2030 'Single-Person Households' Concentrated Near Universities and Workplaces... Increased Risk of 'Social Isolation' for Low-Income Elderly Single-Person Households

SKT and University of Seoul Develop 'Seoul Citizen Life Data' Using Statistics and Big Data Technology
Seoul City Promotes Policies to Improve Quality of Life Linked to 'Four Major Safety Policies for Single-Person Households'

[Asia Economy Reporter Lim Cheol-young] Single-person households in their 20s and 30s tend to cluster in specific administrative districts with many universities or companies, while middle-aged individuals in their 40s and 50s are concentrated in low-rise residential areas, and seniors aged 60 and above show high density in Gangbuk, Dobong, and Nowon districts. Low-income elderly single-person households exhibited significantly fewer movements, outings, and phone calls compared to other groups, indicating a high risk of social isolation. Areas with high usage of delivery apps were ranked in order of Gwanak, Gangnam, and Gwangjin districts, showing that delivery services are heavily used in regions densely populated by single-person households.

On the 29th, the Seoul Metropolitan Government, in collaboration with SK Telecom and the University of Seoul, developed and announced the ‘Seoul Citizen Life Data,’ which combines and analyzes pseudonymized data from 3 million people. Seoul plans to release this data first through the Open Data Plaza and continuously update it monthly.

‘Seoul Citizen Life Data’ merges public data such as population and household statistics (Statistics Korea Census) with pseudonymized telecommunications data (SKT communication information) to estimate the number and living conditions of single-person households by gender and age at the administrative district level. This is the first case of pseudonymized data being applied to real life following the amendment of the Data 3 Act (Personal Information Protection Act).

Its most notable feature is the ability to analyze the lifestyle characteristics of single-person households in detail through telecommunications data that can confirm information such as call and text volumes, days of use of video services like YouTube and Netflix, number and distance of movements, and days of delivery service usage.

Utilized in connection with the ‘Four Major Safety Policies for Single-Person Households’... Policy formulation and implementation for single-person households

Seoul plans to actively use the ‘Seoul Citizen Life Data’ in connection with the ‘Four Major Safety Policies for Single-Person Households’ announced earlier this year to establish and promote practical policies aimed at improving the quality of life for socially vulnerable groups, including single-person households. As of 2021, there are 1.49 million single-person households residing in Seoul, accounting for 36.8% of all households.

By utilizing detailed information by age and region, targeted policies by generation and housing environment improvement projects for single-person households can be implemented. For the elderly, social relations can be improved and issues of loneliness and isolation addressed by linking programs such as ‘Happy Table,’ where people share meals and interact, or companionship projects in areas with low community activity. Beyond single-person household policies, analyzing delivery service usage by administrative district can also be used to select locations for delivery workers’ rest areas.

Additionally, in the second half of this year, the city plans to enhance the reliability and accuracy of the data by combining telecommunications data with credit card data (consumption and merchant information) and credit information (credit and income data). To this end, Seoul plans to sign joint research agreements with private sector companies such as Shinhan Card.

2030s cluster near universities and companies... High delivery service usage in single-person household dense areas

Correlation Coefficient Between Population by Age Group and Single-Person Households Based on Administrative Districts

The density and locations of single-person households varied by generation. Young adults (in their 20s and 30s) tend to live clustered around university areas or company neighborhoods. Middle-aged individuals (40s and 50s) are concentrated in low-rise residential areas, while seniors (60 and above) show high density in Gangbuk, Dobong, and Nowon districts. Notably, although the city center (Jung-gu and Jongno-gu) does not have a large number of single-person households, the proportion of single-person households relative to the population is high.

The administrative districts with the highest number of young single-person households (20s and 30s) were Hwayang-dong in Gwangjin-gu, Yeoksam 1-dong in Gangnam-gu, and Cheongnyong-dong in Gwanak-gu, clustering around universities or company areas. For middle-aged groups (40s and 50s), the highest densities were in Yeoksam 1-dong in Gangnam-gu, Hwagok 1-dong in Gangseo-gu, and Junghwa 2-dong in Jungnang-gu. For seniors (60 and above), the densest areas were Deungchon 3-dong in Gangseo-gu, Junggye 2 and 3-dong in Nowon-gu, and Sanggye 3 and 4-dong in Nowon-gu.

Comparing the population and single-person household concentrations by generation, the largest difference appeared in the 40s age group. For those in their 20s, the overall population density and single-person household density were similar, whereas for those in their 40s, there was a difference between the administrative district with the largest total population (Sinjeong 3-dong in Yangcheon-gu) and the single-person household dense area (Yeoksam 1-dong in Gangnam-gu).

Analyzing delivery service access frequency by administrative district using telecommunications data showed that Sillim-dong in Gwanak-gu (average 18.4 times per month), Nonhyeon 1-dong in Gangnam-gu (18.1 times), and Yeoksam 1-dong in Gangnam-gu (17.6 times) had the highest frequencies, indicating high usage in single-person household dense areas. By age group, those aged 25 to 34 used delivery services the most.

The number of uses of video and broadcasting services such as YouTube was highest among those in their 30s. By region, Sillim-dong in Gwanak-gu (average 28.1 times per month), Yeoksam 1-dong in Gangnam-gu (26.6 times), and Nonhyeon 1-dong in Gangnam-gu (26.4 times) ranked highest, again in single-person household dense areas.

Low-income elderly show fewer movements, outings, and calls, increasing risk of social isolation

Distribution of Single-Person Households with Low Communication by Gender and Age Group and Distribution of Single-Person Households with Low Communication by Administrative District

Among single-person households with low communication (bottom 10%) inferred from text and call volumes, males under 69 years old showed less communication than females across all age groups. Especially, middle-aged and older single-person households living in downtown areas such as Myeong-dong, Euljiro-dong, and Hoehyeon-dong were estimated to have particularly low communication based on telecommunications data.

Seoul found that low-income elderly single-person households had significantly fewer holiday movements, fewer people they called, and fewer holiday outings compared to other groups, indicating a lack of social contact.

Meanwhile, unlike national official statistics based on administrative data such as the Population Census (single-person households) by Statistics Korea and Resident Registration Population Statistics (single-person households) by the Ministry of the Interior and Safety, the ‘Seoul Citizen Life Data’ was created by combining public and private data. Unlike the Population Census produced annually, it is updated monthly with the latest data and can be utilized in detailed segments by administrative district, gender, and age (in 5-year increments).

Lee Hye-kyung, Director of Digital Policy at Seoul City, said, “Timely and high-resolution data in terms of time and space is essential for developing welfare safety net policies for single-person households and socially vulnerable groups.” She added, “We expect that the activation of big data research through the combination of various data types will play a pivotal role in improving citizens’ quality of life.”

This content was produced with the assistance of AI translation services.