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Scranton, Pennsylvania: History, Geography, Community & Culture
Scranton is a second A class city in and the county seat of Lackawanna County, Pennsylvania, United States. With a population of 76,328 at the 2020 census (estimated at 75,514 in 2025), Scranton is the sixth-most populous city in Pennsylvania and the most populous city in Northeastern Pennsylvania. It is part of the Wyoming Valley metropolitan area…
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Scranton, Pennsylvania topic overview
The analysis highlights History, Geography, Community and Culture as prominent areas in the source structure around Scranton, Pennsylvania. 2 topics appear in more than one source area, which can help identify connections that are less obvious in a linear reading.
Related topics
364
Source areas
13
Connected nodes
379
Extracted relationships
44
Concept neighborhoods
119
Bridge connections
379
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
History · 116 topics
Transportation · 49 topics
Media · 35 topics
Arts and culture · 27 topics
Education · 27 topics
Sports · 26 topics
In popular culture · 24 topics
Overview · 18 topics
Demographics · 16 topics
Sister cities · 16 topics
Geography · 6 topics
Fire department · 5 topics
Gallery · 1 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Area codes
570 and 272
Country
United States
County
Lackawanna
Demonym
Scrantonian/Scrantonite
Elevation
745 ft (227 m)
FIPS code
42-69000
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Scranton, Pennsylvania connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Scranton, Pennsylvania shows recurring relationship patterns in the source. For example, Scranton, Pennsylvania → 25.54 sq mi (66.14 km2), 76,328 Another extracted example is Scranton, Pennsylvania → 1,777 sq mi (4,602 km2), 567,559 (US: 100th). Use these groups to spot repeated connection types before inspecting the individual relationships.
Scranton, Pennsylvania
Top relations
• City· 2
Scranton, Pennsylvania → 25.54 sq mi (66.14 km2), 76,328
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 44 structured relationships around Scranton, Pennsylvania. Examples in this analysis include Scranton, Pennsylvania → Area codes → 570 and 272 and Scranton, Pennsylvania → Country → United States. The table shows each extracted connection, where it came from and its confidence.
1st in Northeastern Pennsylvania 6th in Pennsylvania
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infobox
Scranton, Pennsylvania
• Summer (DST)
UTC– 04:00 (EDT)
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infobox
Scranton, Pennsylvania
• Type
Mayor-Council
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infobox
Scranton, Pennsylvania
• Urban
366,713 (US: 113th)
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infobox
Scranton, Pennsylvania
• Urban density
2,261/sq mi (873.1/km2)
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infobox
Scranton, Pennsylvania
• Water
0.23 sq mi (0.60 km2)
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infobox
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Scranton, Pennsylvania bring nearby vocabulary together. In this analysis, examples include Scranton, Electric and Area. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Scranton, Pennsylvania
Scranton
Electric
Area
Center
School
Mine
Built
Coal
Wilkes-barre
New
Company
Downtown
scranton, pennsylvania
States
United
North
Scranton
Electric
State
Area
New
Railroad
Center
School
Mine
second a class city
Scranton
Pennsylvania
Electric
New
York
County
Lackawanna
North
States
United
Railroad
Mine
county seat
Lackawanna
States
Pennsylvania
United
State
Scranton
Mine
Center
History
Including
Iron
Scranton's
lackawanna county, pennsylvania
Lackawanna
Scranton
States
United
Coal
New
North
Pennsylvania
Steel
State
Iron
Center
northeastern pennsylvania
States
United
North
Scranton
Electric
State
New
Railroad
Mine
Built
York
Area
new york city
New
York
Scranton
Pennsylvania
Electric
City
County
Including
Lackawanna
Railroad
North
States
lackawanna river
Scranton
Coal
New
Pennsylvania
Steel
Iron
Center
York
Railroad
Company
Mine
Built
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Scranton, Pennsylvania, one of the stronger structural bridges in this analysis connects Scranton, Pennsylvania with History. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Scranton, Pennsylvania
Nodes380
Edges379
Triples44
Avg. degree1.99
Density0.005263
Components1
Source & methodology
TTTA analyzes the structure around Scranton, Pennsylvania to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Geography, Community & Culture, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
