| Challenge: | ESTUDES de Sanidad: 20.1% of youngsters between 14 and 18 years old have gambled money online . ESTUDES: 2021: 17.9% of students who have gamble would be predisposed to gambling-related problems. |
| Approach: | This paper collects text from online Spanish-speaking communities and analyses it to detect gambling addiction problem. |
| Outcome: | The proposed corpus collects text from Spanish-speaking communities and analyzes it . it finds patterns in written language from frequent and infrequent users . 20.1% of youngsters between 14 and 18 years old have gambled money in person or online . |
Similar Papers
Analyzing Gambling Addictions: A Spanish Corpus for Understanding Pathological Behavior (2025.findings-emnlp)
Copied to clipboard
| Challenge: | a new study examines the interaction between natural language use and gambling disorders. |
| Approach: | They build a new corpus of sentences that are searched and compared using top-k pooling to form the assessment pools of sentences. |
| Outcome: | The proposed model is based on a new corpus of sentences in spanish . |
MentalRiskES: A New Corpus for Early Detection of Mental Disorders in Spanish (2024.lrec-main)
Copied to clipboard
Alba M. Mármol Romero, Adrián Moreno Muñoz, Flor Miriam Plaza-del-Arco, M. Dolores Molina González, María Teresa Martín Valdivia, L. Alfonso Ureña-López, Arturo Montejo Ráez
| Challenge: | Existing studies on the prevalence of mental disorders on the Web are limited to the English language. |
| Approach: | They propose to use user messages posted on Telegram groups to annotate the corpus for natural language processing and to conduct experiments on text classification and regression. |
| Outcome: | The proposed corpus contains over 1,300 subjects with more than 45,000 messages posted in different public Telegram groups. |
Abusive language in Spanish children and young teenager’s conversations: data preparation and short text classification with contextual word embeddings (2020.lrec-1)
Copied to clipboard
| Challenge: | Existing studies on how to automatically detect abusive short texts are gaining interest in the natural language processing community. |
| Approach: | They propose to use a contextual word embedding model to automatically detect abusive short texts for Spanish language. |
| Outcome: | The proposed model outperforms classical methods in the detection of abusive short texts for the spanish language. |
Searching Brazilian Twitter for Signs of Mental Health Issues (2020.lrec-1)
Copied to clipboard
| Challenge: | Existing resources are largely devoted to English NLP, and there is little support for these studies in under resourced languages. |
| Approach: | They propose to build a corpus in Brazilian Portuguese to support both the recognition of mental health issues and the temporal analysis of these illnesses. |
| Outcome: | The proposed corpus will support both the recognition of mental health issues and the temporal analysis of these illnesses in the Brazilian Portuguese language. |
RoBERTuito: a pre-trained language model for social media text in Spanish (2022.lrec-1)
Copied to clipboard
| Challenge: | Pre-trained language models have been used in many natural language processing tasks . some domain-specific models have shown to improve performance in some domains . however, for languages other than English, such models are not widely available . |
| Approach: | They present a pre-trained language model for user-generated text in Spanish . it is based on 500 million tweets and has some cross-lingual abilities . |
| Outcome: | The model outperforms models trained on over 500 million tweets on a benchmark in spanish and english. |
A Dataset for Multi-lingual Epidemiological Event Extraction (2020.lrec-1)
Copied to clipboard
| Challenge: | Using the Web, we propose a corpus for information extraction and text classification. |
| Approach: | They propose to use a corpus for information extraction and natural language processing (NLP) tasks such as text classification. |
| Outcome: | The proposed corpus can be used for information extraction and natural language processing tasks such as text classification. |
HAHA 2019 Dataset: A Corpus for Humor Analysis in Spanish (2020.lrec-1)
Copied to clipboard
| Challenge: | 30,000 Spanish tweets were crowd-annotated with humor value and funniness score . the corpus contains approximately 38.6% of humorous tweets with an average score of 2.04 in a scale from 1 to 5 for the humorous tweet. |
| Approach: | They develop a corpus of 30,000 Spanish tweets crowd-annotated with humor value and funniness score. |
| Outcome: | The results obtained from the 30,000 tweets in the Spanish language are encouraging. |
MultiSocial: Multilingual Benchmark of Machine-Generated Text Detection of Social-Media Texts (2025.acl-long)
Copied to clipboard
| Challenge: | Existing methods for detecting social-media texts are limited to the English language and longer texts are not easily recognisable by humans. |
| Approach: | They propose to use a multilingual and multi-platform dataset to compare machine-generated text detection methods in the social-media domain to compare them to human-written texts. |
| Outcome: | The proposed dataset contains 472,097 texts, of which about 58k are human-written and approximately the same amount is generated by each of 7 multilingual LLMs. |
Words are the Window to the Soul: Language-based User Representations for Fake News Detection (2020.coling-main)
Copied to clipboard
| Challenge: | Existing studies on fake news classification focus on textual content, but also social context in which news are consumed. |
| Approach: | They propose a model that creates representations of individuals on social media based only on the language they produce and uses them to detect fake news. |
| Outcome: | The proposed model exploits the relationship between language use and connections in the social graph to assess the presence of the Echo Chamber effect in the data. |
Making FETCH! Happen: Finding Emergent Dog Whistles Through Common Habitats (2025.acl-long)
Copied to clipboard
| Challenge: | Dog whistles are coded expressions with dual meanings that slip by content moderation filters . a new study finds that state-of-the-art systems fail to identify novel dog whistles . |
| Approach: | They propose a task to find novel dog whistles in massive social media corpora . they use a strong baseline system that combines vector databases and Large Language Models to identify new dog whistle. |
| Outcome: | The proposed system fails to identify dog whistles across three social media cases . it combines vector databases and Large Language Models to efficiently and effectively identify new dog whistle expressions. |