116m Gsm Data ^hot^ May 2026

Based on the search term "116m gsm data paper," you are likely referring to one of the most significant academic papers in the field of computational social science and "Big Data."

The paper is titled: "Unique in the Crowd: The privacy bounds of human mobility" 116m gsm data

It was published in Scientific Reports (Nature) in 2013 by Yves-Alexandre de Montjoye, César A. Hidalgo, Michel Verleysen, and Vincent D. Blondel. Based on the search term "116m gsm data

Here are the key details regarding the "116m" figure and the paper's findings: 116m usually refers to 116 meters — the

What "116m" likely means

116m usually refers to 116 meters — the wavelength corresponding to a frequency near 2.58 MHz (since wavelength λ = c / f, where c ≈ 3×10^8 m/s).
In GSM/mobile contexts, common frequency bands are in MHz (e.g., 900 MHz, 1800 MHz). A 116 m wavelength (≈2.58 MHz) is far below GSM radio frequencies, so 116 m is not a GSM band wavelength.

The "116m" Figure

The number "116m" (116 million) refers to the scale of the dataset analyzed. The researchers analyzed 15 months of mobile phone data covering 1.5 million people in a small European country. Throughout the study period, these users generated approximately 116 million distinct spatial points (records) based on cell tower connections.

(Note: While the dataset contained 1.5 million users, the paper is often associated with the number 116 million in database or scaling contexts due to the total volume of location pings processed. If you are referring to a different specific figure involving "116m users," please see the clarification on the Yahoo dataset below.)

3.3 Measurement Method

Cut a sample of known area (e.g., 100 cm²).
Weigh on precision balance (0.001 g accuracy).
Calculate: GSM = (weight in grams) / (area in m²).
For 116 GSM, a 1 m² sheet weighs exactly 116 grams.

3. Sources of Such Data

How does 116 million records of GSM data end up in one place?

SS7 Vulnerabilities: The global protocol used by networks to route calls and texts is notoriously insecure. Hackers exploiting SS7 vulnerabilities can intercept calls and texts or track locations, harvesting this data in transit.
Contractor/Third-Party Leaks: Telecommunications companies often outsource billing or analytics to third parties. These third parties often spin up ElasticSearch or MongoDB instances to process the data and fail to secure them with authentication (username/password).
SS7 Geolocation Services: There is a grey market where companies offer "find my phone" or "spouse tracking" services. They buy access to SS7 networks to ping phones. These services often keep massive logs of their pings, which subsequently leak.