| The Dawn of the Human-Machine Era: A forecast of new and emerging language technologies. D Sayers, R Sousa-Silva, S Höhn, L Ahmedi, K Allkivi-Metsoja, ... | 46 | 2021 |
| Heuristic evaluation of COVID-19 chatbots S Höhn, K Bongard-Blanchy International Workshop on Chatbot Research and Design, 131-144, 2020 | 36 | 2020 |
| Conversational interfaces for explainable AI: a human-centred approach SF Jentzsch, S Höhn, N Hochgeschwender Explainable, Transparent Autonomous Agents and Multi-Agent Systems: First …, 2019 | 36 | 2019 |
| Artificial conversational companions a requirements analysis S Danilava, S Busemann, C Schommer ICAART 2012, 2012 | 26 | 2012 |
| Quizbot: Exploring formative feedback with conversational interfaces B Vijayakumar, S Höhn, C Schommer Technology Enhanced Assessment: 21st International Conference, TEA 2018 …, 2019 | 25 | 2019 |
| A data-driven model of explanations for a chatbot that helps to practice conversation in a foreign language S Höhn Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue …, 2017 | 17 | 2017 |
| Artificial companion for second language conversation S Höhn Springer International Publishing, 2019 | 15 | 2019 |
| Towards computational models for a long-term interaction with an artificial conversational companion S Danilava, S Busemann, C Schommer, G Ziegler Proceedings" 5th International Conference on Agents an Artificial …, 2013 | 11 | 2013 |
| The Dawn of the Human-Machine Era: A forecast of new and emerging language technologies. Report for EU COST Action CA19102 ‘Language in The Human-Machine Era’ D Sayers, R Sousa-Silva, S Höhn, A Lule, K Allkivi-Metsoja, D Anastasiou | 8 | 2021 |
| Social agents for teamwork and group interactions (dagstuhl seminar 19411) E André, A Paiva, J Shah, S Šabanovic Schloss-Dagstuhl-Leibniz Zentrum für Informatik, 2020 | 8 | 2020 |
| BelElect: a new dataset for bias research from a “dark” platform S Höhn, S Mauw, N Asher Proceedings of the International AAAI Conference on Web and Social Media 16 …, 2022 | 7 | 2022 |
| Examining Linguistic Biases in Telegram with a Game Theoretic Analysis SM Sviatlana Höhn, Nicholas Asher MISDOOM 2021, 2021 | 7* | 2021 |
| PERSEUS: a personalization framework for sentiment categorization with recurrent neural network S Guo, S Höhn, F Xu, C Schommer 10th International Conference on Agents and Artificial Intelligence, 2018 | 7 | 2018 |
| Why are you silent?-Towards responsiveness in chatbots S Danilava, S Busemann, C Schommer, G Ziegler Avec le Temps! Time, Tempo, and Turns in Human-Computer Interaction …, 2013 | 7 | 2013 |
| A personalized sentiment model with textual and contextual information S Guo, S Höhn, C Schommer Proceedings of the 23rd conference on computational natural language …, 2019 | 6 | 2019 |
| Personalized sentiment analysis and a framework with attention-based Hawkes process model S Guo, S Höhn, F Xu, C Schommer Agents and Artificial Intelligence: 10th International Conference, ICAART …, 2019 | 6 | 2019 |
| Data-driven repair models for text chat with language learners S Höhn Unilu-University of Luxembourg, Luxembourg, Luxembourg, 2016 | 6 | 2016 |
| Designing formative and adaptive feedback using incremental user models S Höhn, E Ras Advances in Web-Based Learning–ICWL 2016: 15th International Conference …, 2016 | 6 | 2016 |
| Chatbot Research and Design: 4th International Workshop, CONVERSATIONS 2020, Virtual Event, November 23–24, 2020, Revised Selected Papers A Følstad, T Araujo, S Papadopoulos, ELC Law, E Luger, M Goodwin, ... Springer Nature, 2021 | 5 | 2021 |
| Language Ideology Bias in Conversational Technology S Höhn, B Migge, D Dippold, B Schneider, S Mauw International Workshop on Chatbot Research and Design, 133-148, 2023 | 4 | 2023 |
Stephan BusemannPrincipal Researcher, DFKI GmbHVerified email at dfki.de
