Mobile phone price as a proxy for socio-economic indicators

Sultan, Syed Fahad; Humayun, Hamza; Nadeem, Umar; Bhatti, Zubair Khurshid; Khan, Sohaib

doi:10.1145/2737856.2737892

“…This is possibly due to numerous rural attendees visiting the State Foundation Day celebrations in Budapest or simply higher activity from individuals from groups of lower SES. In line with other research results [6,34] mobile phone prices as SES indicators are sufficient to uncover clusters in an urban population.…”

Section: Socioeconomic Status Clusterssupporting

confidence: 90%

“…Using mobile phone prices as socioeconomic indicators have been proved to work well [6,34]. Sultan et al in identified areas where more expensive phones appear more often using indicators of accessibility to services, infrastructure, hygiene and communication.…”

Section: Socioeconomic Status Analysismentioning

confidence: 99%

See 1 more Smart Citation

Do Social Event Attendees cluster based on Socioeconomic Status?

Szabó¹,

Pintér²,

Felde³

2023

Preprint

0

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Mobile phones have become an integral part of our lives in the last two decades, leaving a digital trace of our activities and communication. This study aims to develop a data processing framework to evaluate human mobility and socioeconomic status based on call detail records. The methodology proposed first calculates radius of gyration and entropy for each user, then estimates the socioeconomic status by the price and age of the subscribers' phones. Finally, an unsupervised machine learning algorithm was used to group the cells into clusters based on their mobility and socioeconomic metrics. The research showed differences between Buda and Pest during a large scale social event using mobile phone ages and prices. Additionally, the clustering results revealed homogenous groups of cells around Budapest, with similar mobility and socioeconomic metrics. The main conclusion is that mobile network data combined with mobile phone properties offer a useful tool for characterising urban mobility and socioeconomic status.

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“…Sultan et al identified areas in Jhelum, Pakistan, where the more expensive phones appear more often [31]. Using the same method, Budapest and its agglomeration were evaluated and the average phone prices were determined for every site based on the activity records.…”

Section: Resultsmentioning

confidence: 99%

“…In this paper, the price and age of subscribers' mobile phones are proposed to be used as socioeconomic indicators. While Blumenstock et al used call history as a factor in socioeconomic status [30], Sultan et al [31] applied mobile phone price as a socioeconomic indicator and identified areas where more expensive phones appear more often; however, only manually collected market prices were used.…”

Section: Introductionmentioning

confidence: 99%

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

Pintér

¹

,

Felde

²

2021

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In this study, Call Detail Records (CDRs) covering Budapest for the month of June in 2016 were analyzed. During this observation period, the 2016 UEFA European Football Championship took place, which significantly affected the habit of the residents despite the fact that not a single match was played in the city. We evaluated the fans’ behavior in Budapest during and after the Hungarian matches and found that the mobile phone network activity reflected the football fans’ behavior, demonstrating the potential of the use of mobile phone network data in a social sensing system. The Call Detail Records were enriched with mobile phone properties and used to analyze the subscribers’ devices. Applying the device information (Type Allocation Code) obtained from the activity records, the Subscriber Identity Modules (SIM), which do not operate in cell phones, were omitted from mobility analyses, allowing us to focus on the behavior of people. Mobile phone price was proposed and evaluated as a socioeconomic indicator and the correlation between the phone price and the mobility customs was found. We also found that, besides the cell phone price, the subscriber age and subscription type also had effects on users’ mobility. On the other hand, these factors did not seem to affect their interest in football.

show abstract

Do Social Event Attendees Cluster Based on Socioeconomic Status?

Szabó¹,

Pintér²,

Felde³

2023

Preprint

0

View full text Add to dashboard Cite

Mobile phones have become an integral part of our lives in the last two decades, leaving a digital trace of our activities and communication. This study aims to develop a data processing framework to evaluate human mobility and socioeconomic status based on call detail records. The methodology proposed first calculates radius of gyration and entropy for each user, then estimates the socioeconomic status by the price and age of the subscribers' phones. Finally, an unsupervised machine learning algorithm was used to group the cells into clusters based on their mobility and socioeconomic metrics. The research showed differences between Buda and Pest during a large scale social event using mobile phone ages and prices. Additionally, the clustering results revealed homogenous groups of cells around Budapest, with similar mobility and socioeconomic metrics. The main conclusion is that mobile network data combined with mobile phone properties offer a useful tool for characterising urban mobility and socioeconomic status.

show abstract

Mobile phone price as a proxy for socio-economic indicators

Cited by 3 publications

References 5 publications

Do Social Event Attendees cluster based on Socioeconomic Status?

Do Social Event Attendees cluster based on Socioeconomic Status?

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

Do Social Event Attendees Cluster Based on Socioeconomic Status?

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