The Technological Bridge: R Programming’s Utility in Converting Social Media Data for Quantitative Financial Analysis
This study explores whether R programming can transform unstructured qualitative social media data into a quantitative format suitable for econometric modelling. It specifically examines how elements such as text, emojis, and sentiment from Reddit and X (formerly Twitter) can be converted into varia...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2025-06-01
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| Series: | Economics and Culture |
| Subjects: | |
| Online Access: | https://doi.org/10.2478/jec-2025-0006 |
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| Summary: | This study explores whether R programming can transform unstructured qualitative social media data into a quantitative format suitable for econometric modelling. It specifically examines how elements such as text, emojis, and sentiment from Reddit and X (formerly Twitter) can be converted into variables for regression analysis. With the aim to enhance the predictive power of traditional financial models using alternative data sources, the paper outlines comprehensive guidelines with specific technical steps, from scripting an API to extracting data from Reddit and X, through cleaning and tokenising to incorporating the data into regression models using R programming. The study addresses the growing need in financial economics to incorporate alternative data streams by offering a structured, replicable process for transforming high-volume, unstructured online content into statistically valid variables, thereby bridging the gap between qualitative market sentiment and quantitative modelling. |
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| ISSN: | 2256-0173 |