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character Traits and States, Mental Health and Electrophysiological Markers of Self-referential Affective Processing – Novel Approaches from Psychological Research for character computing and Brain-Computer Interaction

Character Traits and States, Mental Health and Electrophysio...

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International Workshops on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2024

作者： Herbert, Cornelia Applied Emotion and Motivation Psychology Ulm University Albert-Einstein-Allee 47 Ulm89081 Germany

ISBN: (纸本)9783031730573

character computing aims to predict human experience and behavior based on cognitive, affective, and motivational states and traits related to a person’s self, personality, mental health, and well-being. Previous character computing studies have focused on the analysis of self-report data or behavioral trait and state markers. The present study extends previous character computing studies in terms of methods and paradigms by investigating the modulation of event-related brain potentials (ERPs) during self-referential affective processing. Specifically, the study determines whether modulation of event-related brain potentials (ERPs) could differentiate between affective traits and mental states of well-being during processing conditions during which no overt responses or behavior of the participants are provided. A novel, well-controlled experimental paradigm (the so-called affective HisMine paradigm) was chosen. Data from N = 64 healthy subjects were analyzed. The results suggest that ERP modulation during self-referential affective processing could be included in future character computing studies and during brain-computer interaction to promote mental health and well-being of healthy users. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： brain-computer interaction character computing event-related brain potentials HisMine paradigm self-referential affective processing

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CCOnto: The character computing Ontology 15th

CCOnto: The Character Computing Ontology

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15th International Conference on Research Challenges in Information Science (RCIS)

作者： El Bolock, Alia Elaraby, Nada Herbert, Cornelia Abdennadher, Slim German Univ Cairo Cairo Egypt Univ Ulm Ulm Germany

ISBN: (纸本)9783030750176;9783030750183

Especially in light of the COVID-19 pandemic which is influencing human behavior, it is clear that there is a rising need for joining psychology and computer science to provide technology interventions for people suffering from negative feelings and behavior change. Behavior is driven by an individual's character and the situation they are in, according to character computing and the character-Behavior-Situation (CBS) triad. Accordingly, we developed the first full ontology modeling the CBS triad with the aim of providing domain experts with an intelligent interface for modeling, testing, and unifying hypotheses on the interactions between character, behavior, and situation. The ontology consists of a core module modeling character-based interactions and use-case and domain-specific modules. It was developed by computer scientists and psychology domain experts following an iterative process. The main contributions of this paper include updating the earlier prototypical version of the ontology-based on feedback from psychology experts and existing literature, adding more tools to it for enabling domain expert interaction, and providing the final ontology. Steps taken towards evaluating and validating the ontology are outlined.

关键词： character computing Behavior Personality Psychology Human-based computing

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CCOnto: Towards an Ontology-Based Model for character computing 14th

CCOnto: Towards an Ontology-Based Model for Character Comput...

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14th International Conference on Research Challenges in Information Science (RCIS)

作者： El Bolock, Alia Herbert, Cornelia Abdennadher, Slim German Univ Cairo Cairo Egypt Univ Ulm Ulm Germany

ISBN: (纸本)9783030503154;9783030503161

Our lives are rewritten by technology and data, making it crucial for machines to understand humans and their behavior and react accordingly. Technology systems could adapt to different factors such as affect (Affective computing), personality (Personality computing), or character (character computing). character consists of personality, affect, socio-cultural embedding, cognitive abilities, health, and all other attributes distinguishing one individual from another. Ontology-based conceptual models representing individuals i.e. their character and resulting behavior in situations is needed for providing a unified framework for building truly interactive and adaptive systems. We propose CCOnto, an ontology for character computing that models human character. The ontology is to be used for adaptive interactive systems to understand and predict an individual's behavior in a given situation, more specifically their performance in different tasks. The developed ontology models the different character attributes, their building blocks, and interactions with each other and with a person's performance in different tasks.

关键词： character computing Ontology Personality Affect

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character computing: Computer Science meets Psychology 18

Character Computing: Computer Science meets Psychology

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17th International Conference on Mobile and Ubiquitous Multimedia (MUM)

作者： El Bolock, Alia Herbert, Cornelia Salah, Jailan Abdennadher, Slim Abdelrahman, Yomna German Univ Cairo Fac Media Engn & Technol Comp Sci Al Makinah Egypt Ulm Univ Inst Psychol & Educ Appl Emot & Motivat Psychol Ulm Germany Stuttgart Univ Inst Visualisat & Interact Syst Stuttgart Germany Bundeswehr Univ Munich Germany

ISBN: (纸本)9781450365949

Now that most daily endeavors have migrated to computers and the Internet, having systems that adapt to users is a rising trend. By detecting and adapting to the user's traits and character instead of only the current states, there is great potential for novel user experiences. character computing which was introduced in [3] is now extended to the field of experimental psychology and psychological theorizing. Our approach integrates psychological and computational aspects of advanced sensing and processing technologies to detect the building blocks of a user's character traits and states which will allow computer systems to adapt to the user's behavior and his/her feelings more reliably and mimic them according to situational demands. Accordingly, in this workshop the different aspects of character computing are to be discussed from an interdisciplinary perspective taking computational and psychological accounts into consideration in order to strengthen already investigated and potential applications as well as the theoretical foundation and challenges of character computing.

关键词： character computing Ubiquitous computing Interactive Systems Adaptive Systems Affective computing Personality Psychology

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Non-obtrusive Sleep Detection for character computing Profiling 1st

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1st International Conference on Intelligent Human Systems Integration (IHSI) - Integrating People and Intelligent Systems

作者： ElBolock, Alia Amr, Rowan Abdennadher, Slim German Univ Cairo Comp Sci Cairo Egypt

ISBN: (纸本)9783319738888;9783319738871

The majority of existing Adaptive Systems rely on the user's current state (affect) without taking the user's general state (character) into consideration. In order to achieve truly seamless adaptive interactive systems, understanding the user's character (i.e. character Profile) is required. This paper presents a non-obtrusive sleep detector, My Sleep, which is part of a multimodal lifelogging platform called My Life. MyLife is designed for the main purpose of enabling building character Profiles for users, which is a main artefact required in character computing. The aim of My Sleep is to provide sleep records to be used in character profiling without requiring the user to use any external hardware and with minimal interaction. A study was conducted to test the accuracy of My Sleep and compare it to other wearable sleep detectors. For the required purposes, the results provided by My Sleep are accurate enough with requiring minimal interaction with the user.

关键词： character computing Lifelogging Human computer interaction Adaptive Systems Personality computing

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character computing: Challenges and Opportunities 17

Character Computing: Challenges and Opportunities

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16th International Conference on Mobile and Ubiquitous Multimedia (MUM)

作者： El Bolock, Alia Salah, Jailan Abdennadher, Slim Abdelrahman, Yomna German Univ Cairo Cairo Egypt Univ Stuttgart Stuttgart Germany

ISBN: (纸本)9781450353786

Systems that adapt to the states of users show great potential for creating novel user experiences. However, most approaches in affective computing only rely on the current state of the user. Furthermore, personality computing has recently evolved, it shows a few examples of how personality traits can be inferred from different types of behavioral evidence. We envision introducing novel user experiences by learning more about the user through extracting the building blocks of their character including;morals, mentalities and believes. In this workshop we aim to introduce character computing, a novel approach to examine and leverage characters to build ubiquitous and non-obtrusive character-aware adaptive systems. This workshop aims at engaging participants in reflection and practical work exploring the evolving research strand in hand.

关键词： character computing Affective computing Personality computing

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Predicting User Code-Switching Level from Sociological and Psychological Profiles

Predicting User Code-Switching Level from Sociological and P...

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25th International Conference on Asian Language Processing (IALP)

作者： Hamed, Injy El Bolock, Alia Rizk, Nader Herbert, Cornelia Abdennadher, Slim Ngoc Thang Vu Univ Stuttgart Inst Nat Language Proc Stuttgart Germany Ulm Univ Appl Emot & Motivat Psychol Ulm Germany German Int Univ Informat & Comp Sci Cairo Egypt German Univ Cairo Comp Sci Dept Cairo Egypt

ISBN: (纸本)9781665483117

Multilingual speakers tend to alternate between languages within a conversation, a phenomenon referred to as "code-switching" (CS). CS is a complex phenomenon that not only encompasses linguistic challenges, but also contains a great deal of complexity in terms of its dynamic behaviour across speakers. This dynamic behaviour has been studied by sociologists and psychologists, identifying factors affecting CS. In this paper, we provide an empirical user study on Arabic-English CS, where we show the correlation between users' CS frequency and character traits. We use machine learning (ML) to validate the findings, informing and confirming existing theories. The predictive models were able to predict users' CS frequency with an accuracy higher than 55%, where travel experiences and personality traits played the biggest role in the modeling process.

关键词： Code-switching Code-mixing character computing Personality Arabic-English Code-switching

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How do you feel during the COVID-19 pandemic? A survey using psychological and linguistic self-report measures, and machine learning to investigate mental health, subjective experience, personality, and behaviour during the COVID-19 pandemic among university students

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BMC PSYCHOLOGY 2021年第1期9卷 1页

作者： Herbert, Cornelia El Bolock, Alia Abdennadher, Slim Univ Ulm Fac Engn Comp Sci & Psychol Inst Psychol & Educ Appl Emot & Motivat Psychol Albert Einstein Allee 47 D-89081 Ulm Germany German Univ Cairo GUC Fac Media Engn & Technol Comp Sci Dept New Cairo Egypt

Background The WHO has raised concerns about the psychological consequences of the current COVID-19 pandemic, negatively affecting health across societies, cultures and age-groups. Methods This online survey study investigated mental health, subjective experience, and behaviour (health, learning/teaching) among university students studying in Egypt or Germany shortly after the first pandemic lockdown in May 2020. Psychological assessment included stable personality traits, self-concept and state-like psychological variables related to (a) mental health (depression, anxiety), (b) pandemic threat perception (feelings during the pandemic, perceived difficulties in describing, identifying, expressing emotions), (c) health (e.g., worries about health, bodily symptoms) and behaviour including perceived difficulties in learning. Assessment methods comprised self-report questions, standardized psychological scales, psychological questionnaires, and linguistic self-report measures. Data analysis comprised descriptive analysis of mental health, linguistic analysis of self-concept, personality and feelings, as well as correlational analysis and machine learning. N = 220 (107 women, 112 men, 1 = other) studying in Egypt or Germany provided answers to all psychological questionnaires and survey items. Results Mean state and trait anxiety scores were significantly above the cut off scores that distinguish between high versus low anxious subjects. Depressive symptoms were reported by 51.82% of the student sample, the mean score was significantly above the screening cut off score for risk of depression. Worries about health (mental and physical health) and perceived difficulties in identifying feelings, and difficulties in learning behaviour relative to before the pandemic were also significant. No negative self-concept was found in the linguistic descriptions of the participants, whereas linguistic descriptions of feelings during the pandemic revealed a negativity bias in emotion

关键词： COVID-19 Corona virus Pandemic Personality Mental health Depression Anxiety Emotion perception Self-concept Linguistic analysis Machine learning character computing

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Applying the character-Based Chatbots Generation Framework in Education and Healthcare 21

Applying the Character-Based Chatbots Generation Framework i...

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9th International Conference on User Modeling, Adaptation and Personalization Human-Agent Interaction (HAI)

作者： El Hefny, Walid El Bolock, Alia Herbert, Cornelia Abdennadher, Slim German Univ Cairo Cairo Egypt Ulm Univ Ulm Germany

ISBN: (纸本)9781450386203

Users have different expectations while interacting with chatbots. However, current chatbots do not consider the users' preferences and needs, creating unpleasant biases towards certain user groups. User characteristics play a vital role in predicting preferences and thus eliciting better responses as advocated by character computing. A framework was proposed in the literature to build characterbased chatbots with adjustable traits. In this paper, we customize the framework modules to build two chatbots for different domains using the same set of chatbot characters. First, we present a character-based chatbot for academic support. It provides students with information regarding the content, dates, timings, locations, and deadlines of their courses. Second, we present a character-based chatbot for COVID-19. It provides users with answers to frequently asked questions, advice and precautions, cases per country, and symptoms checking. Users can select their preferable chatbot character to interact with, and receive personalized responses accordingly. Moreover, we investigated the prediction of a user's favorite chatbot character based on their personality traits to create adaptable chatbots in the future. Finally, we investigated the effect of a chatbot's character on its likability and trustworthiness.

关键词： conversational agents chatbots character computing education healthcare COVID-19

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Chase Away the Virus: A character-Based Chatbot for COVID-19 9

Chase Away the Virus: A Character-Based Chatbot for COVID-19

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IEEE 9th International Conference on Serious Games and Applications for Health (SeGAH)

作者： El Hefny, Walid El Bolock, Alia Herbert, Cornelia Abdennadher, Slim German Univ Cairo Dept Comp Sci Cairo Egypt Ulm Univ Dept Appl Emot & Motivat Psychol Ulm Germany

ISBN: (纸本)9781665426497

Chatbots are becoming an attractive tool for people who seek medical advice due to their constant availability. Multiple healthcare chatbots were developed for different purposes such as delivering advice, booking appointments, and accessing medical records. Additionally, it was found that personalized healthcare chatbots affected the user experience positively, due to the addition of human empathy. Therefore, we propose building a character-based chatbot named "Chasey" for COVID-19, to combat the risk of misinformation amplification during the pandemic. Chasey provides users with various COVID-19 information such as tracking the cases per country, giving advice, answering frequently asked questions, and performing symptoms checking. According to the selected chatbot character, users will receive personalized responses to their inquiries from verified sources. Moreover, we investigate how our chatbot implementation overcomes some of the challenges and limitations of healthcare and COVID-19 chatbots. Finally, an experiment was conducted to evaluate the chatbot's usability, as well as, the likability and trustworthiness of the chatbot characters. Overall, the participants were satisfied with the chatbot features and character change option. Moreover, significant results were found between the likability of the chatbot characters.

关键词： conversational agents chatbots character computing healthcare covid-19 coronavirus

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