Name: Sentiment Analysis For Mental Health
Creator: Kaggle
License: http://opendatacommons.org/licenses/dbcl/1.0/

About this Dataset

Sentiment Analysis For Mental Health

This comprehensive dataset is a meticulously curated collection of mental health statuses tagged from various statements. The dataset amalgamates raw data from multiple sources, cleaned and compiled to create a robust resource for developing chatbots and performing sentiment analysis.

Data Source:

The dataset integrates information from the following Kaggle datasets:

Data Overview:

The dataset consists of statements tagged with one of the following seven mental health statuses:

Normal
Depression
Suicidal
Anxiety
Stress
Bi-Polar
Personality Disorder

Data Collection:

The data is sourced from diverse platforms including social media posts, Reddit posts, Twitter posts, and more. Each entry is tagged with a specific mental health status, making it an invaluable asset for:

Developing intelligent mental health chatbots.
Performing in-depth sentiment analysis.
Research and studies related to mental health trends.

Features:

unique_id: A unique identifier for each entry.
Statement: The textual data or post.
Mental Health Status: The tagged mental health status of the statement.

Usage:

This dataset is ideal for training machine learning models aimed at understanding and predicting mental health conditions based on textual data. It can be used in various applications such as:

Chatbot development for mental health support.
Sentiment analysis to gauge mental health trends.
Academic research on mental health patterns.

Acknowledgments:

This dataset was created by aggregating and cleaning data from various publicly available datasets on Kaggle. Special thanks to the original dataset creators for their contributions.

Tables

Combined Data

@kaggle.suchintikasarkar_sentiment_analysis_for_mental_health.combined_data

18.68 MB
53,043 rows
3 columns

CREATE TABLE combined_data (
  "unnamed_0" BIGINT  -- Unnamed: 0,
  "statement" VARCHAR,
  "status" VARCHAR
);