Using Location Data From Mobile Phones to Study Participation in Mass Protests

Abstract

Automatically collected behavioral data on the location of users of mobile phones offer an unprecedented opportunity to measure mobilization in mass protests, while simultaneously expanding the range of researchable questions. Location data not only improve estimation of the number and composition of participants in large demonstrations. Thanks to high spatial and temporal resolution they also reveal when, where, and with whom different sociopolitical sectors join a protest campaign. This article compares the features and advantages of this type of data with other methods of measuring who participates in street protests. The steps in preparing a usable data set are explained with reference to a six-week campaign of mass mobilization in Israel in 2011. Findings based on the Israeli data set illustrate a wide range of potential applications, pertaining to both the determinants and consequences of protest participation. Limitations of mobile location data and the privacy issues it raises are also discussed.

News and Geolocated Social Media Accurately Measure Protest Size Variation

“…The concern that news and social media estimates of protest size cannot be trusted should be laid to rest. Though others have reported protest size using cellphone records, we are the first, as far as we are aware, to use location data from them as opposed to call detail records collected by transmission towers (Shalev and Rotman 2020;Traag, Quax, and Sloot 2017) and to verify secondary datasets. Whether a researcher prefers news or social media to measure protest size variation is his or her choice, as they are equally accurate.…”

Awakening City: Traces of the Circadian Rhythm within the Mobile Phone Network Data

“…CDR processing is often applied for large social event detection, such as football matches [1][2][3][4], concerts [5], sociopolitical events [6,7] or mass protests [8,9]. Epidemiology is mentioned as a potential application of human mobility studies, but the COVID-19 pandemic prioritized its applications in digital epidemiology, as mobile phone network data can reflect the mobility changes caused by the imposed restrictions.…”

Analyzing the Behavior and Financial Status of Soccer Fans from a Mobile Phone Network Perspective: Euro 2016, a Case Study

“…Apart from commuting and connectivity analyses, CDR processing is often used [21][22][23][24][25][26][27][28] for the detection of large social events. When thousands of people are in the same place at the same time, they generate a significant 'anomaly' in the data, whereas small groups usually do not stand out from the 'noise'.…”

“…In [26,27], mass protests are analyzed via mobile phone network data. In [21][22][23]] and [28], the authors examined the location of stadiums where football matches had taken place.…”