@article{SchachnerGrossHasletal.2021,
  author    = {Schachner, Theresa and Gross, Christoph and Hasl, Andrea and Wangenheim, Florian von and Kowatsch, Tobias},
  title     = {Deliberative and paternalistic interaction styles for conversational agents in digital health},
  series = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR},
  volume    = {23},
  journal   = {Journal of medical internet research : international scientific journal for medical research, information and communication on the internet ; JMIR},
  number    = {1},
  publisher = {Healthcare World},
  address   = {Richmond, Va.},
  issn      = {1438-8871},
  doi       = {10.2196/22919},
  pages     = {13},
  year      = {2021},
  abstract  = {Background: Recent years have witnessed a constant increase in the number of people with chronic conditions requiring ongoing medical support in their everyday lives. However, global health systems are not adequately equipped for this extraordinarily time-consuming and cost-intensive development. Here, conversational agents (CAs) can offer easily scalable and ubiquitous support. Moreover, different aspects of CAs have not yet been sufficiently investigated to fully exploit their potential. One such trait is the interaction style between patients and CAs. In human-to-human settings, the interaction style is an imperative part of the interaction between patients and physicians. Patient-physician interaction is recognized as a critical success factor for patient satisfaction, treatment adherence, and subsequent treatment outcomes. However, so far, it remains effectively unknown how different interaction styles can be implemented into CA interactions and whether these styles are recognizable by users. Objective: The objective of this study was to develop an approach to reproducibly induce 2 specific interaction styles into CA-patient dialogs and subsequently test and validate them in a chronic health care context. Methods: On the basis of the Roter Interaction Analysis System and iterative evaluations by scientific experts and medical health care professionals, we identified 10 communication components that characterize the 2 developed interaction styles: deliberative and paternalistic interaction styles. These communication components were used to develop 2 CA variations, each representing one of the 2 interaction styles. We assessed them in a web-based between-subject experiment. The participants were asked to put themselves in the position of a patient with chronic obstructive pulmonary disease. These participants were randomly assigned to interact with one of the 2 CAs and subsequently asked to identify the respective interaction style. Chi-square test was used to assess the correct identification of the CA-patient interaction style. Results: A total of 88 individuals (42/88, 48\% female; mean age 31.5 years, SD 10.1 years) fulfilled the inclusion criteria and participated in the web-based experiment. The participants in both the paternalistic and deliberative conditions correctly identified the underlying interaction styles of the CAs in more than 80\% of the assessments (X-1(,8)8(2)=38.2; P<.001; phi coefficient r(phi)=0.68). The validation of the procedure was hence successful. Conclusions: We developed an approach that is tailored for a medical context to induce a paternalistic and deliberative interaction style into a written interaction between a patient and a CA. We successfully tested and validated the procedure in a web-based experiment involving 88 participants. Future research should implement and test this approach among actual patients with chronic diseases and compare the results in different medical conditions. This approach can further be used as a starting point to develop dynamic CAs that adapt their interaction styles to their users.},
  language  = {en}
}
@article{KaufholdBayerBaeumleretal.2023,
  author    = {Kaufhold, Marc-Andr{\´e} and Bayer, Markus and B{\"a}umler, Julian and Reuter, Christian and Stieglitz, Stefan and Basyurt, Ali Sercan and Mirbabaie, Milad and Fuchss, Christoph and Eyilmez, Kaan},
  title     = {CYLENCE: strategies and tools for cross-media reporting, detection, and treatment of cyberbullying and hatespeech in law enforcement agencies},
  series = {Mensch und Computer 2023: Workshopband MuC 2023},
  journal   = {Mensch und Computer 2023: Workshopband MuC 2023},
  publisher = {Gesellschaft f{\"u}r Informatik e.V. (GI)},
  address   = {Bonn},
  doi       = {10.18420/MUC2023-MCI-WS01-211},
  pages     = {1 -- 8},
  year      = {2023},
  abstract  = {Despite the merits of public and social media in private and professional spaces, citizens and professionals are increasingly exposed to cyberabuse, such as cyberbullying and hate speech. Thus, Law Enforcement Agencies (LEA) are deployed in many countries and organisations to enhance the preventive and reactive capabilities against cyberabuse. However, their tasks are getting more complex by the increasing amount and varying quality of information disseminated into public channels. Adopting the perspectives of Crisis Informatics and safety-critical Human-Computer Interaction (HCI) and based on both a narrative literature review and group discussions, this paper first outlines the research agenda of the CYLENCE project, which seeks to design strategies and tools for cross-media reporting, detection, and treatment of cyberbullying and hatespeech in investigative and law enforcement agencies. Second, it identifies and elaborates seven research challenges with regard to the monitoring, analysis and communication of cyberabuse in LEAs, which serve as a starting point for in-depth research within the project.},
  language  = {en}
}