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Analyzing Brand Sentiment Around Apple’s 2020 Product Launch: A Reddit-Based Study of Marketing Campaign Impact

Submitted:

05 December 2025

Posted:

10 December 2025

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Abstract
Social media platforms have become critical spaces where consumers and investors publicly react to major corporate events. These online reactions provide rich text data for analyzing brand sentiment and evaluating marketing campaigns. This study examines how sentiment toward Apple changed the company’s 2020 product launch within Reddit finance communities. Using a dataset of 297,533 Reddit comments mentioning Apple’s ticker (“AAPL”) posted between November 2016 and October 2021 in finance-related subreddits, comments were labeled as occurring before or after the September 11, 2020, launch. Sentiment was measured using VADER, a lexicon‐ and rule‐based sentiment analyzer optimized for social media text (Hutto & Gilbert, 2014). Descriptive statistics, correlation analyses, and independent‐samples t tests compared sentiment and engagement (upvotes) across periods and explored relationships among sentiment, text length, and upvotes. Overall sentiment was slightly positive (M = 0.13), with a small but statistically significant increase after the launch (Before: M = 0.12; After: M = 0.14). Upvotes did not differ meaningfully by period. Correlations showed that stronger sentiment was associated with longer comments but was essentially unrelated to upvotes. As an exploratory extension, a small labeled subset of comments was used to pilot fine‐tuning a transformer-based model with the Unsloth framework, building on evidence that domain-specific transformers such as FinBERT outperform lexicon-based methods on financial text (Araci, 2019). The findings suggest that Apple’s 2020 launch modestly improved conversational tone in Reddit finance discussions without changing engagement, and they highlight the value of combining fast lexicon methods with modern transformers for campaign evaluation.
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Copyright: This open access article is published under a Creative Commons CC BY 4.0 license, which permit the free download, distribution, and reuse, provided that the author and preprint are cited in any reuse.
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