Depression: Twitter Dataset + Feature Extraction
This dataset contains 20,000 labelled English tweets of depressed and non-depressed users. The data is collected using the Twitter API and includes feature extraction techniques such as topic modelling and emoji sentiment analysis. It is designed for mental health classification at the tweet level.
Pengenalan Terperinci
The Depression: Twitter Dataset + Feature Extraction is a valuable resource for researchers and developers working on mental health classification. It includes 20,000 labelled English tweets, collected using the Twitter API. The dataset provides feature extraction techniques such as topic modelling and emoji sentiment analysis, making it suitable for various machine learning and data analysis projects. The data is essential for understanding and predicting mental health conditions from social media content.
LagiSet data
SmartFlowAI/EmoLLM: Psychology LLM、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2
Psychology LLM、LLM、The Big Model of Mental Health、Finetune、InternLM2、InternLM2.5、Qwen、ChatGLM、Baichuan、DeepSeek、Mixtral、LLama3、GLM4、Qwen2 - SmartFlowAI/EmoLLM
Psychology Therapy Dataset- halilxibrahim/psychology-therapy
Dataset Card for Psychology Therapy Dataset : This dataset card aims to provide information about a dataset focused on psychology therapy conversations. Language(s) (NLP): Turkish (tr)
HuggingFaceFW/fineweb-2
FineWeb-2 is a dataset of over 15 trillion tokens of cleaned and deduplicated English web data from CommonCrawl. This is the second iteration of the popular 🍷 FineWeb dataset, bringing high quality pretraining data to over 1000 🗣️ languages.The 🥂 FineWeb2 dataset is fully reproducible, available under the permissive ODC-By 1.0 license and extensively validated through hundreds of ablation experiments.In particular, on the set of 9 diverse languages we used to guide our processing decisions, 🥂 FineWeb2 outperforms other popular pretraining datasets covering multiple languages (such as CC-100, mC4, CulturaX or HPLT, while being substantially larger) and, in some cases, even performs better than some datasets specifically curated for a single one of these languages, in our diverse set of carefully selected evaluation tasks: FineTasks.