Data-Driven Geospatial Analysis of U.S. UFO Reports (1969–2022): Narratives, Sentiment, and Spatial Patterns in NUFORC Data

To the point

Using NUFORC data on US UFO sightings from 1969 to 2022, it blends data exploration, text mining, sentiment analysis, and geospatial analysis to identify when and where patterns occur, examine possible links to public perception and nearby military bases, acknowledge reporting biases and data limits, and present a case study with open R code and figures to ensure transparency while cautioning against causal claims from unverified reports.

Imminent: Inside the Pentagon’s Hunt for UFOs

Luis Elizondo

Exploring the Cosmos with James Webb

Steeven Cadel

The invisible college

Jacques Vallee

Passport to Magonia: From Folklore to Flying Saucers

Jacques Vallee

Our recommendations from Amazon

escholarship.org

Unveiling Hidden Patterns in UFO Sightings: A Text Mining and Geostatistical Approach

Author(s): Chen, Yuxin | Advisor(s): Zes, David A. | Abstract: This thesis delves into the enigmatic world of unidentified flying objects (UFOs), investigating the diverse characteristics, societal perceptions, and potential associations with military bases. Focusing on UFO sightings reported within the United States and documented by the National UFO Reporting Center (NUFORC) from 1969 to 2022, this study aims to shed light on the complexities surrounding these intriguing phenomena using statistical methods including Exploratory Data Analysis, Text Mining, Sentiment Analysis, and Geostatistical techniques.