White-Jacket; or, The World in a Man-of-War is the fifth book by American writer Herman Melville, first published in London in 1850. The book is based on the author's fourteen months' service in the United States Navy, aboard the frigate USS Neversink (actually USS United States).
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White-Jacket topic overview
The analysis highlights Characters, History, Literary Connections and Measurement as prominent areas in the source structure around White-Jacket.
Related topics
22
Source areas
6
Connected nodes
28
Extracted relationships
121
Concept neighborhoods
9
Bridge connections
28
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.
Legal impact · 8 topics
Overview · 6 topics
White-Jacket and the log of the USS United States · 4 topics
Characters · 2 topics
Publication history · 1 topics
References and further reading · 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.
Author
Herman Melville
Genre
Adventure fiction
Followed by
Moby-Dick
Language
English
Media type
Print
Preceded by
Redburn
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 White-Jacket 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 White-Jacket shows recurring relationship patterns in the source. For example, White-Jacket → As, August, Avery, Battle, But, But Mad Jack, Cape Horn, Chapter, Chase, Englishman John, First, First Captain, Foremost, He, In, Jack Chase, Lantham, Latham, Louis, Lt Another extracted example is White-Jacket → Brazil, British, Chase, Claret, Coffee, Don Pedro II, Emperor, Guinea, He, Jack, LemsfordWilliamsWooloo, Navy, Nord, Norfolk, Polynesian, RevolverOld CombustiblesChaplainCuticle, SurgeonShakingsBland, Tawney, This, Ushant. Use these groups to spot repeated connection types before inspecting the individual relationships.
White-Jacket
Top relations
related to White-Jacket and the log of the USS United States· 37
White-Jacket → As, August, Avery, Battle, But, But Mad Jack, Cape Horn, Chapter, Chase, Englishman John, First, First Captain, Foremost, He, In, Jack Chase, Lantham, Latham, Louis, Lt
related to Characters· 22
White-Jacket → Brazil, British, Chase, Claret, Coffee, Don Pedro II, Emperor, Guinea, He, Jack, LemsfordWilliamsWooloo, Navy, Nord, Norfolk, Polynesian, RevolverOld CombustiblesChaplainCuticle, SurgeonShakingsBland, Tawney, This, Ushant
has impact· 18
White-Jacket → At, Catesby Jones, Hale, He, In, John Wilkes Booth, Jones, Lucy, Melville, Melville's, New Hampshire Senator John, President Abraham Lincoln, President Millard Fillmore, September, The, Thomas, United States Congress, USS United States
related to overview· 16
White-Jacket → American, At, Based, Billy Budd, Bros, Cape Horn, Congress, Due, Harper, He, Melville, Melville's, Navy, The, This, USS United States
related to history· 9
White-Jacket → Brothers, February, Harper, London, March, Melville, New York, Redburn, Richard Bentley
related to References and further reading· 6
White-Jacket → Evanston, Howard, Melville's White-Jacket, Northwestern University Press, The Tailoring, Vincent
related to External links· 4
White-Jacket → Google Books, Internet Archive, LibriVox, Project GutenbergWhite-Jacket
Published· 2
White-Jacket → 1850 (London: Richard Bentley), 1850 (New York: Harper & Brothers)
Author· 1
White-Jacket → Herman Melville
Followed by· 1
White-Jacket → Moby-Dick
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
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 121 structured relationships around White-Jacket. Examples in this analysis include White-Jacket → Author → Herman Melville and White-Jacket → Followed by → Moby-Dick. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
White-Jacket
Author
Herman Melville
1.00
infobox
White-Jacket
Followed by
Moby-Dick
1.00
infobox
White-Jacket
Genre
Adventure fiction
1.00
infobox
White-Jacket
Language
English
1.00
infobox
White-Jacket
Media type
Print
1.00
infobox
White-Jacket
Preceded by
Redburn
1.00
infobox
White-Jacket
Publication place
United States, England
1.00
infobox
White-Jacket
Published
1850 (London: Richard Bentley)
1.00
infobox
White-Jacket
Published
1850 (New York: Harper & Brothers)
1.00
infobox
White-Jacket
has impact
At
0.60
section
White-Jacket
has impact
New Hampshire Senator John
0.60
section
White-Jacket
has impact
Hale
0.60
section
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 White-Jacket bring nearby vocabulary together. In this analysis, examples include Naval, First and London. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
White-Jacket
Naval
First
London
Published
Log
Melville
Crew
Ship
Melville's
Herman
Aboard
Based
white-jacket
Naval
First
London
Published
Log
Melville
Crew
Ship
Melville's
Herman
Aboard
Based
herman melville
London
Published
First
Sea
Chapter
Jack
White-jacket
Melville
Moby-dick
Uss
Aboard
Based
white-jacket and the log of the uss united states
United
Frigate
Uss
August
Naval
Ship
Time
First
London
Published
Log
White-jacket
united states navy
United
Frigate
Uss
Flogging
Log
Time
August
Member
Sailors
Melville's
Crew
Moby-dick
uss united states
United
Frigate
Uss
Time
Flogging
Log
August
Melville's
Moby-dick
Member
Sailors
White-jacket
flogging
Naval
Sea
Frigate
United
Melville's
States
Herman
London
Moby-dick
Published
Member
Sailors
moby-dick
Novel
Published
Flogging
Jacket
Member
Sailors
Time
Hands
Uss
Naval
Sea
One
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 White-Jacket, one of the stronger structural bridges in this analysis connects White-Jacket with Legal impact. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Min side: 3
White-Jacket — Legal impact· splits 20 ⟂ 9White-Jacket — Overview· splits 22 ⟂ 7White-Jacket — White-Jacket and the log of the USS United States· splits 24 ⟂ 5White-Jacket — Characters· splits 26 ⟂ 3
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
White-Jacket
Nodes29
Edges28
Triples121
Avg. degree1.93
Density0.068966
Components1
Source & methodology
TTTA analyzes the structure around White-Jacket to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Characters, History, Literary Connections & Measurement, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
