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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
272
Source areas
10
Connected nodes
282
Extracted relationships
26
Related term clusters
68
Bridge connections
282

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 · 40 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.

Areas affected
Windward Islands, Leeward Antilles, Venezuela, Colombia, Greater Antilles, Lucayan Archipelago, Southeastern United States, Atlantic Canada
Damage
$16.5 billion (2016 USD)
Dissipated
October 10, 2016
Extratropical
October 9, 2016
Fatalities
731 total
Formed
September 28, 2016

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Explore all related topics Closing gaps

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.

Overview

Meteorological history

Preparations

Jamaica

Haiti

Dominican Republic

United States

Impact

Cuba

Aftermath

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How Hurricane Matthew connects Entity context

The extracted context around Hurricane Matthew shows recurring relationship patterns in the source. For example, Hurricane Matthew → Baracoa, Canadian, Category, Coastal, Cuba, Damages, Despite, Granma Province, Guantánamo Province, Majayara, Moa, Nearly, November, October, Sherritt International, Sierra Maestras, Toa, US Another extracted example is Hurricane Matthew → Windward Islands, Leeward Antilles, Venezuela, Colombia, Greater Antilles, Lucayan Archipelago, Southeastern United States, Atlantic Canada. Use these groups to spot repeated connection types before inspecting the individual relationships.

Hurricane Matthew

Top relations

related to Cuba · 18
Hurricane Matthew → Baracoa, Canadian, Category, Coastal, Cuba, Damages, Despite, Granma Province, Guantánamo Province, Majayara, Moa, Nearly, November, October, Sherritt International, Sierra Maestras, 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

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

october matthew hurricane people storm damage haiti across florida carolina 000 winds north flooding south category coast also cuba united

Hurricane Matthew relationships Subject–Predicate–Object triples

TTTA extracted 26 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.

SubjectPredicateObjectConfidenceSrc
Hurricane MatthewAreas affectedWindward Islands, Leeward Antilles, Venezuela, Colombia, Greater Antilles, Lucayan Archipelago, Southeastern United States, Atlantic Canada1.00infobox
Hurricane MatthewDamage$16.5 billion (2016 USD)1.00infobox
Hurricane MatthewDissipatedOctober 10, 20161.00infobox
Hurricane MatthewExtratropicalOctober 9, 20161.00infobox
Hurricane MatthewFatalities731 total1.00infobox
Hurricane MatthewFormedSeptember 28, 20161.00infobox
Hurricane MatthewHighest winds165 mph (270 km/h)1.00infobox
Hurricane MatthewLowest pressure934 mbar (hPa); 27.58 inHg1.00infobox
Hurricane Matthewrelated to CubaCoastal0.60section
Hurricane Matthewrelated to CubaGranma Province0.60section
Hurricane Matthewrelated to CubaCuba0.60section
Hurricane Matthewrelated to CubaOctober0.60section

Related concept clusters Related term clusters

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

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 188 ⟂ 95
Hurricane Matthew — Overview · splits 189 ⟂ 94
Hurricane Matthew — Impact · splits 242 ⟂ 41
Hurricane Matthew — Haiti · splits 265 ⟂ 18
Hurricane Matthew — Meteorological history · splits 267 ⟂ 16
Hurricane Matthew — Aftermath · splits 277 ⟂ 6
Hurricane Matthew — Dominican Republic · splits 278 ⟂ 5
Hurricane Matthew — United States · splits 280 ⟂ 3

Map overview Semantic statistics

Hurricane Matthew

Nodes283
Edges282
Triples26
Avg. degree1.99
Density0.007067
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.

Source: Wikipedia — Hurricane Matthew · EN edition · Analysis: TopicsToTalkAbout

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