Amplification to Synthesis: A Comparative Analysis of Cognitive Operations Before and After Generative AI
Liz Cho, Dongwook Yoon

TL;DR
This study compares behavioral and linguistic patterns in social media data from the 2016 and 2024 US elections, revealing significant shifts likely due to generative AI's influence on cognitive operations.
Contribution
It provides an empirical analysis of how generative AI has altered online coordination and content creation patterns in political discourse.
Findings
Original content increased from 59% to 93% in 2024.
Lexical overlap dropped from 0.99 to 0.27, indicating diverse expressions.
Shift from cross-semantic synchrony to narrative-focused co-occurrence.
Abstract
Cognitive operations are a rising concern in the geopolitical sphere, a quiet yet rigorous fight for public perception and decision making. While such operations have been extensively studied in the context of bot-driven amplification, the emergence of generative AI introduces a new set of capabilities that may have fundamentally altered how these operations are designed and executed. The possible evolution of cognitive operation via generative AI puts nation states vulnerable without proper mitigation strategies. To address this, we compared behavioral and linguistic coordination patterns in X (formerly Twitter) datasets from the 2016 and 2024 U.S. presidential elections. Utilizing a combined corpus of over 133,000 posts, we applied post-type distribution, semantic clustering, temporal synchrony analysis, and Jaccard-based lexical overlap measures. Findings suggest that the 2024 corpus…
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