
International Journal For Multidisciplinary Research
E-ISSN: 2582-2160
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A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 7 Issue 1
January-February 2025
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The Role of Social Media Sentiment in Predicting Stock Returns: An Econometric and Text Analytics Approach
Author(s) | Rajmeet Singh |
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Country | India |
Abstract | This study investigates the role of social media sentiment as a predictor for stock returns, employing an econometric and text analytics approach. As social media platforms have proliferated, they have transformed into significant sources of real-time sentiment that can influence market behavior. Traditional stock prediction models primarily rely on historical data and financial metrics, often overlooking the impact of public sentiment expressed on platforms such as Twitter and Reddit. This research addresses the gap by exploring how social media sentiment can augment existing financial indicators to enhance predictive accuracy. Utilizing econometric models alongside sentiment analysis techniques, the study identifies key sentiment indicators and tests their correlation with stock returns. The findings suggest that integrating social media sentiment into financial analysis not only provides actionable insights for traders but also refines long-term investment strategies for institutional investors. By demonstrating the incremental value of this alternative data source, this research contributes to the evolving landscape of financial modeling in the digital age. |
Keywords | social media sentiment, stock returns, econometrics, text analytics, financial modeling |
Field | Mathematics > Economy / Commerce |
Published In | Volume 7, Issue 1, January-February 2025 |
Published On | 2025-01-20 |
Cite This | The Role of Social Media Sentiment in Predicting Stock Returns: An Econometric and Text Analytics Approach - Rajmeet Singh - IJFMR Volume 7, Issue 1, January-February 2025. DOI 10.36948/ijfmr.2025.v07i01.35498 |
DOI | https://doi.org/10.36948/ijfmr.2025.v07i01.35498 |
Short DOI | https://doi.org/g82gms |
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E-ISSN 2582-2160

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