AICLSIAPJul 20, 2024

Mapping the Technological Future: A Topic, Sentiment, and Emotion Analysis in Social Media Discourse

arXiv:2407.17522v11 citationsh-index: 4
Originality Synthesis-oriented
AI Analysis

This provides insights into public discourse on technological uncertainty for researchers and policymakers, but it is incremental as it applies existing methods to new social media data.

The study analyzed 1.5 million tweets from 2021-2023 to identify tech-driven futures and emotions, finding positive sentiment and 'Hope' scores about 10.33% higher than 'Anxiety' among key opinion leaders.

People worldwide are currently confronted with a number of technological challenges, which act as a potent source of uncertainty. The uncertainty arising from the volatility and unpredictability of technology (such as AI) and its potential consequences is widely discussed on social media. This study uses BERTopic modelling along with sentiment and emotion analysis on 1.5 million tweets from 2021 to 2023 to identify anticipated tech-driven futures and capture the emotions communicated by 400 key opinion leaders (KOLs). Findings indicate positive sentiment significantly outweighs negative, with a prevailing dominance of positive anticipatory emotions. Specifically, the 'Hope' score is approximately 10.33\% higher than the median 'Anxiety' score. KOLs emphasize 'Optimism' and benefits over 'Pessimism' and challenges. The study emphasizes the important role KOLs play in shaping future visions through anticipatory discourse and emotional tone during times of technological uncertainty.

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