Examining the Impact of Social Media Functions and Algorithms on Emotion and General Well-Being (DSI-SRP)
This DSI-SRP fellowship funded Yixin Wang to work in the laboratory of Dr. Shilo Anders in the Department of Anesthesiology during the summer of 2022. Yixin is a senior with majors in Mathematics and Psychology.
This summer, Yixin and Dr. Andres’ laboratory focused on locating which social media platforms they wanted to investigate, analyzed social media usage motivations using factor analysis, principal component analysis, and k-means clustering analysis, and conducted a comprehensive literature review to launch the data collection in fall 2022. First, Yixin calculated the SMU frequency provided by VU students at two representative time stamps during the pandemic. She summarize the top 5 most frequently used social media among young adults during the pandemic based on our data: Instagram, Snapchat, Tiktok, Youtube, and Groupme. She focused on the first three platforms in the following emotion status monitoring based on their distinctive functions. Meanwhile, she utilized Colab and Jamovi to clean the data and conduct Principal Component Analysis, Exploratory Factor Analysis, and Clustering Analysis on our SMU Motivation variables. Based on the results, she decided to generalize her 18 motivation variables into four broader and more influential factors for further study. Yixin and Dr. Andres’ laboratory categorized young adult social media users into three main categories based on k-means clustering analysis. Finally, she drafted a more detailed study background and choose the appropriate method for monitoring users’ emotional status influenced by social media algorithms and functions. She anticipated combining ecological momentary assessment, account tracking, and daily retrospective journal to achieve this goal based on our research.
In addition to receiving support through a DSI-SRP fellowship, this project was supported and facilitated by the DSI Data Science Team through their regular summer workshops and demo sessions.