Welcome to our Collaborative Data Science project, a part of the Emerging Talent program. For many of us, this project is our first foray into the field of data science. Our primary objective is to learn effective collaboration despite facing challenges such as differing time zones and remote work, all while utilizing a variety of tools. Additionally, we aim to explore the synergy between data science methodologies and domain expertise to uncover new insights. Our ultimate goal is to translate these insights into practical real-world solutions.
Our team is made up of individuals from diverse backgrounds, each with varying levels of exposure to data and data analysis. We've embraced this diversity to create a dynamic learning and coordination experience, striving to learn from one another and enhance our skills collectively.
Social media platforms have transformed the way we connect, communicate, and consume information. While they offer opportunities for virtual socialization and networking, they also come with potential risks to mental health, including issues such as cyberbullying, social media addiction, and negative self-comparison. Our project aims to explore the relationship between social media usage and mental health outcomes, contributing to a better understanding of this complex issue.
Our project seeks to investigate how time spent on social media platforms correlates with various mental health indicators. By analyzing a dataset collected through a survey, we aim to uncover insights into the potential impact of social media on mental well-being.
With the widespread use of social media globally, concerns have arisen regarding its potential effects on mental health, particularly among younger demographics. Our project aims to address these concerns by examining the relationship between social media usage and mental health outcomes.
We collected our dataset through a survey conducted from 04/18/2022 to 11/12/2022. The dataset includes responses from individuals regarding their social media usage habits and self-reported mental health indicators.
To assess the impact of social media on mental health, we considered various factors such as occupation status, age, gender, and specific social media behaviors. Our analysis focused on identifying correlations between these variables and mental health indicators.
Our analysis revealed moderate correlations between certain social media behaviors, such as feeling restless without social media and getting easily distracted by it, and mental health indicators like difficulty concentrating. However, the average time spent on social media per day showed a low correlation with mental health problems.
While our findings suggest a correlation between specific social media behaviors and mental health outcomes, further research is needed to better understand these relationships. By acknowledging the potential impact of social media on mental health, we can work towards promoting healthier online habits and supporting mental well-being in the digital age.
Our target audience for this project is composed of social media users, with a particular focus on individuals aged 12-41. This age group constitutes 87% of the participants included in our data analysis.
What better platform exists to engage with social media users than on social media itself? Therefore, we intend to disseminate memes and reels across various social media platforms in a humorous manner to showcase our project findings.
MIT License.