Cyberbullying behaviors manifest uniquely in different regions, shaped strongly by local slang, dialectal expressions, and cultural context. Code-mixed Chinese–English colloquial language (Cantonese) is commonly used in Hong Kong, Macau, and pa...
Recent years have seen increased interest in code-mixing from a usage-based perspective. In usage-based approaches to monolingual language acquisition, a number of methods have been developed that allow for detecting patterns from usage data. In this...
Singlish is a code-mixed creole formed from English and multiple Asian languages and dialects, predominantly spoken in Singapore. Translation of Singlish to standard UK English broadens comprehension of the creole and supports downstream analyses suc...
Usage-based approaches have become increasingly important in research on language acquisition and recently also in bilingual first language acquisition. Lexically specific patterns, such as What’s this? and frame-and-slot patterns, such as [I w...
Due to the increasing reliance on social network platforms in recent years, hate speech has risen significantly among online users. Government and social media platforms face the challenging responsibility of controlling, detecting, and removing mass...
In both child and adult Cantonese, code-mixing is used productively. We focus on the insertion of English verbs into Cantonese utterances. Data from nine simultaneous bilingual children in the Hong Kong Bilingual Child Language Corpus are analyzed. C...
The widespread use of social media has led to a rise in online bullying and abusive language. Huge amounts of content are created on social media daily, creating a challenge for platforms to manually detect and remove offensive posts, making automate...
In the evolving cybersecurity landscape, detecting Thai-English code-mixed malicious scripts within high-trust domains such as governmental and academic portals presents a significant defensive challenge. While Transformer-based architectures excel i...
Depression is a serious mental health disorder affecting cognition, emotions, and behavior. It impacts over 300 million people globally, with mental health care costs exceeding $1 trillion annually. Traditional diagnostic methods are often expensive,...
Modern Standard Arabic (MSA) and the many regional dialects differ substantially in vocabulary, morphology, and pragmatic usage. Most available annotated resources are in MSA, and zero-shot transfer from MSA to dialectal tasks suffers a large perform...
Bilingual speakers often engage in code-switching, that is the use of lexical items and grammatical features from two languages in one sentence. Malaysia is a particularly interesting context for the study of code-switching because Malay-English code...
YouTube is a boon, and through it people can educate, entertain, and express themselves about various topics. YouTube India currently has millions of active users. As there are millions of active users it can be understood that the data present on th...
The study investigated word recognition during neural activation in monolinguals and bilinguals. We specifically examined word retrieval and blood-oxygenation changes in the prefrontal cortex during a code-mixed word recognition task. Participants co...
This Special Issue comprises six original studies that explore the interface between sociolinguistics and music, offering new insights into how language is stylized and perceived in English, Spanish, and code-mixed performance [...]
The increasing use of Arabic and Urdu on social media platforms, particularly Twitter, has created a growing need for robust Named Entity Recognition (NER) systems capable of handling noisy, informal, and code-mixed content. However, both languages r...
This paper presents a qualitative analysis of multilingual past-tense constructions produced by Italian–Peruvian speakers in Turin (Italy). Drawing on data from the Stra-ParlaTO corpus, the study aims both to describe the multilingual practices...
Augmenting the author’s prior research on lyrical code-switching, as presented in Picone, “Artistic Codemixing”, published in 2002, various conceptual frameworks are made explicit, namely the enlistment of multimodal and intertextua...
This study investigates the beliefs about multilingualism and the multilingual language use of multilingual children living in the Netherlands, a highly diverse and multilingual society. We interviewed 26 8- to 12-year-old primary school children wit...
The digital transformation of tourism has turned traveler reviews into a continuously expanding record of what visitors value, yet this evidence is fragmented across platforms and languages and is usually reduced to star ratings that obscure the unde...
With the rapid expansion of social media, detecting offensive language has become critically important for healthy online interactions. This poses a considerable challenge for low-resource languages such as Roman Urdu which are widely spoken on platf...
This study investigated family language policies (FLP) in the current context of the Macao Special Administrative Region (Macao SAR). It explored family language ideologies, management strategies, and intergenerational practices through questionnaire...
Sentiment classification in under-resourced languages remains challenging because of scarce annotated corpora, linguistic complexity, and computational constraints. Indian regional language Malayalam further intensifies these challenges through its a...
Roman Urdu hate and offensive language detection is difficult because informal social-media posts combine non-standard spelling, code-mixing, local abusive expressions, and severe label imbalance. Existing transformer-based detectors improve contextu...
Thai sentiment analysis on social media remains challenging due to the lack of explicit word boundaries, informal expressions, code-mixing, short text length, and severe class imbalance, particularly in the WISESIGHT benchmark dataset. Although trans...
Thisstudy introduces a new model for detecting insults in Roman Urdu, filling an important gap in natural language processing (NLP) for low-resource languages. The transliterated nature of Roman Urdu also poses specific challenges from a computationa...
Fairness audits of hate-speech classifiers are typically performed at a single annotation budget, leaving a basic question unanswered: how much labeled data does a trustworthy fairness audit require? We introduce ABFR (Annotation-Budget Fairness Reli...