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CrimeStat: Products, Functionality & Development

CrimeStat is a crime mapping software program. CrimeStat is Windows-based program that conducts spatial and statistical analysis and is designed to interface with a geographic information system (GIS). The program is developed by Ned Levine & Associates under the direction of Ned Levine, with funding by the National Institute of Justice (NIJ), an agency…

Language: English [EN]
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CrimeStat topic overview

The analysis highlights Products, Functionality and Development as prominent areas in the source structure around CrimeStat.

Related topics
31
Source areas
5
Connected nodes
36
Extracted relationships
82
Concept neighborhoods
12
Bridge connections
36

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.

Functionality · 22 topics
Overview · 4 topics
Development · 3 topics
Reviews and examples · 1 topics
Shortcomings · 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.

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

Development

Functionality

Shortcomings

Reviews and examples

Advanced semantic analysis

Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.

How CrimeStat connects Entity context

The extracted context around CrimeStat shows recurring relationship patterns in the source. For example, CrimeStat → Ascii, Currently, DBF, Esri SHP, GIS, Graphical, MapInfo Interchange Format, MIF/MID, Non-graphical, Screen, Surfer, These, Windows DAT Another extracted example is CrimeStat → Analysts, Another, Baltimore County, Baltimore County Police, Crime, Data Driven Approaches, DDACTS, Nearest Neighbor Hierarchical Spatial, Police, Preliminary, The, The County's DDACTS, Traffic Safety. Use these groups to spot repeated connection types before inspecting the individual relationships.

CrimeStat

Top relations

related to Output · 13
CrimeStat → Ascii, Currently, DBF, Esri SHP, GIS, Graphical, MapInfo Interchange Format, MIF/MID, Non-graphical, Screen, Surfer, These, Windows DAT
related to Use of CrimeStat by Baltimore County Police analysts · 13
CrimeStat → Analysts, Another, Baltimore County, Baltimore County Police, Crime, Data Driven Approaches, DDACTS, Nearest Neighbor Hierarchical Spatial, Police, Preliminary, The, The County's DDACTS, Traffic Safety
related to Statistical routines · 12
CrimeStat → Distance-based, Geary, Getis's, Getis-Ord, Getis-Ord Global, Moran, Moran's, Primary File, Ripley's, Secondary File, Spatial, The
related to Development · 10
CrimeStat → August, Honolulu, In, July, Justice, National Institute, Ned Levine, Pointstat, The, Unix-based
related to Data setup · 8
CrimeStat → Ascii, Distance, GIS, Manhattan, Primary File, Secondary File, Several, The
related to Further reading · 8
CrimeStat → Crime, Encyclopedia, Geographic Information Science, Geographical Analysis, Levine, Shekhar, Springer, Xiong
related to Shortcomings · 7
CrimeStat → Because CrimeStat, Finally, GeoDa, GIS, GUI, Some, Unlike
related to Ancillary CrimeStat development · 5
CrimeStat → August, CrimeStat Libraries, In, NET, Version
related to Reviews and examples · 2
CrimeStat → Examples, Reviews
is a · 1
CrimeStat → crime mapping software program

Important terminology

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

Important terminology

program crime spatial analysis routines use police identify travel objects analysts also traffic many gis data statistical version used areas

CrimeStat relationships Subject–Predicate–Object triples

TTTA extracted 82 structured relationships around CrimeStat. Examples in this analysis include CrimeStat → is a → crime mapping software program and traffic stops → instance of → police analysts will examine information captured from other police sources. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
CrimeStatis acrime mapping software program0.90text
traffic stopsinstance ofpolice analysts will examine information captured from other police sources0.80text
Field Interview Reportsinstance ofpolice analysts will examine information captured from other police sources0.80text
and License Plate Readers to determine if a contact was made with a potential offender.Police have also used CrimeStat's Crime Travel Demand model to identify road networks used by drivers under the influenceinstance ofpolice analysts will examine information captured from other police sources0.80text
CrimeStatrelated to Ancillary CrimeStat developmentIn0.60section
CrimeStatrelated to Ancillary CrimeStat developmentNET0.60section
CrimeStatrelated to Ancillary CrimeStat developmentVersion0.60section
CrimeStatrelated to Ancillary CrimeStat developmentCrimeStat Libraries0.60section
CrimeStatrelated to Ancillary CrimeStat developmentAugust0.60section
CrimeStatrelated to Data setupGIS0.60section
CrimeStatrelated to Data setupThe0.60section
CrimeStatrelated to Data setupAscii0.60section

Related concept clusters Concept neighborhoods

The concept neighborhoods around CrimeStat bring nearby vocabulary together. In this analysis, examples include Use, Analysis and Version. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • CrimeStat
    • Use
    • Analysis
    • Version
    • Spatial
    • Program
    • Mapping
    • Gis
    • Routines
    • Software
    • County
    • Levine
    • Statistical
  • crimestat
    • Use
    • Analysis
    • Version
    • Spatial
    • Program
    • Mapping
    • Gis
    • Routines
    • Software
    • County
    • Levine
    • Statistical
  • crime mapping
    • Software
    • Levine
    • Analysts
    • Identify
    • Crimestat
    • Police
    • Demand
    • Analysis
    • Used
    • Travel
    • Use
    • Program
  • cluster analysis
    • Spatial
    • Crimestat
    • Crime
    • Geographic
    • Events
    • Include
    • Information
    • Statistical
    • Gis
    • Objects
    • Data
    • Identify
  • spatial autocorrelation
    • Identify
    • Routines
    • Events
    • Include
    • Modeling
    • Statistical
    • Objects
    • Space
    • Data
    • Used
    • Analysts
    • Police
  • geographic information system
    • Information
    • Space
    • Events
    • Include
    • Modeling
    • Statistical
    • Gis
    • Spatial
    • Data
    • Identify
    • Traffic
    • Analysts
  • geographic profiling
    • Information
    • Events
    • Include
    • Modeling
    • Statistical
    • Gis
    • Space
    • Spatial
    • Data
    • Identify
    • Routines
    • Program
  • text file
    • File
    • Text
    • Output
    • Include
    • Routines
    • Many
    • Also
    • Use
    • Spatial
    • Program

Connections between topic areas Semantic bridges

For CrimeStat, one of the stronger structural bridges in this analysis connects CrimeStat with Functionality. 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
CrimeStat — Functionality · splits 14 ⟂ 23
CrimeStat — Overview · splits 32 ⟂ 5
CrimeStat — Development · splits 33 ⟂ 4

Map overview Semantic statistics

CrimeStat

Nodes37
Edges36
Triples82
Avg. degree1.95
Density0.054054
Components1

Source & methodology

TTTA analyzes the structure around CrimeStat to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Products, Functionality & Development, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — CrimeStat · EN edition · Analysis: TopicsToTalkAbout

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