MBTI Seoul

Seoul Dongs · MBTI Visualization Group 14 · Yonsei University · Introduction to Visualization

— I / E

— N / S

— T / F

— J / P

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Personality Match Map

IT'S YOUR SEOUL

Based on your MBTI profile, all 427 Seoul neighborhoods are scored by four-dimensional personality distance — Energy (I/E), Information (N/S), Decisions (T/F), and Lifestyle (J/P). Darker blue marks a closer match; use the arrows below to browse top-ranked neighborhoods and districts.

Lower match

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Match score = how well each area's MBTI profile aligns with your settings

Higher match

Top Matches

Neighborhood

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District

#1 —

n = 427 neighborhoods · 25 districts · Match score = Σ|neighborhood value − your profile| across 4 MBTI dimensions · Border highlight only — fill color reflects relative match intensity

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I / E

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N / S

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T / F

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J / P

Adjust Personality

Energy I · E

I E

Information N · S

N S

Decision T · F

T F

Lifestyle J · P

J P

Data Heatmaps ↓

Type Distribution

SEOUL FITS...

Each of Seoul's 427 neighborhoods carries a personality profile across four dimensions. For every MBTI type, we measure how strongly the city aligns — a darker cell means more neighborhoods where that type would feel at home. Percentages show each type's relative share of Seoul's total personality fit.

Introvert ← Energy Axis → Extrovert

Sensing–Thinking · Sensing–Feeling · Intuiting–Feeling · Intuiting–Thinking

ISTJ—

ISFJ—

INFJ—

INTJ—

ISTP—

ISFP—

INFP—

INTP—

ESTP—

ESFP—

ENFP—

ENTP—

ESTJ—

ESFJ—

ENFJ—

ENTJ—

Lower type fit

0%—100%

% = share of Seoul's fit landscape for each type

Higher type fit

n = 427 neighborhoods · Fit score = Σ(1 − |neighborhood value − type profile|) across 4 dimensions · Cell color = relative fit among 16 types · Percentage = share of Seoul's total personality fit landscape

MBTI Dimensions

ONE BY ONE

Seoul's personality is built from four axes — Introvert/Extrovert, Intuiting/Sensing, Thinking/Feeling, and Judging/Perceiving. Here we look at one axis at a time: use the tabs to switch between I/E, N/S, T/F, and J/P. Red shades mark the left pole of each pair; blue marks the right. Hover any district or neighborhood to see its exact percentage split.

Unit

Loading map…

Introvert

100% 50% 100%

← share of residents classified as each pole

Extrovert

Each area's color comes from the same six spatial datasets and weight table used elsewhere in this project. Toggle district or neighborhood view to compare scales, and switch dimensions with the tabs above. Percentages reflect how strongly each area leans toward either pole.

Two Axes at Once

CONSIDERING TWO

Pick any two MBTI dimensions and plot every neighborhood as a dot. Areas with similar scores cluster together; outliers sit apart. Use the axis buttons along the chart to explore different pairings, hover a dot to preview it on the map, and click to pin locations you want to compare. When both axes show the same dimension, points fall on a diagonal — one trait plotted against itself.

Unit

unselected hovered pinned

Hover to preview · click map or chart to pin (multiple) · click empty area to clear

427 neighborhoods

Each dot uses the same weighted MBTI values as the maps above. Axis percentages run from 0% to 100% along each pole; pinned points stay highlighted until you click empty space to clear.

Raw Data

DATASET FOR HYPOTHESIS

Before linking data to personality traits, we gathered six spatial indicators across all of Seoul — from subway access to nighttime noise. The table below summarizes where each dataset comes from, what it measures, and how much ground it covers. Maps and charts that follow show how each indicator is distributed across districts and neighborhoods.

ID	Indicator	Source	Unit	Coverage	Volume / Range
D1	Subway Stations	Ministry of Land, Infrastructure and Transport administrative boundaries · Naver Map crawl	count	214 neighborhoods 25 districts	371 stations total 0–7 per neighborhood
D2	Convenience Stores	Ministry of Land, Infrastructure and Transport administrative boundaries · Naver Map crawl	count	363 neighborhoods 25 districts	2,618 stores total 0–64 per neighborhood
D3	Han River Distance	admdongkor (ver 20260401) · southkorea/seoul-maps (2013) · Han River boundary	meters	427 neighborhoods 25 districts	0 m (riverside) – 10 km+ (outer north)
D4	Green Space Ratio	Environmental Spatial Information Service — Seoul green space distribution (Fig. 2-4)	%	427 neighborhoods 25 districts	Forest + grassland share 0 – 100%
D5	Foot Traffic Mix	Seoul Open Data Plaza (2018) — weekly living-population hour mix (HPM)	index	427 neighborhoods 25 districts	0.465 – 0.859 HPM
D6	Nighttime Noise	Hankook Ilbo · 2013–2018 3D noise map (Seoul + 11 municipalities)	dBA	427 neighborhoods 25 districts	45 – 78 dBA (night traffic)

Geographic Distribution

For each indicator, the map shows how values vary across Seoul — darker areas mean higher counts or stronger intensity. The stacked bar chart beside each map breaks the same data down by district, with lighter segments for smaller neighborhoods and darker ones for larger contributions within each district.

Subway Stations

Neighborhood and district counts of subway stations across Seoul.

Source: Ministry of Land, Infrastructure and Transport administrative boundaries · Naver Map crawl

0
stations

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Stacked by Neighborhood per District

Convenience Stores

Distribution of convenience store locations by neighborhood and district.

Source: Ministry of Land, Infrastructure and Transport administrative boundaries · Naver Map crawl

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stores

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Stacked by Neighborhood per District

Distance to Han River

Average distance from each area to the Han River shoreline.

Source: Ministry of Land, Infrastructure and Transport administrative boundaries · Naver Map crawl

0 km
(riverside)

~12 km
(outer)

Neighborhood spread per District

Green Space Ratio

Share of forest and grassland area within each neighborhood (Figure 2-4, Seoul green space distribution).

Source: Environmental Spatial Information Service (egis.me.go.kr)

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Neighborhood spread per District

Hour-based People Mix

Hour-based people mix (HPM) for a week — living population time-band diversity by neighborhood.

Source: Seoul Open Data Plaza (2018)

0.47
min (Seoul)

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Neighborhood spread per District

Nighttime Noise

Nighttime traffic noise levels (dBA) from Seoul’s 3D noise map — night standard 55 dBA for traffic noise management areas.

Source: Hankook Ilbo · 2013–2018 3D noise map project (Seoul and 11 municipalities)

45 dBA

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Neighborhood spread per District

Data × MBTI

HYPOTHESIS TO WEIGHT

For each indicator, we wrote explicit hypotheses about which MBTI traits it might support — for example, more subway stations suggesting a more extroverted, connected area. Those ideas became signed weights in the table below: positive values push toward E, N, F, or J; negative values push toward the opposite pole. Each column sums to 100%, so every dataset's influence is fully allocated across the four axes.

Indicator	Hypothesis	E	N	F	J
D1 Subway Stations	E:More stations mean vibrant, connected mobility hubs. J:Dense transit hubs imply planned routines. S:Station areas feel concrete and sensory.	+30%	−10%	—	+30%
D2 Convenience Stores	S:More convenience stores signal immediate, practical needs. J:Tight neighborhood infrastructure supports routine living.	—	−10%	—	+30%
D3 Distance to Han River	E:Farther from the Han River means outer-urban, socially connected edges. N·FFarther from the river also means quieter, nature-adjacent neighborhoods. J:Closer to the river suggests planned riverside living (inverse distance).	+10%	+40%	+30%	−20%
D4 Green Space Ratio	N·FHigher green space suggests nature-friendly, emotionally attuned places. J:Lower green cover aligns with denser urban fabric (inverse ratio).	—	+40%	+50%	−20%
D5 Foot Traffic Mix	E:Higher foot-traffic mix across time bands suggests vibrant, socially active districts. —Lower mix often marks districts with steadier, routine foot traffic.	+40%	—	—	—
D6 Nighttime Noise (dBA)	E:Higher noise marks areas with active nightlife. F:Lower noise suggests softer, emotionally attuned neighborhoods.	+20%	—	−20%	—
Σ \|weight\| per dimension		100%	100%	100%	100%

+X% Weight toward trait in column header (E / N / F / J)

−X% Weight toward opposite trait (I / S / T / P)

— No effect on this axis

Normalization & Scoring Formula

Each indicator is normalized city-wide as norm(x) = (x − min) / (max − min) to 0–1.
Positive weights use |w| × norm(x); negative weights use |w| × (1 − norm(x)).
Final dimension score = sum of contributions in that column → 0 (E/S/T/P) to 1 (I/N/T/J). For TF, the F column is inverted: TF = 1 − F_score.

FIND YOUR SEOUL

MBTI Seoul

SEOUL FITS...

ONE BY ONE

CONSIDERING TWO

DATASET FOR HYPOTHESIS

HYPOTHESIS TO WEIGHT

Area Colors