Tokenization is an important text preprocessing step to prepare input tokens for deep
language models. WordPiece and BPE are de facto methods employed by important …

Named entity recognition aims to detect pre-determined entity types in unstructured text.
There is a limited number of studies on this task for low-resource languages such as Turkish …

Hate Speech encompasses different forms of trolling, bullying, harassment, and threats
directed against specific individuals or groups. This phenomena is mainly expressed on …

Hate speech has unfortunately become a significant phenomenon on social media
platforms, and it can cover various topics (misogyny, sexism, racism, xenophobia, etc.) and …

Hate speech represents a pervasive and detrimental form of online discourse, often
manifested through an array of slurs, from hateful tweets to defamatory posts. As such …

Text-embedded images can serve as a means of spreading hate speech, propaganda, and
extremist beliefs. Throughout the Russia-Ukraine war, both opposing factions heavily relied …

Social media is awash with hateful content, much of which is often veiled with linguistic and
topical diversity. The benchmark datasets used for hate speech detection do not account for …

This paper presents a comprehensive survey of corpora and lexical resources available for
Turkish. We review a broad range of resources, focusing on the ones that are publicly …

The use of social media during election campaigns has become increasingly popular.
However, the unbridled nature of online discourse can lead to the propagation of hate …

This paper compares different pre-trained and fine-tuned large language models (LLMs) for
hate speech detection. Our research underscores challenges in LLMs' cross-domain validity …