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20132022
most citedSemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)

16 citations · 52 across the 9 of their papers we have counts for

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cs.CL2022

Bridging the Domain Gap for Stance Detection for the Zulu language

Gcinizwe Dlamini, Imad Eddine Ibrahim Bekkouch, Adil Khan +1

Misinformation has become a major concern in recent last years given its spread across our information sources. In the past years, many NLP tasks have been introduced in this area,…

cs.CL20211 cited

Optimal Size-Performance Tradeoffs: Weighing PoS Tagger Models

Magnus Jacobsen, Mikkel H. Sørensen, Leon Derczynski

Improvement in machine learning-based NLP performance are often presented with bigger models and more complex code. This presents a trade-off: better scores come at the cost of lar…

cs.CL202016 cited

SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)

Marcos Zampieri, Preslav Nakov, Sara Rosenthal +6

We present the results and main findings of SemEval-2020 Task 12 on Multilingual Offensive Language Identification in Social Media (OffensEval 2020). The task involves three subtas…

cs.CL20206 cited

The Rumour Mill: Making the Spread of Misinformation Explicit and Tangible

Nanna Inie, Jeanette Falk Olesen, Leon Derczynski

Misinformation spread presents a technological and social threat to society. With the advance of AI-based language models, automatically generated texts have become difficult to id…

cs.CL2019

Simple Natural Language Processing Tools for Danish

Leon Derczynski

This technical note describes a set of baseline tools for automatic processing of Danish text. The tools are machine-learning based, using natural language processing models traine…

cs.CL2018

Stance Prediction for Russian: Data and Analysis

Nikita Lozhnikov, Leon Derczynski, Manuel Mazzara

Stance detection is a critical component of rumour and fake news identification. It involves the extraction of the stance a particular author takes related to a given claim, both e…