensemaking, compared with argumentation representation. Method: Participants performed a small investigation using the IEEE 2011 VAST challenge dataset in which they structured information either as a timeline, an argumentation or as they wished (freeform). 30 participants took part in the study. The study used three levels of a between participants independent variable of representation type. The dependent variables were performance (in terms of recall, precision efficiency and understanding) and user experience (in terms of cognitive load, engagement and confidence in understanding). Result: The result shows that the freeform condition experienced a lower cognitive load than the other two: timeline and argument respectively. A post hoc exploratory analysis was conducted to better understand the information behaviour and structuring activities across conditions and to better understand the types of structuring that participants perform in the freeform condition. The analysis resulted in an Embedded Representational Structuring Theory (ERST) that helps to characterise and describe representations primarily in terms of their elements and their relations. Conclusion: The results suggest that: (a) people experienced lower cognitive load when they are free to structure information as they wish, (b) during their investigations, they create complex heterogeneous representations consisting of various entities and multiple relation types and (c) their structuring activities can be described by a finite set of structuring conventions

The Role of Argumentation in Hypothetico-Deductive Reasoning During Problem-Based Learning in Medical Education: A Conceptual Framework

One of the important goals of problem-based learning (PBL) in medical education is to enhance medical students’ clinical reasoning—hypothetico-deductive reasoning (HDR) in particular—through small group discussions. However, few studies have focused on explicit strategies for promoting students’ HDR during group discussions in PBL. This paper proposes a novel conceptual framework that integrates Toulmin’s argumentation model (1958) into Barrows’s HDR process (1994). This framework explains the structure of argumentation (a claim, data, and a warrant) contextualized in each phase of HDR during PBL. This paper suggests four instructional strategies—understanding argument structures, questioning, elaborating on structural knowledge, and assessing argumentation—for promoting medical students’ argumentation in relation to HDR processes. Further implications of the proposed framework for other disciplines, such as science, legal, and engineering education, are also discussed

Using learning design as a framework for supporting the design and reuse of OER

The paper will argue that adopting a learning design methodology may provide a vehicle for enabling better design and reuse of Open Educational Resources (OERs). It will describe a learning design methodology, which is being developed and implemented at the Open University in the UK. The aim is to develop a 'pick and mix' learning design toolbox of different resources and tools to help designers/teachers make informed decisions about creating new or adapting existing learning activities. The methodology is applicable for designers/teachers designing in a traditional context – such as creation of materials as part of a formal curriculum, but also has value for those wanting to create OERs or adapt and repurpose existing OERs. With the increasing range of OERs now available through initiatives as part of the Open Courseware movement, we believe that methodologies, such as the one we describe in this paper, which can help guide reuse and adaptation will become increasingly important and arguably are an important aspect of ensuring longer term sustainability and uptake of OERs. Our approach adopts an empirically based approach to understanding and representing the design process. This includes a range of evaluation studies (capturing of case studies, interviews with designers/teachers, in-depth course evaluation and focus groups/workshops), which are helping to develop our understanding of how designers/teachers go about creating new learning activities. Alongside this we are collating an extensive set of tools and resources to support the design process, as well as developing a new Learning Design tool that helps teachers articulate and represent their design ideas. The paper will describe how we have adapted a mind mapping and argumentation tool, Compendium, for this purpose and how it is being used to help designers and teachers create and share learning activities. It will consider how initial evaluation of the use of the tool for learning design has been positive; users report that the tool is easy to use and helps them organise and articulate their learning designs. Importantly the tool also enables them to share and discuss their thinking about the design process. However it is also clear that visualising the design process is only one aspect of design, which is complex and multi-faceted