Abstract Analysis of subjective texts like offensive content or hate speech is a great
challenge, especially regarding annotation process. Most of current annotation procedures …

In this article we present an extended version of PolEmo–a corpus of consumer reviews from
4 domains: medicine, hotels, products and school. Current version (PolEmo 2.0) contains …

In this article, we present the results of our experiments on sentiment and emotion
recognition for English and Polish texts, aiming to work in the context of a therapeutic …

Since the Internet is flooded with hate, it is one of the main tasks for NLP experts to master
automated online content moderation. However, advancements in this field require …

Exposure to hate speech (HS) leads to desensitization of listeners. Yet, most evidence of this
process has been obtained using self‐report measures. In this paper, we examined …

We introduce the first dataset of harmful and offensive language collected from the Polish
Internet. This dataset was meticulously curated to facilitate the exploration of harmful online …

The automatic detection of aggressive language is a difficult challenge. Currently, three
datasets are available in Polish, enabling the training of machine learning models to …

The goal of the paper is to present a Simplified Offensive Language (SOL) Taxonomy, its
application and testing in the Second Annotation Campaign conducted between March-May …

Since the Internet is flooded with hate, it is one of the main tasks for NLP experts to master
automated online content moderation. However, advancements in this field require …

Abstract Aspect-Sentiment Triplet Extraction (ASTE) is one of the most challenging and
complex tasks in sentiment analysis. It concerns the construction of triplets that contain an …