Predictive Algorithms and the Erosion of Autonomy: How Social Media Anticipates Human Expression

Author(s)	Kush Mittal
Country	India
Abstract	Social media platforms have transitioned from passive communication spaces to predictive environments that anticipate user behavior in real time. This research examines how platforms integrate language models and behavioral data to generate suggestions before users finish typing. By drawing on existing literature, the study highlights how predictive algorithms use transformer-based natural language processing, sentiment analysis, and real-time behavioral monitoring to shape communication patterns. Findings suggest that these systems may increase convenience and engagement, but they also contribute to diminished autonomy, reduced creativity, and growing dependence on automated suggestions. Predictive tools influence emotional expression, reinforce linguistic biases, and operate through opaque “black-box” mechanisms that limit user awareness of data extraction practices. These insights underline the need for transparency, ethical design, and regulatory protection of anticipatory data. The study emphasizes that while predictive features can support communication, they must be managed carefully to preserve user agency and maintain authenticity in digital expression.
Keywords	Keywords: predictive algorithms, NLP, personalization, autonomy, social media behavior, algorithmic influence
Field	Business Administration
Published In	Volume 7, Issue 6, November-December 2025
Published On	2025-11-16
DOI	https://doi.org/10.36948/ijfmr.2025.v07i06.60267

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