Publications

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2021

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Janek Bevendorff, Berta Chulvi, Gretel Liz De la Pena Sarracen, Mike Kestemont, Enrique Manjavacas, Ilia Markov, Maximilian Mayerl, Martin Potthast, Francisco Rangel, Paolo Rosso, Efstathios Stamatatos, Benno Stein, Matti Wiegmann, Magdalena Wolska and Eva Zangerle: Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection. In Experimental IR Meets Multilinguality, Multimodality, and Interaction - 12th International Conference of the CLEF Association, CLEF 2021, Virtual Event, September 21-24, 2021, Proceedings, vol.

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Eva Zangerle, Maximilian Mayerl, Martin Potthast and Benno Stein: Overview of the Style Change Detection Task at PAN 2021. In CLEF 2021 Labs and Workshops, Notebook Papers, pages 1760-1771. CEUR-WS.org, 2021

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Eva Zangerle , Christine Bauer and Alan Said: Proceedings of the Perspectives on the Evaluation of Recommender Systems Workshop 2021, co-located with the 15th ACM Conference on Recommender Systems (RecSys 2021). Vol. 2955. CEUR-WS.org, 2021

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Benjamin Murauer and Günther Specht: Small-Scale Cross-Language Authorship Attribution on Social Media Comments. In Proceedings of the 4th Workshop on Technologies for MT of Low Resource Languages (LoResMT2021), pages 11-19. 2021

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Martin Pichl and Eva Zangerle: User models for multi-context-aware music recommendation. In Multimedia Tools and Applications, vol. 80, no. 15, pages 22509-22531. Springer, 2021

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Eva Zangerle, Christine Bauer and Alan Said: Perspectives on the Evaluation of Recommender Systems (PERSPECTIVES). In Fifteenth ACM Conference on Recommender Systems, pages 794–795. Association for Computing Machinery, 2021

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Janek Bevendorff, BERTa Chulvi, Gretel Liz De La Pena Sarracen, Mike Kestemont, Enrique Manjavacas, Ilia Markov, Maximilian Mayerl, Martin Potthast, Francisco Rangel, Paolo Rosso, Efstathios Stamatatos, Benno Stein, Matti Wiegmann, Magdalena Wolska and Eva Zangerle: Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection. In Advances in Information Retrieval, pages 567-573. Springer International Publishing, 2021

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Eva Zangerle, Chih-Ming Chen, Ming-Feng Tsai and Yi-Hsuan Yang: Leveraging Affective Hashtags for Ranking Music Recommendations. In IEEE Transactions on Affective Computing, vol. 12, no. 1, pages 78-91. 2021

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Dominik Kowald, Peter Muellner, Eva Zangerle, Christine Bauer, Markus Schedl and Elisabeth Lex: Support the underground: characteristics of beyond-mainstream music listeners. In EPJ Data Science, vol. 10, no. 1, pages 1-26. Springer, 2021

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Günther Specht, Johannes Kessler, Maximilian Mayerl and Michael Tschuggnall: RelaX - Interaktive Relationale Algebra in der Lehre. In Datenbank-Spektrum. (1) 2021

2020

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Julie Cumming, Jin Ha Lee, Brian McFee, Markus Schedl, Johanna Devaney, Cory McKay, Eva Zangerle and Timothy de Reuse: Proceedings of the 21th International Society for Music Information Retrieval Conference, ISMIR 2020, Montreal, Canada, October 11-16, 2020. 

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Janek Bevendorff, Bilal Ghanem, Anastasia Giachanou, Mike Kestemont, Enrique Manjavacas, Martin Potthast, Francisco Rangel, Paolo Rosso, Günther Specht, Efstathios Stamatatos, Benno Stein, Matti Wiegmann and Eva Zangerle: Shared Tasks on Authorship Analysis at PAN 2020. In Advances in Information Retrieval (ECIR 2020), pages 508-516. Springer International Publishing, 2020

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Eva Zangerle, Martin Pichl and Markus Schedl: User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues. In Transactions of the International Society for Music Information Retrieval, vol. 3, no. 1. Ubiquity Press, 2020

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Manfred Moosleitner, Benjamin Murauer and Günther Specht: Detecting Conspiracy Tweets using Support Vector Machines. In Working Notes Proceedings of the MediaEval 2020 Workshop. ceur-ws.org, 2020.

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Michael Vötter, Maximilian Mayerl, Günther Specht and Eva Zangerle: Recognizing Song Mood and Theme: Leveraging Ensembles of Tag Groups. In Working Notes Proceedings of the MediaEval 2020 Workshop. ceur-ws.org, 2020

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Maximilian Mayerl, Michael Vötter, Manfred Moosleitner and Eva Zangerle: Comparing Lyrics Features for Genre Recognition. In Proceedings of the 1st Workshop on NLP for Music and Audio (NLP4MusA), pages 73-77. 2020.

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Alessandro B. Melchiorre, Eva Zangerle and Markus Schedl: Personality Bias of Music Recommendation Algorithms. In 14th ACM Conference on Recommender Systems (RecSys 2020), pages 533–538. ACM, 2020.

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Meijun Liu, Eva Zangerle, Xiao Hu, Alessandro Melchiorre and Markus Schedl: Pandemics, Music, and Collective Sentiment: Evidence from the Outbreak of COVID-19. In Proceedings of the 21st International Society for Music Information Retrieval Conference 2020 (ISMIR 2020), pages 157-165. 2020

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Clemens Hörtenhuemer and Eva Zangerle: A Multi-Aspect Classification Ensemble Approach for Profiling Fake News Spreaders on Twitter. In Proceedings of the International Conference and Labs of the Evaluation Forum (CLEF), Thessaloniki, Greece, pages 22-25. 2020.

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Janek Bevendorff, Bilal Ghanem, Anastasia Giachanou, Mike Kestemont, Enrique Manjavacas, Ilia Markov, Maximilian Mayerl, Martin Potthast, Francisco Rangel, Paolo Rosso and others: Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection. In International Conference of the Cross-Language Evaluation Forum for European Languages (CLEF 2020), pages 372-383. 2020.

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Eva Zangerle, Maximilian Mayerl, Günther Specht, Martin Potthast and Benno Stein: Overview of the style change detection task at PAN 2020. In CLEF 2020 Working Notes, CEUR Workshop Proceedings 2696, Paper 256. 9 S. 2020

2019

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Asir Saeed, Suzana Ilic and Eva Zangerle: Creating GANs for generating poems, lyrics and metaphors. In NeurIPS Machine Learning for Creativity and Design Workshop, 2019

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Michael Tschuggnall, Benjamin Murauer and Günther Specht: Reduce & Attribute: Two-Step Authorship Attribution for Large-Scale Problems. In Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL), pages 951-960. Association for Computational Linguistics, 2019

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Eva Zangerle, Ramona Huber, Michael Vötter and Yi-Hsuan Yang: Hit Song Prediction: Leveraging Low- and High-Level Audio Features. In Proceedings of the 20th International Society for Music Information Retrieval Conference 2019 (ISMIR 2019), pages 319-326. 2019

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Eva Zangerle, Michael Tschuggnall, Günther Specht, Martin Potthast and Benno Stein: Overview of the Style Change Detection Task at PAN 2019. In CLEF 2019 Labs and Workshops, Notebook Papers. CEUR-WS.org, 2019