Unraveling Sentiment Threads: An Analysis of Comment Sentiment and User Participation in Scratch Project Creation

Investigating the Impact of Comment Sentiment on the Creator's Activity on a Social Coding Platform

Bachelor thesis (2024)

Authors

G.J. Schaap Electrical Engineering, Mathematics and Computer Science

Contributors

E.A. Aivaloglou Web Information Systems - EEMCS (supervisor 1)
M.S. Pera Web Information Systems - EEMCS (supervisor 1)
Jorge Martinez (supervisor 2)
Faculty
Electrical Engineering, Mathematics and Computer Science
Copyright: © 2024 Gert-Jan Schaap
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Published Date

02-02-2024

Language

English

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Faculty

Electrical Engineering, Mathematics and Computer Science

Abstract

Although existing work demonstrates that the usage of Scratch strengthens programming skills, little is known about the effect of children encouraging or criticizing each other when programming on the development of their programming skills. To address this gap, we conducted a data analysis to reveal the correlation (or lack thereof) between the sentiment of comments on a Scratch project and the creator's inclination to continue producing projects.

In particular, using a known dataset of Scratch projects, which we enriched with new projects, we examined several independent variables that capture sentiment on comments from different perspectives, e.g. the absolute or relative number of comments with a particular sentiment score that a user receives, or the ratio of comments that fall in a certain category. We also examined several dependent variables that capture the creator's inclination to continue producing projects, e.g. the number of projects they create or the total time that they are active on the platform.

The results of our experiments reveal that the absolute and relative number of comments with a specific sentiment score given to a user have a low correlation to the time that a user is active on the platform. Additionally, the ratio of the number of positive and negative comments over the total number of comments given to a user has a low correlation to the time that a user is active on the platform. Finally, the number of comments that a user receives has a low correlation to the number of projects a user creates.