HCI Publications

2024

- Ferwerda, B., Germanakos, P., Tkalcic, M. (2024). Seventh HUMANIZE Workshop on Transparency and Explainability in Adaptive Systems Through User Modeling Grounded in Psychological Theory: Summary. ACM Digital Library More information

- Germanakos, P., Dimitrova, V., Steichen, B., Ferwerda, B., Tkalcic, M. (2024). HAAPIE 2024: 9th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments. ACM Digital Library More information

- van Bree, L., Graus, M., Ferwerda, B. (2024). Framing Theory on Music Streaming Platforms: How Vocabulary Influences Music Playlist Decision-Making and Expectations. CEUR-WS More information

- Ghaffari, M., Khan, G., Singh, S., Ferwerda, B. (2024). The impact of COVID-19 on online music listening behaviors in light of listeners’ social interactions. Multimedia tools and applications (pp. 13197-13239). More information

2023

- Alklind Taylor, A., Nalin, K., Holgersson, J., Gising, A., Ferwerda, B., Chen, L. (2023). Guardian Angel: Using Lighting Drones to Improve Traffic Safety, Sense of Security, and Comfort for Cyclists. Springer More information

- Starke, A., Emami, K., Makarová, A., Ferwerda, B. (2023). Using Visual and Linguistic Framing to Support Sustainable Decisions in an Online Store. CEUR More information

- Ferwerda, B., Boksjö, N., Petricioiu, N., Wollny, C. (2023). What’s in a Name?: How Perceived Music Playlist Personalization Influences Content Expectations. Springer More information

- Knees, P., Schedl, M., Ferwerda, B., Laplante, A. (2023). Listener awareness in music recommender systems: directions and current trends. In: M. Augstein, E. Herder & W. Wörndl (Ed.), De Gruyter Textbook Oldenbourg: Walter de Gruyter More information

- Graus, M., Ferwerda, B. (2023). Theory-grounded user modeling for personalized HCI. In: M. Augstein, E. Herder & W. Wörndl (Ed.), De Gruyter Textbook Oldenbourg: Walter de Gruyter More information

- Horikawa, R., Nakajima, T., Ferwerda, B. (2023). Investigating the psychological impact of emotion visualization and heart rate sharing in online communication. Cham: Springer More information

- Ferwerda, B., Ingesson, E., Berndl, M., Schedl, M. (2023). I Don't Care How Popular You Are! Investigating Popularity Bias in Music Recommendations from a User's Perspective. Association for Computing Machinery (ACM) More information

- Lesota, O., Escobedo, G., Deldjoo, Y., Ferwerda, B., Kopeinik, S., Lex, E. ... Schedl, M. (2023). Computational Versus Perceived Popularity Miscalibration in Recommender Systems. Association for Computing Machinery (ACM) More information

- Ferwerda, B., Hanbury, A., Knijnenburg, B., Larsen, B., Michiels, L., Papenmeier, A. ... Willemsen, M. (2023). Reality Check – Conducting Real World Studies. Dagstuhl Reports 13(1), 20-40 More information

- Germanakos, P., Dimitrova, V., Steichen, B., Ferwerda, B., Tkalcic, M. (2023). HAAPIE 2023: 8th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments. Association for Computing Machinery (ACM) More information

- Bauer, C., Ferwerda, B. (2023). The Effect of Ingroup Identification on Conformity Behavior in Group Decision-Making: The Flipping Direction Matters. IEEE Computer Society More information

2022

- Knees, P., Ferwerda, B., Rauber, A., Strumbelj, S., Resch, A., Tomandl, L. ... Dizdar, R. (2022). A Reproducibility Study On User-Centric Mir Researchand Why It Is Important. More information

- Landia, N., McAlister, R., North, D., Kalloori, S., Srivastava, A., Ferwerda, B. (2022). RecSys Challenge 2022 Dataset: Dressipi 1M Fashion Sessions. Association for Computing Machinery (ACM) More information

- Landia, N., Cheung, F., North, D., Kalloori, S., Srivastava, A., Ferwerda, B. (2022). RecSys Challenge 2022: Fashion Purchase Prediction. Association for Computing Machinery (ACM) More information

- Ferwerda, B., Kiunsi, D., Tkalčič, M. (2022). Too Much of a Good Thing: When In-Car Driver Assistance Notifications Become Too Much. Association for Computing Machinery (ACM) More information

- Ferwerda, B., Bauer, C. (2022). To Flip or Not to Flip: Conformity Effect Across Cultures. Association for Computing Machinery (ACM) More information

- Starke, A., Sedkowska, J., Chouhan, M., Ferwerda, B. (2022). Examining Choice Overload across Single-list andMulti-list User Interfaces. CEUR-WS More information

- Germanakos, P., Dimitrova, V., Steichen, B., Ferwerda, B., Tkalcic, M. (2022). HAAPIE 2022: 7th International Workshop on Human Aspects in Adaptive and Personalized Interactive Environments. Association for Computing Machinery (ACM) More information

- Ferwerda, B., Tkalčič, M., Germanakos, P. (2022). Sixth HUMANIZE Workshop on Transparency and Explainability in Adaptive Systems Through User Modeling Grounded in Psychological Theory: Summary. ACM Digital Library More information

2021

- Belli, L., Tejani, A., Portman, F., Lung-Yut-Fong, A., Chamberlain, B., Xie, Y. ... Shi, W. (2021). The 2021 RecSys Challenge Dataset: Fairness is Not Optional. Association for Computing Machinery (ACM) More information

- Anelli, V., Kalloori, S., Ferwerda, B., Belli, L., Tejani, A., Portman, F. ... Shi, W. (2021). RecSys 2021 challenge workshop: Fairness-aware engagement prediction at scale on Twiter's Home Timeline. Association for Computing Machinery (ACM) More information

- Graus, M., Ferwerda, B., Tkalcic, M., Germanakos, P. (2021). Fifth HUMANIZE workshop on transparency and explainability in adaptive systems through user modeling grounded in psychological theory: Summary. Association for Computing Machinery More information

- Ferwerda, B., Chen, L., Tkalčič, M. (2021). Editorial: Psychological Models for Personalized Human-Computer Interaction (HCI). Frontiers in Psychology More information

- Graus, M., Ferwerda, B. (2021). The moderating effect of active engagement on appreciation of popularity in song recommendations. Cham: Springer More information

- Eriksson, M., Ferwerda, B. (2021). Towards a User Experience Framework for Business Intelligence. Journal of Computer Information Systems 61(5), 428-437 More information

2020

- Ghaffari, M., Khan, G., Ferwerda, B., Singh, S. (2020). Music Oh my Music: A Network Perspective on Online Music Listening Behaviour. More information

- Ferwerda, B., Tkalčič, M. (2020). Exploring the Prediction of Personality Traits from Drug Consumption Profiles. Association for Computing Machinery (ACM) More information

- Graus, M., Ferwerda, B., Tkalcic, M., Germanakos, P. (2020). Fourth HUMANIZE workshop on transparency and explainability in adaptive systems through user modeling grounded in psychological theory: Summary. Association for Computing Machinery (ACM) More information

- Xu, Y., Ferwerda, B., Lee, M. (2020). A Qualitative Study of User Participation and Challenges in a Social Shopping Context. Association for Computing Machinery (ACM) More information

- Bauer, C., Ferwerda, B. (2020). Conformity Behavior in Group Playlist Creation. More information

2019

- Knees, P., Schedl, M., Ferwerda, B., Laplante, A. (2019). User Awareness in Music Recommender Systems. In: M. Augstein, E. Herder & W. Wörndl (Ed.), De Gruyter Textbook Berlin: Walter de Gruyter More information

- Graus, M., Ferwerda, B. (2019). Theory-grounded user modeling for personalized HCI. In: M. Augstein, E. Herder & W. Wörndl (Ed.), De Gruyter Textbook Berlin: Walter de Gruyter More information

- Ferwerda, B., Tkalcic, M. (2019). Exploring Online Music Listening Behaviors of Musically Sophisticated Users. More information

- Graus, M., Ferwerda, B., Tkalcic, M., Germanakos, P. (2019). Third workshop on theory-informed user modeling for tailoring and personalizing interfaces (HUMANIZE): preface. Association for Computing Machinery (ACM) More information

- Graus, M., Ferwerda, B., Tkalčič, M., Germanakos, P. (2019). A summary of the third workshop on theory-informed user modeling for tailoring and personalizing interfaces. CEUR-WS More information

- Ferwerda, B., Yang, E., Schedl, M., Tkalcic, M. (2019). Personality and taxonomy preferences, and the influence of category choice on the user experience for music streaming services. Multimedia tools and applications 78(14), 20157-20190 More information

- Ferwerda, B., Lee, M. (2019). Tamagotchi++: A Serious, Personalized Game to Encourage Healthy Behavior. CEUR-WS More information

- Kiunsi, D., Ferwerda, B. (2019). Using a Serious Game to Teach User-Centered Design. CEUR-WS More information

2018

- Graus, M., Ferwerda, B., Tkalcic, M., Germanakos, P. (2018). Second workshop on theory-informed user modeling for tailoring and personalizing interfaces (HUMANIZE): Workshop preface. CEUR-WS More information

- Ferwerda, B., Graus, M. (2018). Predicting Musical Sophistication from Music Listening Behaviors: A Preliminary Study. More information

- Tkalcic, M., Ferwerda, B. (2018). Theory-driven Recommendations: Modeling Hedonic and Eudaimonic Movie Preferences. Aachen: CEUR-WS More information

- Tkalcic, M., Ferwerda, B. (2018). Eudaimonic Modeling of Moviegoers. More information

- Ferwerda, B., Tkalcic, M. (2018). Predicting Users' Personality from Instagram Pictures: Using Visual and/or Content Features?. Association for Computing Machinery (ACM) More information

- Graus, M., Ferwerda, B., Tkalcic, M., Germanakos, P. (2018). Second Workshop on Theory-Informed User Modeling for Tailoring and Personalizing Interfaces (HUMANIZE). CEUR-WS More information

- Lay, A., Ferwerda, B. (2018). Predicting Users’ Personality Based on Their ‘Liked’ Images on Instagram. CEUR-WS More information

- Ferwerda, B., Tkalcic, M. (2018). You Are What You Post: What the Content of Instagram Pictures Tells About Users’ Personality. CEUR-WS More information

2017

- Schedl, M., Lemmerich, F., Ferwerda, B., Skowron, M., Knees, P. (2017). Indicators of Country Similarity in Terms of Music Taste, Cultural, and Socio-economic Factors. IEEE More information

- Schedl, M., Ferwerda, B. (2017). Large-scale Analysis of Group-specific Music Genre Taste From Collaborative Tags. IEEE More information

- Ferwerda, B., Tkalcic, M., Schedl, M. (2017). Personality Traits and Music Genre Preferences: How Music Taste Varies Over Age Groups. CEUR-WS More information