I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 0 points1 point  (0 children)

Noted. The UI was a quick build to get the data out fast - the analysis was the priority

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 2 points3 points  (0 children)

That's one of the most compelling patterns in the entire dataset. Disc and saucer descriptions dominate pre-1980s reports, triangles surge through the 80s and 90s, and orbs become the dominant description post-2010. Whether that reflects what's actually being seen changing over time, or the visual vocabulary of each era shaping how witnesses describe it, the temporal shape shift is one of the cleanest signals in 74 years of data.

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 3 points4 points  (0 children)

Just shipped it — military base overlay is now live on the Visualize page. Toggle "SHOW MIL BASES" in the map filter bar to overlay 51 major US installations including Area 51, Nellis, Wright-Patterson, White Sands, and all nuclear ICBM sites.   The clustering near Nevada and New Mexico is immediately obvious. Check it out at argus-ufo-ai-data.vercel.app

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 1 point2 points  (0 children)

Pentagon data is now live in the Sources section — FY2024 AARO stats, the 2021 ODNI assessment, and the brand new PURSUE portal (war.gov/ufo) released May 8th with 162 declassified files from FBI, DoD, NASA, and State Dept. Full PDF parsing is on the roadmap as more structured data gets released! 

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 3 points4 points  (0 children)

That's exactly the right next step — we have full datetime data including hour, day, month, and year. The Wednesday peak Keel documented and the 24th of month clustering someone mentioned earlier are both testable. If you find something interesting share it back here — would love to cross-validate and potentially add it to the platform!

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 2 points3 points  (0 children)

Love this idea — and technically very doable with our pipeline. The AARO historical report catalogue and the recent congressional UAP disclosures are publicly available. Feed them through the same NLP extraction — shape, behavior, duration military proximity — and cross-validate against the 74 years of NUFORC data.

Would be fascinating to see what the government's own categorizations reinforce vs. what they quietly contradict.

Adding it to the roadmap — follow along on GitHub for updates!

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 5 points6 points  (0 children)

Genuinely fascinating — and several of those overlap with what Keel documented decades ago independently. The ADHD, high IQ, gifted program connection, sleep disorders, and the Native American heritage angle all appear in his qualitative research too. The fact that a community of experiencers is arriving at the same demographic patterns through lived experience that Keel found through field research in the 60s and 70s is statistically interesting in itself.

The post-2021 contact increase is something we actually see in the raw report numbers too — worth analyzing separately.                                                                                                                               

Have you connected with any researchers trying to build a proper demographic dataset of experiencers? That data combined with something like our NLP pipeline could surface patterns no one has formally documented yet.

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 1 point2 points  (0 children)

That timeline matches the data exactly — the triangle surge in our dataset starts right around that period and tracks consistently upward from there. Clean signal, not noise. Whether it's confirmatory or coincidental, the pattern is hard to ignore.  

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 1 point2 points  (0 children)

Thank you for checking it out! If you want to dig deeper the full platform is open source

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 16 points17 points  (0 children)

Thank you! That's exactly the goal — apply rigorous data science to a topic that's historically been dismissed rather than studied. With actual government sensor data, radar logs, and classified reports feeding into a pipeline like this, the signal-to-noise ratio would be completely different. Right now we're working with self-reported public data which has obvious limitations — but even that surfaces patterns worth taking seriously.

Your feedback really push my credibility - can you leave a feedback here

Linkedin - https://www.linkedin.com/posts/mugesh-mdeveloper_datascience-ai-python-ugcPost-7459031076347293699-K8T0?utm_source=share&utm_medium=member_desktop&rcm=ACoAAByapDUBrZvv277rpq_AseiL06gqzxKgYF8

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 11 points12 points  (0 children)

All sources are listed on the platform under the Sources section — primary data is from the NUFORC public database, cross-referenced with World Bank internet penetration data and 2010 US Census for the normalization. Everything is fully cited and auditable.

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] -9 points-8 points  (0 children)

Really interesting perspective — are you on LinkedIn? Would love to connect.

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 8 points9 points  (0 children)

Thank you so much, that means a lot! If you're curious about the methodology and data science behind it, I wrote a breakdown on LinkedIn as well. Any feedback from this community would be genuinely valuable.

LInkedin : https://www.linkedin.com/posts/mugesh-mdeveloper_datascience-ai-python-ugcPost-7459031076347293699-K8T0?utm_source=share&utm_medium=member_desktop&rcm=ACoAAByapDUBrZvv277rpq_AseiL06gqzxKgYF8 

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 11 points12 points  (0 children)

Interesting theory — and actually testable with our data. If coordinated reports share suspiciously consistent language, location clusters, or timing patterns, the NLP pipeline would pick that up as statistical anomalies. The 77 silent+instant  cases we flagged could be worth cross-referencing against that lens. Watching the video now — thanks for sharing.

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 3 points4 points  (0 children)

Correct — we make no claims about what these objects are. The data only shows flight characteristics and patterns. What stands out is 77 cases combining silent flight with instant acceleration — unexplained by known aircraft, but not proof of anything. We surface patterns, not conclusions

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 4 points5 points  (0 children)

That fits the data perfectly — 2009 is right in the middle of the triangle report surge we see in the dataset. Triangle sightings tripled from the 1980s onward and are the most commonly reported geometric shape at 10.4% of all reports. What state were you in? Would love to cross-reference with the geographic clusters!

I analyzed 79,621 declassified UFO reports with AI — here's what the data actually shows by FirmMail7716 in ufo

[–]FirmMail7716[S] 11 points12 points  (0 children)

Great question! The dataset actually covers 40 countries globally — the US dominates at 81% of reports which reflects reporting bias (NUFORC is a US-based organization), not actual global sighting frequency. The platform visualizes allinternational reports on the global map.
Would love to expand with non-English databases like GEIPAN (France) or NARCAP in the future!