We describe the second edition of the LongEval CLEF 2024 shared task. This lab evaluates
the temporal persistence of Information Retrieval (IR) systems and Text Classifiers. Task 1 …

The growing prevalence and rapid evolution of offensive language in social media amplify
the complexities of detection, particularly highlighting the challenges in identifying such …

The advancement of machine learning and symbolic approaches have underscored their
strengths and weaknesses in Natural Language Processing (NLP). While machine learning …

The use of abusive language online has become an increasingly pervasive problem that
damages both individuals and society, with effects ranging from psychological harm right …

This paper introduces the planned second LongEval Lab, part of the CLEF 2024 conference.
The aim of the lab's two tasks is to give researchers test data for addressing temporal …

Previous studies have highlighted the importance of vaccination as an effective strategy to
control the transmission of the COVID-19 virus. It is crucial for policymakers to have a …

LongEval-Retrieval is a Web document retrieval benchmark that focuses on continuous
retrieval evaluation. This test collection is intended to be used to study the temporal …

We examine how the language of online reviews has changed over the past 20 years. The
corpora we use for this analysis consist of online reviews, each of which is paired with a …

This report gives an overview of the system developed by Team DAM for Task 1 of the
LongEval Lab at CLEF 2024. The team members are students enrolled in the Computer …

In this work we investigate the hypothesis that enriching contextualized models using fine-
tuning tasks can improve theircapacity to detect lexical semantic change (LSC). We include …