Article
Computer Science, Interdisciplinary Applications
Anastasios Lytos, Thomas Lagkas, Panagiotis Sarigiannidis, Vasileios Argyriou, George Eleftherakis
Summary: The technological advancements in AI and machine learning have led to significant progress in NLP and natural language understanding. This paper explores the modeling of argumentation in short text and proposes a novel framework for argumentation detection. The findings suggest that the modeling process provides a solid foundation for technical research and hybrid solutions have the potential to be applied to various NLP-related tasks.
SIMULATION MODELLING PRACTICE AND THEORY
(2022)
Article
Engineering, Multidisciplinary
Ozkan Canay, Umit Kocabicak
Summary: This study proposes a method for user tracking, session management, and collecting web usage data based on an innovative approach. The method uses collected data as the data source in web usage mining, and successfully gathers and stores structured data that is more convenient to browse, filter, and process than web server logs. This structured data can be used as a reliable data source for various purposes such as web usage mining, real-time web analytics, machine learning algorithms, or a functional recommendation system.
ENGINEERING SCIENCE AND TECHNOLOGY-AN INTERNATIONAL JOURNAL-JESTECH
(2023)
Article
Chemistry, Multidisciplinary
Alicia Huidobro, Raul Monroy, Barbara Cervantes
Summary: Understanding visitor navigation behavior on a website has various applications, such as personalized navigation experiences and identifying website failures. This paper presents a method that represents the navigation behavior of a class of website visitors as a small graph, aiming to simplify web analysis, particularly in marketing areas.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Artificial Intelligence
Anthony Hunter
Summary: This paper focuses on one aspect of argument strength in deductive argumentation based on defeasible logic. It investigates various ways to calculate argument strength based on the probabilistic necessity and sufficiency of the premises, as well as competing premises and claims. The study provides axioms and explores four specific probability-based measures.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2022)
Article
Computer Science, Artificial Intelligence
Johannes De Smedt, Ewelina Lacka, Spyro Nita, Hans-Helmut Kohls, Ross Paton
Summary: The way people navigate the web has changed significantly with the use of multiple devices and shared devices. Analyzing a large volume of seemingly disjoint data can support decision-making through machine learning. This study introduces an alternative approach based on learning behavioral patterns from web page visit fingerprints to identify and stitch web sessions efficiently.
DECISION SUPPORT SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Ulrike Hahn, Marko Tesic
Summary: In this paper, the authors explore the relationship between argument and explanation, providing an integrative review of relevant research from cognitive science and AI literatures. They also propose areas for future research where bridging these two perspectives would be mutually beneficial.
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Leila Amgoud, Dragan Doder, Srdjan Vesic
Summary: An argumentation framework consists of a graph and a semantics, where the graph represents arguments and their relations while the semantics evaluates the strength of each argument. This paper investigates gradual semantics for weighted graphs, proposing key principles for evaluating argument strength. It provides a formal analysis and comparison of existing semantics, introduces three new semantics, and demonstrates their efficiency in computational strength of arguments.
ARTIFICIAL INTELLIGENCE
(2022)
Article
Chemistry, Multidisciplinary
Ramon Ruiz-Dolz, Montserrat Nofre, Mariona Taule, Stella Heras, Ana Garcia-Fornes
Summary: The paper presents VivesDebate, a large, richly annotated and versatile professional debate corpus for computational argumentation research. The corpus, derived from 29 transcripts of a debate tournament in Catalan, has been machine-translated into Spanish and English. It contains annotations of argumentative propositions, relations, interactions and evaluations, making it a valuable resource for a diverse set of computational argumentation tasks.
APPLIED SCIENCES-BASEL
(2021)
Review
Psychology, Multidisciplinary
Kalypso Iordanou, Chrysi Rapanta
Summary: Research shows that intensive engagement in goal-based activities involving extended dialogic practice and reflection is effective in fostering argument skills and dispositions. The mechanisms of this development include the role of meta-level understanding regarding the purpose of argument, supporting the development of dialogic skills at the strategic level.
FRONTIERS IN PSYCHOLOGY
(2021)
Article
Management
Mikko Ketokivi, Saku Mantere
Summary: This article discusses the challenge of justifying generalized theoretical conclusions from specific empirical analysis, attributing it to an incomplete understanding of argument structure. By applying Toulmin's argument structure model, the importance of theoretical, inferential, procedural, and contextual warrants in empirical management research is highlighted. The article emphasizes the crucial role of making warrants and their backings explicit in understanding argument structure and justifying claims.
JOURNAL OF OPERATIONS MANAGEMENT
(2021)
Article
Chemistry, Multidisciplinary
Jaejong Ho, Hyoji Ha, Seok-Won Lee, Kyungwon Lee
Summary: This paper proposes a topic segmentation model, CSseg, based on conceptual recurrence and debate consistency metrics. It investigates the relationship between conceptual similarity and topic segmentation. CSseg segments transcripts using similarity cohesion methods and weights based on conceptual similarities and debate consistency metrics, providing user-driven topic segmentation. The prototype of CSseg was implemented and compared with a previous model, showing better performance in debates.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Interdisciplinary Applications
E. A. Sidorova, I. R. Akhmadeeva, I. S. Kononenko, P. M. Chagina
Summary: The article presents an indicator approach to extracting arguments in popular science literature and proposes a deep learning method based on the analysis of indicator contexts. By constructing training samples and using a classifier, the experiment on argument mining shows the best performance of the classifier based on indicators.
PATTERN RECOGNITION AND IMAGE ANALYSIS
(2023)
Article
Psychology, Multidisciplinary
Yvonne Berkle, Lukas Schmitt, Antonia Tolzin, Andreas Janson, Thiemo Wambsganss, Jan Marco Leimeister, Miriam Leuchter
Summary: Theory argumentation is crucial for academic disciplines, but students lack argumentation skills. This study developed an instrument to measure the recognition of argument structures and fallacies among preservice teachers and business economics students. The study found differences in the recognition of congruent and incongruent fallacies based on dual process theories.
FRONTIERS IN PSYCHOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Benjamin Delhomme, Franck Taillandier, Irene Abi-Zeid, Rallou Thomopoulos, Cedric Baudrit, Laurent Mora
Summary: Participatory approaches are increasingly used in policy planning, but there are currently no tools to support real-time debates and resolve conflicts effectively.
DECISION SUPPORT SYSTEMS
(2022)
Article
Multidisciplinary Sciences
Heng Zou
Summary: This paper develops a sports development system based on data mining and Web technology in order to improve conventional image technology for promoting national sports and enhancing the impact of school physical education. The paper analyzes the reconstruction principle of the matrix model, the introduction and suppression mechanism of reconstruction noise, and proposes two reconstruction algorithm ideas to eliminate reconstruction noise. A new reconstruction algorithm is suggested as a sports image processing algorithm, and the system also integrates real-world requirements for developing a sports development system based on data mining and Web technology. The system can mine data to analyze user information, provide customized recommendations, and guide users' online sports training.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Editorial Material
Multidisciplinary Sciences
Chris Reed
Editorial Material
Computer Science, Artificial Intelligence
Katie Atkinson, Jacky Visser
ARGUMENT & COMPUTATION
(2021)
Article
Linguistics
Annette Hautli-Janisz, Katarzyna Budzynska, Conor McKillop, Brian Pluss, Valentin Gold, Chris Reed
Summary: This paper explores the relationship between linguistics and pragmatics in terms of question structure and context in argumentative discourse. The study demonstrates that different types of questions directly impact the structure of arguments, and challenges previous assumptions about the consequences of non-canonical questions.
JOURNAL OF PRAGMATICS
(2022)
Article
Communication
Elena Musi, Chris Reed
Summary: This study examines the phenomenon of fake news during the pandemic through the lens of critical thinking. It addresses the lack of systematic criteria for fact-checking misinformation in the gray area. By drawing from fallacy theory, the study identifies 10 fallacious strategies that flag misinformation and provides a deterministic analysis method for recognizing them.
DISCOURSE & SOCIETY
(2022)
Article
Linguistics
Annette Hautli-Janisz, Katarzyna Budzynska, Chris Reed
Summary: In this paper, the authors discuss the conventional implicatures (cis) as an interesting phenomenon in the field of semantics, pragmatics, and argumentation. They extend an existing model for argument diagramming to incorporate this implicit meaning and show that cis differ from enthymemes, making them more suitable for argument analysis. By bringing the conventionally implicated material to the surface, the authors are able to explore the interplay between conventional implicature and argumentation, shedding new light on the relationship between meaning and argumentation.
Article
History & Philosophy Of Science
Katarzyna Budzynska, Chris Reed
Summary: This paper argues that expertise, authority, and testimony play crucial roles in communication and cognition. It recognizes various forms of persuasion, including the appeals to position to know, witness testimony, expert opinion, and authority. The paper further demonstrates that analyzing these types of arguments requires considering speech activities and communication strategies such as using others' words, attacking statements, and reasoning from others' reasoning.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Annette Hautli-Janisz, Zlata Kikteva, Wassiliki Siskou, Kamila Gorska, Ray Becker, Chris Reed
Summary: Broadcast political debate is crucial for democracy as it provides the general public with easy access to opinions that shape policies. QT30 is the largest corpus of analysed broadcast political debate, featuring 30 episodes of BBC's 'Question Time' from 2020 and 2021. The resource utilizes Inference Anchoring Theory to annotate the creation and reaction of arguments and conflicts in dialogical settings.
LREC 2022: THIRTEEN INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
(2022)
Article
Computer Science, Artificial Intelligence
Yohan Jo, Seojin Bang, Chris Reed, Eduard Hovy
Summary: While current research on argument mining lacks a comprehensive understanding of the logical mechanisms that constitute argumentative relations, this study attempts to classify argumentative relations based on four logical and theory-informed mechanisms, achieving better results than unsupervised baselines.
TRANSACTIONS OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS
(2021)
Article
Logic
Chris Reed
JOURNAL OF APPLIED LOGICS-IFCOLOG JOURNAL OF LOGICS AND THEIR APPLICATIONS
(2021)
Article
Communication
Jacky Visser, John Lawrence, Chris Reed, Jean Wagemans, Douglas Walton
Summary: Argument schemes are essential abstractions for understanding argumentative communication. Annotated corpora of argumentative discourse are limited, particularly in terms of argument scheme corpora. By extending existing annotated corpora and proposing improvements in annotation guidelines, this paper contributes to a better understanding of argumentation in communicative practice.
