Reproduce “Mapping Technological Futures: Anticipatory Discourse Through Text Mining” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Maciej Skorski, Alina Landowska, Krzysztof Rajda
Researchers analyzed 1.5 million social media posts from 400 Key Opinion Leaders (KOLs) on X (formerly Twitter) to map anticipatory discourse about technological futures. The study utilized BERTopic modeling and refined Plutchik-based emotion calculations to identify dominant themes and emotional landscapes, revealing that Hope significantly outweighed Anxiety (p = 5.58 × 10⁻⁷) and Optimism surpassed Pessimism towards emerging technologies like AI.
Key insights
- KOLs exhibit concentrated influence, with the top 10 generating 13% of the corpus and dominating 49% of discussions across 22 topics, demonstrating distinct specialization.
- Anticipation is a prevalent emotion in technological discourse, showing a moderate positive correlation with Trust (0.455), a weak positive correlation with Fear (0.217), and a moderate negative correlation with Sadness (-0.353).
- KOLs engage in both "present futures" (framing technologies as tangible solutions) and "future presents" (exploring speculative societal impacts and ethical dilemmas), navigating between current visions and long-term consequences.
Summary by alphaXiv.
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.