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Found 18 papers, 4 papers with code
Abuse is Contextual, What about NLP? The Role of Context in Abusive Language Annotation and Detection
We first re-annotate part of a widely used dataset for abusive language detection in English in two conditions, i. e. with and without context.
Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators’ Disagreement
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
FBK-DH at SemEval-2020 Task 12: Using Multi-channel BERT for Multilingual Offensive Language Detection
In this paper we present our submission to sub-task A at SemEval 2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval2).
RAMBLE ON: Tracing Movements of Popular Historical Figures
We present RAMBLE ON, an application integrating a pipeline for frame-based information extraction and an interface to track and display movement trajectories.
Topic-Based Agreement and Disagreement in US Electoral Manifestos
We present a topic-based analysis of agreement and disagreement in political manifestos, which relies on a new method for topic detection based on key concept clustering.
Creating a WhatsApp Dataset to Study Pre-teen Cyberbullying
Although WhatsApp is used by teenagers as one major channel of cyberbullying, such interactions remain invisible due to the app privacy policies that do not allow ex-post data collection.
Agreement and Disagreement: Comparison of Points of View in the Political Domain
The automated comparison of points of view between two politicians is a very challenging task, due not only to the lack of annotated resources, but also to the different dimensions participating to the definition of agreement and disagreement.
A SICK cure for the evaluation of compositional distributional semantic models
Shared and internationally recognized benchmarks are fundamental for the development of any computational system.
``Who was Pietro Badoglio?'' Towards a QA system for Italian History
This paper presents QUANDHO (QUestion ANswering Data for italian HistOry), an Italian question answering dataset created to cover a specific domain, i. e. the history of Italy in the first half of the XX century.
A System to Monitor Cyberbullying based on Message Classification and Social Network Analysis
Social media platforms like Twitter and Instagram face a surge in cyberbullying phenomena against young users and need to develop scalable computational methods to limit the negative consequences of this kind of abuse.
Creating a Multimodal Dataset of Images and Text to Study Abusive Language
We find that users judge the same images in different ways, although the presence of a person in the picture increases the probability to get an offensive comment.
Hybrid Emoji-Based Masked Language Models for Zero-Shot Abusive Language Detection
Recent studies have demonstrated the effectiveness of cross-lingual language model pre-training on different NLP tasks, such as natural language inference and machine translation.
Agreeing to Disagree: Annotating Offensive Language Datasets with Annotators' Disagreement
Since state-of-the-art approaches to offensive language detection rely on supervised learning, it is crucial to quickly adapt them to the continuously evolving scenario of social media.
FrameNet-like Annotation of Olfactory Information in Texts
Although olfactory references play a crucial role in our cultural memory, only few works in NLP have tried to capture them from a computational perspective.
A Multilingual Benchmark to Capture Olfactory Situations over Time
We present a benchmark in six European languages containing manually annotated information about olfactory situations and events following a FrameNet-like approach.
Building a Multilingual Taxonomy of Olfactory Terms with Timestamps
Olfactory references play a crucial role in our memory and, more generally, in our experiences, since researchers have shown that smell is the sense that is most directly connected with emotions.
BERToldo, the Historical BERT for Italian
This has led to the creation of BERT-like models for different languages trained with digital repositories from the past.
