Samuel Gandang Gunanto
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Analisis Sentimen Publik terhadap Pengaruh Kecerdasan Buatan pada Produksi Animasi Berbasis Data Media Sosial X Menggunakan Metode Lexicon-Based VADER Ginanjar Setyo Nugroho; Troy; Samuel Gandang Gunanto; Venus Khesya Tyasmara
Arcitech: Journal of Computer Science and Artificial Intelligence Vol. 6 No. 1 (2026): June 2026
Publisher : Institut Agama Islam Negeri (IAIN) Curup

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29240/arcitech.v6i1.16391

Abstract

Artificial Intelligence (AI) has emerged as a primary driver in various industries, yet its integration into animation production faces mixed reactions, creating a dualism between innovation and professional sustainability. Despite growing research on AI's technical efficiency in animation, there remains a significant gap in understanding public sentiment toward its broader impacts, particularly through large-scale social media analysis. This study aims to address this gap by analyzing public sentiment regarding the impact of AI on animation production. Using the Lexicon-Based VADER method, this study collected and analyzed 1,545 tweets from the social media platform X (formerly Twitter) during the period from June 1 to 30, 2025. The results showed a dominance of positive sentiment with 935 tweets, 385 neutral tweets, and 225 negative tweets. The results of this study are expected to provide insights, reference for decision-making, and further exploration. These findings not only highlight widespread support for AI but also underscore the need for ethical frameworks to mitigate job displacement risks, offering actionable implications for industry stakeholders to foster balanced human-AI collaboration in creative fields.