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

TL;DR

This study analyzes social media discourse on technological challenges using topic modeling and sentiment analysis, revealing predominantly positive emotions and optimism among key opinion leaders shaping future technological visions.

Contribution

It introduces a novel combination of BERTopic, sentiment, and emotion analysis on a large Twitter dataset to understand anticipatory discourse on technology.

Findings

Positive sentiment outweighs negative sentiment.

Hope emotions are significantly higher than Anxiety.

Key opinion leaders emphasize optimism and benefits.

Abstract

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.