Basso, L., Nalis, I., & Neidhardt, J. (2023). News Diversity and Well-Being – An Experimental Exploration Of Diversity-Aware Recommender Systems (forthcoming). 5th FAccTRec Workshop on Responsible Recommendation at RecSys 2023.

Dietz, L. W., Sertkan, M., Myftija, S., Thimbiri Palage, S., Neidhardt, J., & Wörndl, W. (2022). A comparative study of data-driven models for travel destination characterization. Frontiers in Big Data, 5, 829939.

Grossmann, W., Sertkan, M., & Neidhardt, J. (2023). Pictures as a tool for matching tourist preferences with destinations. Personalized Human-Computer Interaction, 337–353. Link

Knees, P., Neidhardt, J., & Nalis, I. (2023). Recommender Systems: Techniques, Effects, and Measures Towards Pluralism and Fairness. In C. Ghezzi, J. Kramer, J. Nida-Rümelin, B. Nuseibeh, E. Prem, A. Stanger, & H. Werthner (Eds.), Introduction to Digital Humanism. Springer.

Kolb, T. E., Nalis, I., Sertkan, M., & Neidhardt, J. (2022). The Role of Bias in News Recommendation in the Perception of the Covid-19 Pandemic. In T. Kolb (Ed.), 5th FAccTRec Workshop on Responsible Recommendation at RecSys 2022. Link

Kolb, T. E., Nalis, I., & Neidhardt, J. (2023). Like a Skilled DJ - an Expert Study on News Recommendations Beyond Accuracy (forthcoming). Proceedings of the 11th International Workshop on News Recommendation and Analytics (INRA) in Conjunction with ACM RecSys 2023.

Kolb, T. E., Wagne, A., Sertkan, M., & Neidhardt, J. (2023). Potentials of Combining Local Knowledge and LLMs for Recommender Systems (forthcoming). Proceedings of the 5th Edition of Knowledge-Aware and Conversational Recommender Systems (KaRS) in Conjunction with ACM RecSys 2023.

Modre, L., Neidhardt, J., & Nalis, I. (2023). Value-Based Nudging in News Recommender Systems – Results From an Experimental User Study (forthcoming). Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems in Conjunction with ACM RecSys 2023.

Nalis, I., & Neidhardt, J. (2023). Not Facial Expression, nor Fingerprint–Acknowledging Complexity and Context in Emotion Research for Human-Centered Personalization and Adaptation. Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization, 325–330.

Neidhardt, J. (2022). Network Science and e-Tourism. In Z. Xiang, M. Fuchs, U. Gretzel, & W. Höpken (Eds.), Handbook of e-Tourism (pp. 583–594). Springer. Link

Neidhardt, J., & Sertkan, M. (2022). Towards an Approach for Analyzing Dynamic Aspects of Bias and Beyond-Accuracy Measures. In L. Boratto, S. Faralli, M. Marras, & G. Stilo (Eds.), Advances in Bias and Fairness in Information Retrieval (pp. 35–42). Springer International Publishing.

Neidhardt, J., Werthner, H., & Woltran, S. (2022). It Is Simple, It Is Complicated. In H. Werthner, E. Prem, E. A. Lee, & C. Ghezzi (Eds.), Perspectives on Digital Humanism (pp. 335–342). Springer International Publishing. Link

Pachinger, P., Hanbury, A., Neidhardt, J., & Planitzer, A. (2023). Toward Disambiguating the Definitions of Abusive, Offensive, Toxic, and Uncivil Comments. Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP), 107–113. Link

Prem, E., Neidhardt, J., Knees, P., Woltran, S., & Werthner, H. (2023). Digital Humanism and Norms in Recommender Systems. Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems in Conjunction with ACM RecSys 2023.

Sertkan, M., Althammer, S., Hofstätter, S. (2023). Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation. Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), 581–587. Link

Sertkan, M., Althammer, S., Hofstätter, S., Knees, P., & Neidhardt, J. (2023). Exploring Effect-Size-Based Meta-Analysis for Multi-Dataset Evaluation. Proceedings of the 3rd Workshop Perspectives on the Evaluation of Recommender Systems 2023 Co-Located with the 17th ACM Conference on Recommender Systems (RecSys 2023).

Sertkan, M., Althammer, S., Hofstätter, S., Neidhardt, J. (2022). Diversifying sentiments in news recommendation. Proceedings of the 2nd Perspectives on the Evaluation of Recommender Systems Workshop.

Sertkan, M., & Neidhardt, J. (2023). On the Effect of Incorporating Expressed Emotions in News Articles on Diversity Within Recommendation Models. Proceedings of the 11th International Workshop on News Recommendation and Analytics (INRA) in Conjunction with ACM RecSys 2023.

Sertkan, M., & Neidhardt, J. (2022). Exploring Expressed Emotions for Neural News Recommendation. Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, 22–28.