Social Media and Mental Health

This dataset was originally collected for a data science and machine learning project that aimed at investigating the potential correlation between the amount of time an individual spends on social media and the impact it has on their mental health.

The project involves conducting a survey to collect data, organizing the data, and using machine learning techniques to create a predictive model that can determine whether a person should seek professional help based on their answers to the survey questions.

This project was completed as part of a Statistics course at a university, and the team is currently in the process of writing a report and completing a paper that summarizes and discusses the findings in relation to other research on the topic.

The following is the Google Colab link to the project, done on Jupyter Notebook -

[https://colab.research.google.com/drive/1p7P6lL1QUw1TtyUD1odNR4M6TVJK7IYN](url)

The following is the GitHub Repository of the project -

[https://github.com/daerkns/social-media-and-mental-health](url)

Libraries used for the Project -

Pandas
Numpy
Matplotlib
Seaborn
Sci-kit Learn

该数据集最初是为一项旨在探究个体在社交媒体上花费时间与对其心理健康影响之间潜在相关性的数据科学和机器学习项目所收集。该项目包括开展调查以收集数据、整理数据以及运用机器学习技术构建预测模型，该模型可根据调查问题的答案判断个人是否需要寻求专业帮助。该研究作为大学统计学课程的一部分完成，团队目前正在撰写报告并撰写论文，以总结和讨论研究结果，并将其与其他关于该主题的研究成果进行对比。以下为该项目在 Jupyter Notebook 上的 Google Colab 链接 - [https://colab.research.google.com/drive/1p7P6lL1QUw1TtyUD1odNR4M6TVJK7IYN](url)，以及项目的 GitHub 仓库链接 - [https://github.com/daerkns/social-media-and-mental-health](url)。项目所使用的库包括 Pandas、Numpy、Matplotlib、Seaborn 和 Sci-kit Learn。

搜集汇总

背景与挑战

背景概述

该数据集收集了关于社交媒体使用习惯和心理健康状况的调查数据，包含21个字段，主要用于研究两者之间的相关性。数据集来自大学统计课程项目，已应用于机器学习建模和分析。