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1. Rhetorical strategies in German argumentative dialogs

Author

Annette Hautli-Janisz and Mennatallah El-Assady

Subjects
Electronic computers. Computer science, QA75.5-76.95, Computational linguistics. Natural language processing, P98-98.5
Abstract

An important factor of argument mining in dialog or multilog data is the framing with which interlocutors put forth their arguments. By using rhetorical devices such as hedging or reference to the Common Ground, speakers relate themselves to their interlocutors, their arguments, and the ongoing discourse. Capitalizing on theoretical linguistic insights into the semantics and pragmatics of discourse particles in German, we propose a categorization of rhetorical information that is highly relevant in natural transcribed speech. In order to shed light on the rhetorical strategies of different interlocutors in large amounts of real mediation data, we use a method from Visual Analytics which allows for an exploration of the rhetorical patterns via an interactive visual interface. With this innovative combination of theoretical linguistics, argument mining and information visualization, we offer a novel way of analyzing framing strategies in large amounts of multi-party argumentative discourse in German.

Published
2017
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29. Visualization and the Humanities: Towards a Shared Research Agenda (Dagstuhl Seminar 23381)

Author

Johanna Drucker and Mennatallah El-Assady and Uta Hinrichs and Florian Windhager and Derya Akbaba, Drucker, Johanna, El-Assady, Mennatallah, Hinrichs, Uta, Windhager, Florian, Akbaba, Derya, Johanna Drucker and Mennatallah El-Assady and Uta Hinrichs and Florian Windhager and Derya Akbaba, Drucker, Johanna, El-Assady, Mennatallah, Hinrichs, Uta, Windhager, Florian, and Akbaba, Derya

Abstract

This report documents the program and the outcomes of Dagstuhl Seminar 23381 "Visualization and the Humanities: Towards a Shared Research Agenda". The seminar was motivated by the fact that visualization has become a vital element in (digital) humanist research practices recently, while the value and impact of research at the intersection of visualization and the humanities is still widely debated and frequently contested from both sides. Visualization scholars critique the service-oriented focus on visualization as a tool to facilitate humanist research, which hampers the discovery of complementary and mutually enriching research perspectives for all fields involved. At the same time, humanists warn of visualizations' roots in the quantitative sciences which introduce non-trivial shifts in the topology of knowledge-power, creating epistemic, political, ethical, pedagogical, and cultural tensions. Building on advances in this young and highly interdisciplinary research area, the seminar discussed how to leverage synergies and how to build productively on tensions between methodologies at the intersection of visualization and (digital) humanities fields that span a vast spectrum of research philosophies and methods. The seminar thus brought together researchers and practitioners from the fields of visualization, computer science, the humanities, and design to reflect on existing research methods within visualization and the humanities, to identify tensions and synergies between the different fields, and to develop concrete avenues that address and leverage these.

Published
2024
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45. Which Biases and Reasoning Pitfalls Do Explanations Trigger? Decomposing Communication Processes in Human–AI Interaction

Author

Mennatallah El-Assady and Caterina Moruzzi

Subjects
Computer Graphics and Computer-Aided Design, Software
Abstract

Collaborative human-AI problem-solving and decision-making rely on effective communications between both agents. Such communication processes comprise explanations and interactions between a sender and a receiver. Investigating these dynamics is crucial to avoid miscommunication problems. Hence, in this paper, we propose a communication dynamics model, examining the impact of the sender's explanation intention and strategy on the receiver's perception of explanation effects. We further present potential biases and reasoning pitfalls with the aim of contributing to the design of hybrid intelligence systems. Lastly, we propose six desiderata for human-centered explainable AI and discuss future research opportunities.

Published
2022

46. MediCoSpace: Visual Decision-Support for Doctor-Patient Consultations using Medical Concept Spaces from EHRs

Author

Sanne van der Linden, Rita Sevastjanova, Mathias Funk, Mennatallah El-Assady, Visual Analytics, EAISI High Tech Systems, and Future Everyday

Subjects
electronic health records, General Computer Science, natural language processing, interaction design, Visual analytics, ddc:004, Visual Analytics, Natural Language Processing, Interaction Design, Management Information Systems
Abstract

Healthcare systems are under pressure from an aging population, rising costs, and increasingly complex conditions and treatments. Although data are determined to play a bigger role in how doctors diagnose and prescribe treatments, they struggle due to a lack of time and an abundance of structured and unstructured information. To address this challenge, we introduce MediCoSpace, a visual decision-support tool for more efficient doctor-patient consultations. The tool links patient reports to past and present diagnoses, diseases, drugs, and treatments, both for the current patient and other patients in comparable situations. MediCoSpace uses textual medical data, deep-learning supported text analysis and concept spaces to facilitate a visual discovery process. The tool is evaluated by five medical doctors. The results show that MediCoSpace facilitates a promising, yet complex way to discover unlikely relations and thus suggests a path toward the development of interactive visual tools to provide physicians with more holistic diagnoses and personalized, dynamic treatments for patients., ACM Transactions on Management Information Systems, 14 (2), ISSN:2158-656X, ISSN:2158-6578

Published
2023

50. Lotse: A Practical Framework for Guidance in Visual Analytics

Author

Fabian Sperrle, Davide Ceneda, and Mennatallah El-Assady

Subjects
FOS: Computer and information sciences, Signal Processing, Computer Science - Human-Computer Interaction, Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design, Software, Human-Computer Interaction (cs.HC)
Abstract

Co-adaptive guidance aims to enable efficient human-machine collaboration in visual analytics, as proposed by multiple theoretical frameworks. This paper bridges the gap between such conceptual frameworks and practical implementation by introducing an accessible model of guidance and an accompanying guidance library, mapping theory into practice. We contribute a model of system-provided guidance based on design templates and derived strategies. We instantiate the model in a library called Lotse that allows specifying guidance strategies in definition files and generates running code from them. Lotse is the first guidance library using such an approach. It supports the creation of reusable guidance strategies to retrofit existing applications with guidance and fosters the creation of general guidance strategy patterns. We demonstrate its effectiveness through first-use case studies with VA researchers of varying guidance design expertise and find that they are able to effectively and quickly implement guidance with Lotse. Further, we analyze our framework's cognitive dimensions to evaluate its expressiveness and outline a summary of open research questions for aligning guidance practice with its intricate theory., VIS 2022, to appear in TVCG

Published
2022

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