@inproceedings{LinCzarnuchMalhotraetal., author = {Lin, Luyuan and Czarnuch, Stephen and Malhotra, Aarti and Yu, Lifei and Schr{\"o}der, Tobias and Hoey, Jesse}, title = {Affectively Aligned Cognitive Assistance Using Bayesian Affect Control Theory}, series = {Ambient Assisted Living and Daily Activities}, booktitle = {Ambient Assisted Living and Daily Activities}, publisher = {Springer}, address = {Cham}, isbn = {978-3-319-13105-4}, issn = {1611-3349}, doi = {10.1007/978-3-319-13105-4_41}, pages = {279 -- 287}, abstract = {This paper describes a novel emotionally intelligent cognitive assistant to engage and help older adults with Alzheimer's disease (AD) to complete activities of daily living (ADL) more independently. Our new system combines two research streams. First, the development of cognitive assistants with artificially intelligent controllers using partially observable Markov decision processes (POMDPs). Second, a model of the dynamics of emotion and identity called Affect Control Theory that arises from the sociological literature on culturally shared sentiments. We present background material on both of these research streams, and then demonstrate a prototype assistive technology that combines the two. We discuss the affective reasoning, the probabilistic and decision-theoretic reasoning, the computer-vision based activity monitoring, the embodied prompting, and we show results in proof-of-concept tests.}, subject = {Dichte }, language = {en} } @inproceedings{MalhotraYuSchroederetal., author = {Malhotra, Aarti and Yu, Lifei and Schr{\"o}der, Tobias and Hoey, Jesse}, title = {An exploratory study into the use of an emotionally aware cognitive assistant}, series = {AAAI Workshop : Artificial Intelligence Applied to Assistive Technologies and Smart Environments}, booktitle = {AAAI Workshop : Artificial Intelligence Applied to Assistive Technologies and Smart Environments}, publisher = {Association for the Advancement of Artificial Intelligence}, address = {Palo Alto}, pages = {6}, abstract = {This paper presents an exploratory study conducted to understand how audio-visual prompts are understood by people on an emotional level as a first step towards the more challenging task of designing emotionally aligned prompts for persons with cognitive disabilities such as Alzheimer's disease and related dementias (ADRD). Persons with ADRD often need assistance from a caregiver to complete daily living activities such as washing hands, making food, or getting dressed. Artificially intelligent systems have been developed that can assist in such situations. This paper presents a set of prompt videos of a virtual human 'Rachel', wherein she expressively communicates prompts at each step of a simple hand washing task, with various human-like emotions and behaviors. A user study was conducted for 30 such videos with respect to three basic and important dimensions of emotional experience: evaluation, potency, and activity. The results show that, while people generally agree on the evaluation (valence: good/bad) of a prompt, consensus about power and activity is not as socially homogeneous. Our long term aim is to enhance such systems by delivering automated prompts that are emotionally aligned with individuals in order to help with prompt adherence and with long-term adoption.}, subject = {Audiovisuelles Material}, language = {en} } @article{AmbrasatvonScheveSchauenburgetal., author = {Ambrasat, Jens and von Scheve, Christian and Schauenburg, Gesche and Conrad, Markus and Schr{\"o}der, Tobias}, title = {Unpacking the Habitus}, series = {Sociological Forum}, volume = {31}, journal = {Sociological Forum}, number = {4}, publisher = {Wiley}, address = {Hoboken}, issn = {1573-7861}, doi = {10.1111/socf.12293}, pages = {994 -- 1017}, abstract = {The concept of habitus refers to socially stratified patterns of perception, classification, and thinking that are supposed to bring about specific lifestyles. Until now, research on the links between stratification and lifestyles has accounted for the habitus mainly in conceptual and theoretical terms, and studies directly measuring habitus and its association with stratification and lifestyles are rare. The present study conceptualizes the habitus as an individual-level pattern of meaning making and suggests an operationalization that is commonly used in identity research. Using survey data of 3,438 respondents, the study investigates associations between different lifestyles and patterns of meaning making. Results show, first, that self-related meanings vary systematically across lifestyle categories and mirror respondents' stratification position. Second, the meanings of various social concepts also vary significantly across lifestyle categories and partly reflect descriptive lifestyle characteristics. In sum, the study presents a plausible operationalization of (parts of) the habitus and advances our understanding of its mediating position between stratification and lifestyles.}, subject = {Habitus}, language = {en} } @article{HoeySchroederMorganetal., author = {Hoey, Jesse and Schr{\"o}der, Tobias and Morgan, Jonathan Howard and Rogers, Kimberly B. and Rishi, Deepak and Nagappan, Meiyappan}, title = {Artificial Intelligence and Social Simulation}, series = {Small Group Research}, volume = {49}, journal = {Small Group Research}, number = {6}, publisher = {Sage Publications}, address = {London}, issn = {1552-8278}, doi = {10.1177/1046496418802362}, pages = {647 -- 683}, abstract = {Recent advances in artificial intelligence and computer science can be used by social scientists in their study of groups and teams. Here, we explain how developments in machine learning and simulations with artificially intelligent agents can help group and team scholars to overcome two major problems they face when studying group dynamics. First, because empirical research on groups relies on manual coding, it is hard to study groups in large numbers (the scaling problem). Second, conventional statistical methods in behavioral science often fail to capture the nonlinear interaction dynamics occurring in small groups (the dynamics problem). Machine learning helps to address the scaling problem, as massive computing power can be harnessed to multiply manual codings of group interactions. Computer simulations with artificially intelligent agents help to address the dynamics problem by implementing social psychological theory in data-generating algorithms that allow for sophisticated statements and tests of theory. We describe an ongoing research project aimed at computational analysis of virtual software development teams.}, subject = {K{\"u}nstliche Intelligenz}, language = {en} } @article{KajićSchroederStewartetal., author = {Kajić, Ivana and Schr{\"o}der, Tobias and Stewart, Terrence C. and Thagard, Paul}, title = {The semantic pointer theory of emotion}, series = {Cognitive Systems Research}, volume = {58}, journal = {Cognitive Systems Research}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1389-0417}, doi = {10.1016/j.cogsys.2019.04.007}, pages = {35 -- 53}, abstract = {Emotion theory needs to explain the relationship of language and emotions, and the embodiment of emotions, by specifying the computational mechanisms underlying emotion generation in the brain. We used Chris Eliasmith's Semantic Pointer Architecture to develop POEM, a computational model that explains numerous important phenomena concerning emotions, including how some stimuli generate immediate emotional reactions, how some emotional reactions depend on cognitive evaluations, how bodily states influence the generation of emotions, how some emotions depend on interactions between physiological inputs and cognitive appraisals, and how some emotional reactions concern syntactically complex representations. We contrast our theory with current alternatives, and discuss some possible applications to individual and social emotions.}, subject = {Gef{\"u}hlstheorie}, language = {en} } @article{WolfSchroeder, author = {Wolf, Ingo and Schr{\"o}der, Tobias}, title = {Connotative meanings of sustainable mobility}, series = {Transportation Research Part A: Policy and Practice}, volume = {126}, journal = {Transportation Research Part A: Policy and Practice}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1879-2375}, doi = {10.1016/j.tra.2019.06.002}, pages = {259 -- 280}, abstract = {Changing people's travel behaviours and mode choices is an important mitigation option to reduce greenhouse gas emission in transport. Previous studies have shown that symbolic meanings associated with new low-emission vehicles and travel services influence people's willingness to adopt these innovations. However, little is known about the symbolic meanings of many upcoming transport innovations, which often influence habitual decision-making and their stratification within the population. This study thus examines cultural affective meanings of a broad range of conventional and novel transport mode options in a nationally representative German sample. Cluster analysis of affective meanings of travel modes identified six unique traveller segments. These consumer groups differ significantly in their intention to adopt low-emission travel modes and are characterized by specific psychographic, socio-demographic and behavioural profiles. The results demonstrate that affective meanings of choice options are predictive regarding the attitudes and (intended) behaviour of traveller segments. Moreover, the invariant positive meanings of conventional cars across segments indicate the strong cultural embeddedness of this mode in society. We discuss the implications of our approach for the development of government strategies for sustainable transport.}, subject = {Segmentierung}, language = {en} } @article{SchauenburgConradvonScheveetal., author = {Schauenburg, Gesche and Conrad, Markus and von Scheve, Christian and Barber, Horacio A. and Ambrasat, Jens and Aryani, Arash and Schr{\"o}der, Tobias}, title = {Making sense of social interaction : emotional coherence drives semantic integration as assessed by event-related potentials}, series = {Neuropsychologia}, volume = {125}, journal = {Neuropsychologia}, publisher = {Amsterdam}, address = {Elsevier}, issn = {1873-3514}, doi = {10.1016/j.neuropsychologia.2019.01.002}, pages = {1 -- 13}, abstract = {We compared event-related potentials during sentence reading, using impression formation equations of a model of affective coherence, to investigate the role of affective content processing during meaning making. The model of Affect Control Theory (ACT; Heise, 1979, 2007) predicts and quantifies the degree to which social interactions deflect from prevailing social norms and values - based on the affective meanings of involved concepts. We tested whether this model can predict the amplitude of brain waves traditionally associated with semantic processing. To this end, we visually presented sentences describing basic subject-verb-object social interactions and measured event-related potentials for final words of sentences from three different conditions of affective deflection (low, medium, high) as computed by a variant of the ACT model (Schr{\"o}der, 2011). Sentence stimuli were closely controlled across conditions for alternate semantic dimensions such as contextual constraints, cloze probabilities, co-occurrences of subject-object and verb-object relations. Personality characteristics (schizotypy, Big Five) were assessed to account for individual differences, assumed to influence emotion-language interactions in information processing. Affective deflection provoked increased negativity of ERP waves during the P2/N2 and N400 components. Our data suggest that affective incoherence is perceived as conflicting information interfering with early semantic processing and that increased respective processing demands - in particular in the case of medium violations of social norms - linger on until the N400 time window classically associated with the integration of concepts into embedding context. We conclude from these results that affective meanings influence basic stages of meaning making.}, subject = {Interaktion}, language = {en} } @inproceedings{SzczepanskaPriebeSchroeder, author = {Szczepanska, Timo and Priebe, Max and Schr{\"o}der, Tobias}, title = {Teaching the Complexity of Urban Systems with Participatory Social Simulation}, series = {Advances in Social Simulation}, booktitle = {Advances in Social Simulation}, publisher = {Springer}, address = {Cham}, isbn = {978-3-030-34127-5}, doi = {10.1007/978-3-030-34127-5_43}, pages = {427 -- 439}, abstract = {We describe how we use social simulation as a core method in a new master's program designed to teach future leaders of urban change to deal with the complexity inherent in current societal transformations. We start by depicting the challenges with regard to cross-disciplinary knowledge integration and overcoming value-based, rigid thinking styles that inevitably arise in the process of solving ecological, technological, or social problems in cities new and old. Next, we describe a course based on urban modeling and participatory approaches, designed to meet those challenges. We reflect on our first experience with this approach and discuss future developments and research needs.}, subject = {Verst{\"a}dterung}, language = {en} } @article{ZoellerMorganSchroeder, author = {Z{\"o}ller, Nikolas and Morgan, Jonathan Howard and Schr{\"o}der, Tobias}, title = {A topology of groups}, series = {Technological Forecasting and Social Change}, volume = {161}, journal = {Technological Forecasting and Social Change}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1873-5509}, doi = {10.1016/j.techfore.2020.120291}, pages = {19}, abstract = {In this work, we study the collaboration patterns of open source software projects on GitHub by analyzing the pull request submissions and acceptances of repositories. We develop a group typology based on the structural properties of the corresponding directed graphs, and analyze how the topology is connected to the repositorys collective identity, hierarchy, productivity, popularity, resilience and stability. These analyses indicate significant differences between group types and thereby provide valuable insights on how to effectively organize collaborative software development. Identifying the mechanisms that underlie self-organized collaboration on digital platforms is important not just to better understand open source software development but also all other decentralized and digital work environments, a setting widely regarded as a key feature of the future work place.}, subject = {GitHub}, language = {en} } @article{LuthardtSchroederHildebrandtetal., author = {Luthardt, Jasmin and Schr{\"o}der, Tobias and Hildebrandt, Frauke and Bormann, Inka}, title = {"And then we'll just check if it suits us" : cognitive-affective maps of social innovation in early childhood education}, series = {Frontiers in Education}, volume = {5}, journal = {Frontiers in Education}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2504-284X}, doi = {10.3389/feduc.2020.00033}, pages = {19}, abstract = {The idea that a simple execution of an innovation invented by actors other than those who are expected to apply it is not likely to take place is a truism. We assume, however, in this paper the idea of a discursive production of knowledge on the application of an innovation across different levels of the education system. We aim to shed light on an innovation's 'journey' from educational policy over training providers to teams of professionals in early childhood education and care (ECEC). By investigating knowledge and emotions associated with the introduction of an intended innovation using the example of "stimulation interactions" in day care-centers, the paper contributes to research on the transfer of innovations in education. To better understand challenges occurring during the transfer of innovations, we triangulate methods from discourse theory (coding techniques based on GTM) and cognitive science, namely cognitive-affective mapping (according to the scholarly conventions). The data corpus includes educational plans (N = 2), in-service training programs (N = 123) and group discussions of pedagogical teams (N = 6) who participated in an in-service training on the subject, stimulating interaction. Findings underline that similar messages from the inventors on the educational policy level are received and processed heterogeneously by the teams of pedagogues as a result of their preexisting views, routine practices and experiences with intended innovations through in-service trainings. Besides, a diffuse mixture of competing and contradictory information is communicated to the professionals and, hence, collides with the in-service training providers' and educational policy actors' expectations on the processing of the intended innovation. Specific knowledge elements and their valences are diametrically opposed to each other. Dissonances like these are considered as obstacles to social innovation. The obstacles are caused by the lack of a 'common language' beyond all levels. Hence, policy-makers and in-service-training providers should anticipate the supportive as well as competing knowledge-emotional complexes of professionals and take these into account when communicating an intended innovation.}, subject = {Sozialinnovation}, language = {en} }