Sentiment and Presentiment in Twitter: Do Trends in Collective Mood "Feel the Future"?
📄 Original study ↗📌 Appears in:
Plain English Summary
Can the collective mood of millions of Twitter users sense bad things before they happen? This study analyzed 13 years of daily mood scores from tweets in 10 languages before 83 surprise tragedies like terrorist attacks and mass shootings. Across all 10 languages, mood consistently dipped in the two weeks before events. The combined result was highly significant (p = 0.001), meaning pure chance is very unlikely. Removing English (used to build the method) and retesting only the remaining 9 languages gave an even stronger result. First-ever test of "collective presentiment" (group-level gut feeling about the future) outside a lab, using publicly verifiable data.
Research Notes
First large-scale observational test of collective presentiment using public social media data. Bridges the individual psychophysiological presentiment literature (Mossbridge 2012, Duggan 2018) with GCP-style collective-mind research. Unique for using 13 years of 10-language Twitter sentiment as a publicly verifiable, non-laboratory dataset. The 9-language replication subset (excluding the development language English) yielded Stouffer z = -3.229, p = 0.0006, strengthening the findings.
Tests whether daily Twitter sentiment data in 10 languages shows anticipatory declines before unpredictable negative world events (terrorism, mass shootings, unexpected celebrity deaths). Thirteen years of hedonometer.org sentiment data (2009-2023) were filtered through a four-step process to identify 83 unpredictable negative events. Ensemble averages of sentiment from 14 to 2 days before each event were analyzed via linear regression slopes corrected with circular-shift permutation testing. All 10 languages showed negative slopes; combined Stouffer z = -3.087, p = 0.001, suggesting a form of population-scale collective presentiment.
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Cites
- Effects of Mass Consciousness: Changes in Random Data During Global Events — Nelson, R.D (2011)
- Predictive Physiological Anticipation Preceding Seemingly Unpredictable Stimuli: A Meta-Analysis — Mossbridge, Julia (2012)
- Predicting the Unpredictable: Critical Analysis and Practical Implications of Predictive Anticipatory Activity — Mossbridge, Julia A (2014)
- Predictive Physiological Anticipation Preceding Seemingly Unpredictable Stimuli: An Update of Mossbridge et al.'s Meta-Analysis — Duggan, Michael (2018)
- Feeling the Future: Experimental Evidence for Anomalous Retroactive Influences on Cognition and Affect — Bem, Daryl J (2011)
- Feeling the Future: A Meta-Analysis of 90 Experiments on the Anomalous Anticipation of Random Future Events — Bem, Daryl J (2015)
- Examining Psychokinesis: The Interaction of Human Intention With Random Number Generators—A Meta-Analysis — Bösch, Holger (2006)
- Reexamining Psychokinesis: Commentary on the Bösch, Steinkamp and Boller Meta-Analysis — Radin, D (2006)
- Evidence for Consciousness-Related Anomalies in Random Physical Systems — Radin, Dean I (1989)
- Electrophysiological Evidence of Intuition: Part 1. The Surprising Role of the Heart — McCraty, Rollin (2004)
Extends
- Predictive Physiological Anticipation Preceding Seemingly Unpredictable Stimuli: A Meta-Analysis — Mossbridge, Julia (2012)
- Predictive Physiological Anticipation Preceding Seemingly Unpredictable Stimuli: An Update of Mossbridge et al.'s Meta-Analysis — Duggan, Michael (2018)
- Temporal patterns of happiness and information in a global social network: Hedonometrics and Twitter — Dodds, Peter Sheridan (2011)
- Unconscious Perception of Future Emotions: An Experiment in Presentiment — Radin, Dean I (1997)
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📋 Cite this paper
Radin, Dean I (2023). Sentiment and Presentiment in Twitter: Do Trends in Collective Mood "Feel the Future"?. World Futures. https://doi.org/10.1080/02604027.2023.2216629
@article{radin_2023_sentiment,
title = {Sentiment and Presentiment in Twitter: Do Trends in Collective Mood "Feel the Future"?},
author = {Radin, Dean I},
year = {2023},
journal = {World Futures},
doi = {10.1080/02604027.2023.2216629},
}