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Hurricane Matthew: History & Measurement
Hurricane Matthew was a powerful and devastating tropical cyclone which caused catastrophic damage and a humanitarian crisis in Haiti, as well as widespread devastation across Cuba, the Bahamas, and the southeastern United States. The deadliest Atlantic hurricane since Hurricane Stan in 2005, and the first Category 5 Atlantic hurricane since Felix in…
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Hurricane Matthew topic overview
The analysis highlights History and Measurement as prominent areas in the source structure around Hurricane Matthew.
Related topics
273
Source areas
10
Connected nodes
283
Extracted relationships
47
Concept neighborhoods
68
Bridge connections
283
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.
Preparations · 94 topics
Overview · 93 topics
Impact · 41 topics
Haiti · 17 topics
Meteorological history · 15 topics
Aftermath · 5 topics
Dominican Republic · 4 topics
United States · 2 topics
Cuba · 1 topics
Jamaica · 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.
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 Hurricane Matthew 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 Hurricane Matthew shows recurring relationship patterns in the source. For example, Hurricane Matthew → AF, Affairs, Air Force, Armed Forces News Service, Copernicus Emergency Management Service, EMSR186, Haiti, Hurricane MatthewTaylor, Joint Base McGuire-Dix-Lakehurst Public, Little Rock AFB, Matthew, October, Retrieved October, Scalf, Southeastern United States, SRA Mercedes, The NHC's, Tropical Cyclone Matthew, TSG Ralph, US Another extracted example is Hurricane Matthew → Baracoa, Canadian, Category, Coastal, Cuba, Damages, Despite, Granma Province, Guantánamo Province, Majayara, Moa, Nearly, November, October, Sherritt International, Sierra Maestras, The, Toa, US. Use these groups to spot repeated connection types before inspecting the individual relationships.
Hurricane Matthew
Top relations
related to External links· 20
Hurricane Matthew → AF, Affairs, Air Force, Armed Forces News Service, Copernicus Emergency Management Service, EMSR186, Haiti, Hurricane MatthewTaylor, Joint Base McGuire-Dix-Lakehurst Public, Little Rock AFB, Matthew, October, Retrieved October, Scalf, Southeastern United States, SRA Mercedes, The NHC's, Tropical Cyclone Matthew, TSG Ralph, US
related to Cuba· 19
Hurricane Matthew → Baracoa, Canadian, Category, Coastal, Cuba, Damages, Despite, Granma Province, Guantánamo Province, Majayara, Moa, Nearly, November, October, Sherritt International, Sierra Maestras, The, Toa, US
Areas affected· 1
Hurricane Matthew → Windward Islands, Leeward Antilles, Venezuela, Colombia, Greater Antilles, Lucayan Archipelago, Southeastern United States, Atlantic Canada
Damage· 1
Hurricane Matthew → $16.5 billion (2016 USD)
Dissipated· 1
Hurricane Matthew → October 10, 2016
Extratropical· 1
Hurricane Matthew → October 9, 2016
Fatalities· 1
Hurricane Matthew → 731 total
Formed· 1
Hurricane Matthew → September 28, 2016
Highest winds· 1
Hurricane Matthew → 165 mph (270 km/h)
Lowest pressure· 1
Hurricane Matthew → 934 mbar (hPa); 27.58 inHg
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.
Hurricane Matthew relationships Subject–Predicate–Object triples
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 47 structured relationships around Hurricane Matthew. Examples in this analysis include Hurricane Matthew → Areas affected → Windward Islands, Leeward Antilles, Venezuela, Colombia, Greater Antilles, Lucayan Archipelago, Southeastern United States, Atlantic Canada and Hurricane Matthew → Damage → $16.5 billion (2016 USD). The table shows each extracted connection, where it came from and its confidence.
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 Hurricane Matthew bring nearby vocabulary together. In this analysis, examples include Category, Matthew and October. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Hurricane Matthew
Category
Matthew
October
Cuba
Bahamas
Southeastern
States
Tropical
Storm
United
Mph
North
hurricane matthew
Category
Matthew
October
Cuba
September
Bahamas
Southeastern
States
Tropical
Storm
United
Mph
haiti
October
Us
Matthew
States
United
Across
Bahamas
Islands
Southeastern
Cuba
Hurricane
Tropical
cuba
Hurricane
Southeastern
Damage
Category
Bahamas
Us
October
States
Tropical
United
Coast
Florida
the bahamas
Islands
Southeastern
States
United
Hurricane
Damage
Matthew
Several
Cuba
Tropical
Km
Mph
atlantic hurricane
Category
Matthew
October
Cuba
Bahamas
Southeastern
States
Storm
United
Mph
North
South
hurricane stan
Category
Matthew
October
Cuba
Bahamas
Southeastern
States
Storm
United
Mph
North
South
hurricane
Category
Matthew
October
Cuba
Bahamas
Southeastern
States
Storm
United
Mph
North
South
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 Hurricane Matthew, one of the stronger structural bridges in this analysis connects Hurricane Matthew with Preparations. 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
Hurricane Matthew — Preparations· splits 189 ⟂ 95Hurricane Matthew — Overview· splits 190 ⟂ 94Hurricane Matthew — Impact· splits 242 ⟂ 42Hurricane Matthew — Haiti· splits 266 ⟂ 18Hurricane Matthew — Meteorological history· splits 268 ⟂ 16Hurricane Matthew — Aftermath· splits 278 ⟂ 6Hurricane Matthew — Dominican Republic· splits 279 ⟂ 5Hurricane Matthew — United States· splits 281 ⟂ 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.
Hurricane Matthew
Nodes284
Edges283
Triples47
Avg. degree1.99
Density0.007042
Components1
Source & methodology
TTTA analyzes the structure around Hurricane Matthew to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History & Measurement, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
