What Twitter Data Tell Us about the Future?
Alina Landowska Marek Robak Maciej Skorski
Anticipation is a fundamental human cognitive ability that involves thinking
about and living towards the future. While language markers reflect
anticipatory thinking, research on anticipation from the perspective of natural
language processing is limited. This study aims to investigate the futures
projected by futurists on Twitter and explore the impact of language cues on
anticipatory thinking among social media users. We address the research
questions of what futures Twitter's futurists anticipate and share, and how
these anticipated futures can be modeled from social data. To investigate this,
we review related works on anticipation, discuss the influence of language
markers and prestigious individuals on anticipatory thinking, and present a
taxonomy system categorizing futures into "present futures" and "future
present". This research presents a compiled dataset of over 1 million publicly
shared tweets by future influencers and develops a scalable NLP pipeline using
SOTA models. The study identifies 15 topics from the LDA approach and 100
distinct topics from the BERTopic approach within the futurists' tweets. These
findings contribute to the research on topic modelling and provide insights
into the futures anticipated by Twitter's futurists. The research demonstrates
the futurists' language cues signals futures-in-the-making that enhance social
media users to anticipate their own scenarios and respond to them in present.
The fully open-sourced dataset, interactive analysis, and reproducible source
code are available for further exploration.