Overview of PAN 2021: Authorship Verification, Profiling Hate Speech Spreaders on Twitter, and Style Change Detection
| Autor: | Magdalena Wolska, Eva Zangerle, Matti Wiegmann, Enrique Manjavacas, Francisco Rangel, Maximilian Mayerl, Paolo Rosso, Efstathios Stamatatos, Gretel Liz De la Peña Sarracén, Martin Potthast, Berta Chulvi, Mike Kestemont, Ilia Markov, Janek Bevendorff, Benno Stein |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Computer. Automation
Computer science Profiling hate speech spreaders on Twitter Authorship verification PAN Lab Clef Style (sociolinguistics) World Wide Web Benchmark (surveying) Stylometry Profiling (information science) Objective evaluation Style change detection LENGUAJES Y SISTEMAS INFORMATICOS Change detection |
| Zdroj: | Advances in Information Retrieval: 43rd European Conference on IR Research, ECIR 2021, Virtual Event, March 28 – April 1, 2021, Proceedings, Part II Lecture Notes in Computer Science ISBN: 9783030852504 CLEF |
| Popis: | [EN] The paper gives a brief overview of the three shared tasks to be organized at the PAN 2021 lab on digital text forensics and stylometry hosted at the CLEF conference. The tasks include authorship verification across domains, author profiling for hate speech spreaders, and style change detection for multi-author documents. In part the tasks are new and in part they continue and advance past shared tasks, with the overall goal of advancing the state of the art, providing for an objective evaluation on newly developed benchmark datasets. The work of the researchers from Universitat Politecnica de Valencia was partially funded by the Spanish MICINN under the project MISMISFAKEnHATE on MISinformation and MIScommunication in social media: FAKE news and HATE speech (PGC2018-096212-B-C31), and by the Generalitat Valenciana under the project DeepPattern (PROMETEO/2019/121). |
| Databáze: | OpenAIRE |
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