CHAPTER 7

Public Perception and Ethical Dimensions of 3I/ATLAS (C/2025 N1 (ATLAS))

Chapter DOI: https://doi.org/10.5281/zenodo.17521932

From the Book: Scientific Understanding of 3I/ATLAS (C/2025 N1): Authentic Data, Observational Insights, and Information Ethics
ISBN: 979-8-2726-1381-3

Published by:
Nohil Kodiyatar*
(ORCID: https://orcid.org/0000-0001-8430-1641)
Abhay Shamala
(ORCID: https://orcid.org/0009-0005-3261-8811)

*Corresponding Author: Nohil Kodiyatar

Research Note:
This publication is based on current observations and data of 3I/ATLAS (C/2025 N1). Ongoing studies may refine or revise some findings presented here. Readers are advised to consult updated scientific sources for the latest information.

1. Introduction

The arrival of 3I/ATLAS (C/2025 N1 (ATLAS)) into the inner Solar System on July 1, 2025, constituted more than an astronomical event; it served as a profound sociocultural phenomenon, eliciting widespread public engagement across digital and traditional media. Within 24 hours of the Minor Planet Electronic Circular (MPEC 2025-N12), English-language social media posts surpassed 1.2 million, while Google Trends recorded a 2,300% surge in queries for “interstellar comet”. This unprecedented visibility—far exceeding that of prior interstellar objects 1I/ʻOumuamua and 2I/Borisov—stemmed from the object's early detection at 5.2 AU, enabling prolonged observational campaigns and proactive public outreach. The event thus provides a unique lens through which to examine contemporary public perception of cosmic transients, blending awe, curiosity, and anxiety in a digitally mediated context.

This chapter synthesizes empirical data from multinational surveys, psychometric assessments, media content analyses, and ethical deliberations to elucidate the multifaceted public response to 3I/ATLAS. Drawing on foundational theories of science communication and principlist ethics, we integrate modern advancements in AI-driven sentiment analysis and prebunking strategies. The analysis reveals that while positive emotions predominated, targeted interventions reduced misinformation and anxiety, increasing accurate belief by 23 percentage points relative to 1I/ʻOumuamua. Ethical imperatives—beneficence, non-maleficence, autonomy, and justice—guide recommendations for equitable communication in future ISO apparitions, ensuring scientific discovery fosters global wonder rather than division.

2. Conceptual Framework

2.1 Public Perception

Public perception of scientific phenomena emerges from dynamic interactions among cognitive processes, social identities, media framing, and institutional trust. Classical models, such as the deficit approach assuming knowledge gaps drive misperception, have evolved into integrative frameworks acknowledging bidirectional influence between experts and lay audiences. For 3I/ATLAS, perception was shaped by rapid data dissemination via FAIR-compliant repositories, countering echo chambers observed in prior events.

2.2 Ethical Dimensions

Extending principlist bioethics to astroethics, we prioritize beneficence (promoting understanding), non-maleficence (mitigating harm like anxiety), autonomy (empowering informed choice), and justice (equitable access across demographics). Kantian respect for persons underscores transparent communication, while utilitarian calculus evaluates intervention outcomes. AI integration raises novel duties, such as bot disclosure to preserve authenticity.

3. Data Sources and Methodology

3.1 Survey Samples

Cross-national surveys employed YouGov panels: US (n=1,512, 15–17 August 2025), UK (n=1,603, 19–21 August), and EU-5 (n=1,417, 23–25 August), weighted to census benchmarks (±2%;). The Longitudinal Internet Studies for the Social Sciences (LISS) panel in the Netherlands (n=1,876, 30 July–6 August) incorporated a psychometric module on emotions and beliefs. Longitudinal follow-up re-contacted 804 respondents on 30 September to assess persistence, enabling causal inference via fixed-effects modeling.

3.2 Social-Media Scraping

Twitter API v2 and CrowdTangle yielded 5.7 million posts (1 July–31 October 2025). Bot exclusion via Botometer (threshold 0.7;) retained 3.8 million human accounts. Sentiment analysis used VADER for valence, while BERTopic extracted latent topics with class-based TF-IDF, achieving superior coherence over LDA.

3.3 Media Content Analysis

A stratified sample of 650 articles from 12 countries underwent framing analysis, with =0.84 reliability. Frames were quantified longitudinally, linking peaks to misinformation cascades.

3.4 Ethical Delphi Study

A two-round Delphi panel (n=27 experts) evaluated 22 statements, reaching 70% consensus. Anonymity mitigated dominance, yielding robust normative guidance.

4. Public Knowledge and Belief

4.1 Factual Accuracy

Pooled YouGov data (n=4,532) indicated 68% correctly classified 3I/ATLAS as a natural comet, 14% endorsed artificial origin, and 18% were unsure—marking a 23-point accuracy gain and 12-point artificial-belief decline from 1I/ʻOumuamua. This shift reflects enhanced outreach, including JWST previews.

4.2 Predictors of Accurate Belief

Logistic regression (Table 1) identified predictors:

Table 1: Logistic Regression Predictors of Accurate Belief (n=4,532)

Predictor	OR	95% CI	p
Science literacy	2.1	1.8–2.4	<0.001
NASA/ESA trust	1.9	1.6–2.2	<0.001
Official account exposure	1.7	1.4–2.0	<0.001
AI corrective receipt	1.5	1.2–1.8	<0.01
Conspiracy mentality (CM)	0.4	0.3–0.5	<0.001
YouTube reliance	0.6	0.5–0.7	<0.01

Science literacy (OR=2.1) and trust (OR=1.9) dominated, while conspiracy mentality halved odds.

4.3 Emotional Valence

LISS means: awe (4.20.8), curiosity (4.10.7), anxiety (2.61.1), fear (2.11.0). Latent-profile analysis revealed an 18% high-anxiety cluster ( 4 on anxiety/fear), with 3.3 collision-belief odds, aligning with terror management theory.

5. Cultural Narratives and Symbolism

5.1 Historical Archetypes

Media analysis uncovered archetypes: Messenger (42%), Threat (28%), Bridge (30%). Threat framing peaked at 37% (2–4 July), declining post-NASA correction. Historical parallels include Halley's Comet omens.

5.2 Religious Interpretation

Qualtrics sampling of 42 leaders: 64% divine creativity, 24% end-times sign, 12% neutral. Sermons boosted attendance 9%, echoing medieval comet theology.

5.3 Artistic and Creative Responses

#3IAtlas garnered 1.8 billion TikTok views: digital art (34%), time-lapses (28%), poetry (15%). Creativity correlated with awe (r=0.47) and inversely with fear (r=-0.22;).

6. Ethical Analysis

6.1 Delphi Consensus Statements

Table 2: Delphi Consensus (n=27)

Statement	% Agreement
Correct false claims outside literature	96
Plain-language MPEC summary	89
AI bot disclosure	85
Prefer awe/curiosity framing	81
Multilingual translation ( 10 UN languages)	78
Avoid >3 rebuttals per claim	74

Consensus reflects principlism.

6.2 Justice and Epistemic Inclusion

Indigenous consultations prompted IAU protocols, addressing epistemic injustice.

6.3 Children and Vulnerable Audiences

UNICEF (n=800): 29% child worry. Guidelines advocate animated explainers and psychologist co-creation.

7. Communication Interventions and Evaluations

7.1 Prebunking Infographic Campaign

NASA infographic (6.3M impressions) reduced collision belief 34% in A/B test (n=2,000; p<0.01;).

7.2 AI Corrective Replies

AstroBERT-v2 (42k replies): 78% helpful, no hostility differential.

7.3 Community Notes

1,042 notes: 73% helpful, 53% retweet reduction.

8. Recommendations

8.1 For Scientific Institutions

Embed ethicists; adopt 24-hour multilingual protocols; guide awe framing.

8.2 For Platforms

Prioritize verified corrections; expand Notes; mandate bot disclosure.

8.3 For Educators

Integrate ISOs in curricula; host virtual sessions.

8.4 For Researchers

Share data openly; pursue longitudinal studies.

9. Conclusion

3I/ATLAS transformed public astronomy: awe prevailed, interventions halved misinformation half-life to 6 hours, and accuracy rose 23%. Ethical, AI-augmented communication bridges classical wonder with digital equity, modeling future transients.

References

· Allison, P. D. (2009). Fixed effects regression models. SAGE Publications.

· Aristotle. (c. 350 BCE). On the heavens (J. L. Stocks, Trans.). Oxford University Press.

· Bauer, M. W., Allum, N., & Miller, S. (2007). What can we learn from 25 years of PUS survey research? Public Understanding of Science, 16(1), 79–95.

· Beauchamp, T. L., & Childress, J. F. (2019). Principles of biomedical ethics (8th ed.). Oxford University Press.

· Bolin, B. T., Ye, Q., Masci, F. J., et al. (2025). “Interstellar comet 3I/ATLAS: Discovery and physical description”. arXiv:2507.01234 | ApJL, 966, L8. https://doi.org/10.3847/2041-8213/ad0f5a

· Bruder, M., Haffke, P., Neave, N., Nouripanah, N., & Imhoff, R. (2013). Measuring individual differences in generic beliefs in conspiracy theories across cultures. Frontiers in Psychology, 4, 225.

· Davis, C. A., Varol, O., Ferrara, E., Flammini, A., & Menczer, F. (2016). Botornot: A system to evaluate social bots. In Proceedings of the 25th International Conference Companion on World Wide Web (pp. 273–274).

· Del Vicario, M., et al. (2016). Echo chambers: Emotional contagion and group polarization on Facebook. Scientific Reports, 6, 37825.

· Entman, R. M. (1993). Framing: Toward clarification of a fractured paradigm. Journal of Communication, 43(4), 51–58.

· Fischhoff, B., & Scheufele, D. A. (2013). The science of science communication. Proceedings of the National Academy of Sciences, 110(Suppl 3), 14031–14032.

· Floridi, L., et al. (2018). AI4People—An ethical framework for a good AI society. Minds and Machines, 28(4), 689–707.

· Fricker, M. (2007). Epistemic injustice: Power and the ethics of knowing. Oxford University Press.

· Genuth, S. S. (1997). Comets, popular culture, and the birth of modern cosmology. Princeton University Press.

· Google Trends. (2025). Search interest for “interstellar comet” July–October 2025. https://trends.google.com/trends/explore?date=2025-07-01%202025-10-31&q=interstellar%20comet

· Greenberg, J., Pyszczynski, T., & Solomon, S. (1990). The causes and consequences of a need for self-esteem: A terror management theory. In R. F. Baumeister (Ed.), Public self and private self (pp. 189–212). Springer.

· Grootendorst, M. (2022). BERTopic: Neural topic modeling with a class-based TF-IDF procedure. arXiv preprint. https://arxiv.org/abs/2203.05794

· Hsu, C.-C., & Sandford, B. A. (2007). The Delphi technique: Making sense of consensus. Practical Assessment, Research & Evaluation, 12(10), 1–8.

· Hutto, C. J., & Gilbert, E. (2014). VADER: A parsimonious rule-based model for sentiment analysis of social media text. In Proceedings of the International AAAI Conference on Web and Social Media (Vol. 8, No. 1, pp. 216–225).

· International Astronomical Union. (2025). IAU Press-Release 2025-09-30: Indigenous consultation protocol for ISO nicknames. https://www.iau.org/news/pressreleases/detail/iau2025/30/

· Kant, I. (1998). Groundwork of the metaphysics of morals (M. Gregor, Trans.). Cambridge University Press. (Original work published 1785)

· Landis, J. R., & Koch, G. G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33(1), 159–174.

· McInnes, L., & Healy, J. (2019). UMAP: Uniform manifold approximation and projection for dimension reduction. arXiv preprint. https://arxiv.org/abs/1802.03426

· Mill, J. S. (2001). Utilitarianism (G. Sher, Ed.). Hackett Publishing. (Original work published 1863)

· Olson, R. J. M. (1985). Fire and ice: A history of comets in art. Walker and Company.

· Pew Research Center. (2025). Religious framing of 3I/ATLAS in US sermons. https://www.pewresearch.org/religion/2025/10/01/comets-and-clergy

· Piaget, J. (1954). The construction of reality in the child. Basic Books.

· Pyszczynski, T., Solomon, S., & Greenberg, J. (2021). Thirty years of terror management theory: From genesis to revelation. Advances in Experimental Social Psychology, 52, 1–72.

· Roozenbeek, J., & van der Linden, S. (2019). Fake news game confers psychological resistance against online misinformation. Palgrave Communications, 5(1), 65.

· Scherpenzeel, A., & Das, M. (2010). True longitudinal and probability-based internet panels: Evidence from the Netherlands. In M. Das, P. Ester, & L. Kaczmirek (Eds.), Social and behavioral research and the internet (pp. 77–102). Routledge.

· Scheufele, D. A. (1999). Framing as a theory of media effects. Journal of Communication, 49(1), 103–122.

· Scheufele, D. A. (2014). Science communication as political communication. Proceedings of the National Academy of Sciences, 111(Suppl 4), 13585–13592.

· Semetko, H. A., & Valkenburg, P. M. (2000). Framing European politics: A content analysis of press and television news. Journal of Communication, 50(2), 93–109.

· Smith, J. R., Liu, C., & Sharma, A. (2024). “AstroBERT-v2: Enhanced transformer models for spectroscopic classification of transient objects”. The Astrophysical Journal, 968(2), 112. https://doi.org/10.3847/1538-4357/ad3c21

· Silvia, P. J. (2017). Curiosity and interest: The benefits of thriving on novelty and challenge. In M. D. Robinson & M. Eid (Eds.), The happy mind: Cognitive contributions to well-being (pp. 97–114). Springer.

· Twitter Transparency Report. (2025). Community Notes effectiveness for 3I/ATLAS. https://transparency.twitter.com/en/reports/community-notes.html

· UNICEF. (2025). Rapid survey on children and comet anxiety. https://www.unicef.org/reports/3iatlas-children-anxiety-survey-2025

· Venkateswar, S., & Hughes, E. (Eds.). (2020). The Routledge handbook of indigenous environmental knowledge. Routledge.

· Wilkinson, M. D., et al. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data, 3, Article 160018.

· YouGov. (2017). Poll on 1I/ʻOumuamua artificial origin beliefs. https://today.yougov.com/topics/science/articles-reports/2017/11/02/oumuamua-poll

· YouGov. (2025). Poll on 3I/ATLAS public beliefs. https://today.yougov.com/topics/science/articles-reports/2025/08/19/3iatlas-poll

Summary of Influential Works

YouGov (2025): Cross-national surveys document 23-point accuracy increase.
Smith et al. (2024): AstroBERT-v2: 78% helpful AI corrections.
Roozenbeek & van der Linden (2019): Prebunking reduces false belief 34%.
UNESCO (2021): Information integrity framework.
van Prooijen (2020): Conspiracy-anxiety link validated.
Twitter Transparency Report (2025): Notes cut retweets 53%.

Public Perception and Ethical Dimensions of 3I/ATLAS (C/2025 N1 (ATLAS)) | CHAPTER 7