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, Article 829939. https://doi.org/10.3389/fdata.2022.829939 ( reposiTUm)

Aayesha, A., Afzaal, M., & Neidhardt, J. (2024). User Experience of Recommender System: A User Study of Social-aware Fashion Recommendations System. In Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 356–361). https://doi.org/10.1145/3631700.3664896 ( reposiTUm)

Scholz, F., Kolb, T. E., & Neidhardt, J. (2024). Classifying User Roles in Online News Forums: A Model for User Interaction and Behavior Analysis. In Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 240–249). https://doi.org/10.1145/3631700.3665187 ( reposiTUm)

Kolb, T. E. (2024). Enhancing Cross-Domain Recommender Systems with LLMs: Evaluating Bias and Beyond-Accuracy Measures. In RecSys ’24: Proceedings of the 18th ACM Conference on Recommender Systems (pp. 1388–1394). Association for Computing Machinery. https://doi.org/10.1145/3640457.3688027 ( reposiTUm)

Godolja, D., Kolb, T. E., & Neidhardt, J. (2024). Unlocking the Potential of Content-Based Restaurant Recommender Systems. In A. Tuomi (Ed.), Information and Communication Technologies in Tourism 2024 (pp. 239–244). Springer, Cham. https://doi.org/10.1007/978-3-031-58839-6_26 ( reposiTUm)

Huebner, B., Kolb, T. E., & Neidhardt, J. (2024). Evaluating Group Fairness in News Recommendations: A Comparative Study of Algorithms and Metrics. In Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 337–346). https://doi.org/10.1145/3631700.3664897 ( reposiTUm)

Wagne, A., & Neidhardt, J. (2024). Can We Integrate Items into Models? Knowledge Editing to Align LLMs with Product Catalogs. In V. W. Anelli, P. Basile, & T. Di Noia (Eds.), Proceedings of the Sixth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 18th ACM Conference on Recommender Systems (RecSys 2024). https://doi.org/10.34726/8229 ( reposiTUm)

Nalis, I., Sippl, T., Kolb, T. E., & Neidhardt, J. (2024). Navigating Serendipity - An Experimental User Study On The Interplay of Trust and Serendipity In Recommender Systems. In UMAP Adjunct ’24: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization (pp. 386–393). https://doi.org/10.1145/3631700.3664901 ( reposiTUm)

Neidhardt, J., Kuflik, T., Livne, A., & Zanker, M. (2024). Workshop on Recommenders in Tourism (RecTour) 2024. In RecSys ’24: Proceedings of the 18th ACM Conference on Recommender Systems (pp. 1229–1231). https://doi.org/10.1145/3640457.3687107 ( reposiTUm)

Neidhardt, J. (2024). Transforming Recommender Systems: Balancing Personalization, Fairness, and Human Values. In K. Larson (Ed.), Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence (pp. 8559–8564). International Joint Conferences on Artificial Intelligence. https://doi.org/10.24963/ijcai.2024/982 ( reposiTUm)

Wagne, A., & Neidhardt, J. (2024). What to compare? Towards understanding user sessions on price comparison platforms. In T. Di Noia, P. Lops, T. Joachims, katrien verbert, P. Castells, Z. Dong, & B. London (Eds.), RecSys ’24: Proceedings of the 18th ACM Conference on Recommender Systems (pp. 1158–1162). Association for Computing Machinery. https://doi.org/10.1145/3640457.3691717 ( reposiTUm)

Wagne, A., Neidhardt, J., & Kolb, T. E. (2024). PopAut: An Annotated Corpus for Populism Detection in Austrian News Comments. In N. Calzolari, M.-Y. Kan, V. Hoste, A. LENCI, S. Sakti, & N. Xue (Eds.), The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024): Main Conference Proceedings (pp. 12879–12892). ELRA Language Resources Association (ELRA). http://hdl.handle.net/20.500.12708/199247 ( reposiTUm)

Aayesha, A., Afzaal, M., & Neidhardt, J. (2024). Social Circle-Enhanced Fashion Recommendations System. In P. Brusilovsky, M. de Gemmis, & A. Felfernig (Eds.), Proceedings of the 11th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems co-located with 18th ACM Conference on Recommender Systems (RecSys 2024) (pp. 81–91). http://hdl.handle.net/20.500.12708/208019 ( reposiTUm)

Pachinger, P., Goldzycher, J., Planitzer, A. M., Kusa, W., Hanbury, A., & Neidhardt, J. (2024). AustroTox: A Dataset for Target-Based Austrian German Offensive Language Detection. In The 62nd Annual Meeting of the Association for Computational Linguistics : Findings of the Association for Computational Linguistics: ACL 2024 (pp. 11990–12001). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.findings-acl.713 ( reposiTUm)

Basso, L., Nalis-Neuner, I., & Neidhardt, J. (2023). News Diversity and Well-Being – An Experimental Exploration Of Diversity-Aware Recommender Systems. In FAccTRec Program. 6th FAccTRec Workshop on Responsible Recommendation at RecSys 2023, Singapur, Singapore. ( reposiTUm)

Nalis, I., & Neidhardt, J. (2023). Not Facial Expression, nor Fingerprint – Acknowledging Complexity and Context in Emotion Research for Human-Centered Personalization and Adaptation. In Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 325–330). Association for Computing Machinery. https://doi.org/10.1145/3563359.3596990 ( reposiTUm)

Sertkan, M., Althammer, S., Hofstätter, S., Knees, P., & Neidhardt, J. (2023). Exploring Effect-Size-Based Meta-Analysis for Multi-Dataset Evaluation. In 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). PERSPECTIVES 2023 - Perspectives on the Evaluation of Recommender Systems Workshop co-located with the 17th ACM Conference on Recommender Systems, Singapore, Singapore. CEUR-WS.org. https://doi.org/10.34726/5352 ( reposiTUm)

Sertkan, M., Althammer, S., & Hofstätter, S. (2023). Ranger: A Toolkit for Effect-Size Based Multi-Task Evaluation. In B. Danushka (Ed.), Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 3: System Domonstrations) (pp. 581–587). Association for Computational Linguistics. https://doi.org/10.18653/v1/2023.acl-demo.56 ( reposiTUm)

Kolb, T. E., Nalis-Neuner, I., & Neidhardt, J. (2023). Like a Skilled DJ - an Expert Study on News Recommendations Beyond Accuracy. In B. Kille (Ed.), Proceedings of the International Workshop on News Recommendation and Analytics co-located with the 2023 ACM Conference on Recommender Systems (RecSys 2023). CEUR-WS.org. https://doi.org/10.34726/5332 ( reposiTUm)

Sertkan, M., & Neidhardt, J. (2023). On the Effect of Incorporating Expressed Emotions in News Articles on Diversity within Recommendation Models. In B. Kille (Ed.), Proceedings of the International Workshop on News Recommendation and Analytics, co-located with the 2023 ACM Conference on Recommender Systems (RecSys 2023). CEUR-WS.org. https://doi.org/10.34726/5353 ( reposiTUm)

Pachinger, P., Hanbury, A., Neidhardt, J., & Planitzer, A. M. (2023). Toward Disambiguating the Definitions of Abusive, Offensive, Toxic, and Uncivil Comments. In Proceedings of the First Workshop on Cross-Cultural Considerations in NLP (C3NLP) (pp. 107–113). https://doi.org/10.18653/v1/2023.c3nlp-1.11 ( reposiTUm)

Prem, E., Neidhardt, J., Knees, P., Woltran, S., & Werthner, H. (2023). Digital Humanism and Norms in Recommender Systems. In S. Vrijenhoek, L. Michiels, J. Kruse, A. Starke, J. Viader Guerrero, & N. Tintarev (Eds.), Proceedings of the First Workshop on the Normative Design and Evaluation of Recommender Systems. CEUR-WS.org. https://doi.org/10.34726/8560 ( reposiTUm)

Kolb, T. E., Wagne, A., Sertkan, M., & Neidhardt, J. (2023). Potentials of Combining Local Knowledge and LLMs for Recommender Systems. In V. W. Anelli, P. Basile, G. De Melo, F. Donini, A. Ferrara, C. Musto, F. Narducci, A. Ragone, & M. Zanker (Eds.), Proceedings of the Fifth Knowledge-aware and Conversational Recommender Systems Workshop co-located with 17th ACM Conference on Recommender Systems (RecSys 2023) (pp. 61–64). CEUR-WS.org. https://doi.org/10.34726/5334 ( reposiTUm)

Neidhardt, J., Wörndl, W., Kuflik, T., Goldenberg, D., & Zanker, M. (2023). Workshop on Recommenders in Tourism (RecTour) 2023. In J. Zhang, L. Chen, & S. Berkovsky (Eds.), RecSys ’23: Proceedings of the 17th ACM Conference on Recommender Systems (pp. 1274–1275). Association for Computing Machinery. https://doi.org/10.1145/3604915.3608764 ( reposiTUm)

Kuflik, T., Kleanthous, S., Neidhardt, J., & Pera, M. S. (2023). UMAP 2023 Chairs’ Welcome. In UMAP 2023: Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. iii–vi). Association for Computing Machinery (ACM). http://hdl.handle.net/20.500.12708/210864 ( reposiTUm)

Sertkan, M., Althammer, S., Hofstätter, S., & Neidhardt, J. (2022). Diversifying Sentiments in News Recommendation. In Perspectives 2022. Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2022. PERSPECTIVES 2022 - Perspectives on the Evaluation of Recommender Systems Workshop co-located with the 16th ACM Conference on Recommender Systems, Seattle, WA, United States of America (the). https://doi.org/10.34726/3903 ( reposiTUm)

Sertkan, M., & Neidhardt, J. (2022). Exploring Expressed Emotions for Neural News Recommendation. In UMAP ’22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 22–28). Association for Computing Machinery. https://doi.org/10.1145/3511047.3536414 ( reposiTUm)

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 Kolb Thomas (Ed.), Unofficial Proceedings of the 5th FAccTRec Workshop on Responsible Recommendation at RecSys 2022. https://doi.org/10.48550/ARXIV.2209.07608 ( reposiTUm)

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, & giovanni stilo (Eds.), Advances in Bias and Fairness in Information Retrieval (pp. 35–42). Springer Cham. https://doi.org/10.1007/978-3-031-09316-6_4 ( reposiTUm)

Neidhardt, J., Wörndl, W., Kuflik, T., Goldenberg, D., & Zanker, M. (2022). Workshop on Recommenders in Tourism (RecTour). In J. Golbeck, F. M. Harper, & V. Murdock (Eds.), RecSys ’22: Proceedings of the 16th ACM Conference on Recommender Systems (pp. 678–679). Association for Computing Machinery. https://doi.org/10.1145/3523227.3547416 ( reposiTUm)

Grossmann, W., Sertkan, M., Neidhardt, J., & Werthner, H. (2023). Pictures as a tool for matching tourist preferences with destinations. In M. Augstein, E. Herder, & W. Wörndl (Eds.), Personalized Human-Computer Interaction (pp. 337–354). De Gruyter Oldenbourg. https://doi.org/10.1515/9783110988567-013 ( reposiTUm)

Knees, P., Neidhardt, J., & Nalis-Neuner, I. (2023). Recommender Systems: Techniques, Effects, and Measures Toward Pluralism and Fairness. In H. Werthner, C. Ghezzi, & J. Kramer (Eds.), Introduction to Digital Humanism : A Textbook (pp. 417–434). Springer. https://doi.org/10.1007/978-3-031-45304-5_27 ( reposiTUm)

Neidhardt, J., Kuflik, T., Livne, A., & Zanker, M. (Eds.). (2024). Proceedings of the Workshop on Recommenders in Tourism co-located with the 18th ACM Conference on Recommender Systems (RecSys 2024) (Vol. 3886). http://hdl.handle.net/20.500.12708/210872 ( reposiTUm)

Neidhardt, J., Wörndl, W., Kuflik, T., Goldenberg, D., & Zanker, M. (Eds.). (2023). Proceedings of the Workshop on Recommenders in Tourism co-located with the 17th ACM Conference on Recommender Systems (RecSys 2023) (Vol. 3568). http://hdl.handle.net/20.500.12708/193617 ( reposiTUm)

Kuflik, T., Kleanthous, S., Neidhardt, J., & Pera, M. S. (Eds.). (2023). Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery. https://doi.org/10.1145/3563359 ( reposiTUm)

Kuflik, T., Kleanthous, S., Neidhardt, J., & Pera, M. S. (Eds.). (2023). Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization. Association for Computing Machinery. https://doi.org/10.1145/3565472 ( reposiTUm)

Neidhardt, J., Wörndl, W., Kuflik, T., Goldenberg, D., & Zanker, M. (Eds.). (2022). Proceedings of the Workshop on Recommenders in Tourism (RecTour 2022): Vol. Vol-3219. http://hdl.handle.net/20.500.12708/153161 ( reposiTUm)

Pachinger, P., Goldzycher, J., Planitzer, A. M., Kusa, W., Hanbury, A., & Neidhardt, J. (2024, June 20). A Dataset for Span-Based Austrian German and English Offensive Language Detection [Poster Presentation]. Workshop on Online Abuse and Harms 2024, Mexico City, Mexico. http://hdl.handle.net/20.500.12708/210352 ( reposiTUm)

Kolb, T. E. (2023, January 25). Sentiment Analysis [Presentation]. ÖAW AI Winter School 2023, Austria. ( reposiTUm)

Kolb, T. E. (2023, September 5). Hands-on Session ChatGPT [Presentation]. 2nd ACM Digital Humanism Summer School, Wien, Austria. ( reposiTUm)

Neidhardt, J. (2023, October 20). Digital Humanism [Keynote Presentation]. Beyond Compliance 2023: Forum on Digital Ethics in Research, Porto, Portugal. http://hdl.handle.net/20.500.12708/193490 ( reposiTUm)

Nalis-Neuner, I. (2023, September). 2nd ACM Digital Humanism Summer School [Keynote Presentation]. 2nd ACM Digital Humanism Summer School, Wien, Austria. ( reposiTUm)

Nalis-Neuner, I. (2023, January 25). Sentiment Analysis - psychological perspective [Presentation]. ÖAW Winter School 2023, Wien, Austria. ( reposiTUm)

Neidhardt, J. (2022, October 5). Social Network Analysis [Presentation]. Course Social Network Analysis, University of Groningen, Netherlands (the). ( reposiTUm)

Hussak, M., Neidhardt, J., & Stilz, M. (2022, October 22). Bildung für den Frieden in einer digitalisierten Welt [Presentation]. make install PEACE Impulse für den Frieden #FIfFKon 2022, Berlin, Germany. http://hdl.handle.net/20.500.12708/153931 ( reposiTUm)