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Human Resource Machine: Companies, Reception & Development

Human Resource Machine is a visual programming-based puzzle video game developed by Tomorrow Corporation. The game was released for Microsoft Windows, OS X and Wii U in 2015, being additionally released for Linux in March 2016, for iOS in June 2016, for Android in December 2016 and for the Nintendo Switch in March 2017. Human Resource Machine uses the…

Language: English [EN]
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Human Resource Machine topic overview

The analysis highlights Companies, Reception and Development as prominent areas in the source structure around Human Resource Machine.

Related topics
28
Source areas
4
Connected nodes
32
Extracted relationships
46
Concept neighborhoods
14
Bridge connections
32

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.

Overview · 13 topics
Reception · 6 topics
Development · 5 topics
Gameplay · 4 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.

Genre
Puzzle
Artists
Kyle Gabler · Kyle Gray
Composer
Kyle Gabler
Designers
Kyle Gabler · Kyle Gray
Developer
Tomorrow Corporation
Mode
Single-player

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

Gameplay

Development

Reception

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 Human Resource Machine connects Entity context

The extracted context around Human Resource Machine shows recurring relationship patterns in the source. For example, Human Resource Machine → Allan Blomquist, Boy, Gabler, Goo, Hooke's, In, Kyle Gabler, Kyle Gray, Little Inferno, Ron Carmel, The, They, Tomorrow Corporation, World Another extracted example is Human Resource Machine → Android, iOS, Linux, Microsoft Windows, Nintendo Switch, OS X, Wii U. Use these groups to spot repeated connection types before inspecting the individual relationships.

Human Resource Machine

Top relations

related to Development · 14
Human Resource Machine → Allan Blomquist, Boy, Gabler, Goo, Hooke's, In, Kyle Gabler, Kyle Gray, Little Inferno, Ron Carmel, The, They, Tomorrow Corporation, World
Platforms · 7
Human Resource Machine → Android, iOS, Linux, Microsoft Windows, Nintendo Switch, OS X, Wii U
related to Sequel · 5
Human Resource Machine → August, Billion Humans, In January, The, Tomorrow Corporation
Release · 4
Human Resource Machine → EU: December 3, 2015, NA: March 16, 2017, NA: October 29, 2015, PAL: March 23, 2017
related to External links · 3
Human Resource Machine → MobyGames, Official, Resource Machine
Artists · 2
Human Resource Machine → Kyle Gabler, Kyle Gray
Designers · 2
Human Resource Machine → Kyle Gabler, Kyle Gray
Publishers · 2
Human Resource Machine → Experimental Gameplay Group (iOS), Tomorrow Corporation
Composer · 1
Human Resource Machine → Kyle Gabler
Developer · 1
Human Resource Machine → Tomorrow Corporation

Important terminology

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

Important terminology

player game puzzle human resource machine instructions also language avatar visual office outbox assembly puzzles task tomorrow corporation programming list

Human Resource Machine relationships Subject–Predicate–Object triples

TTTA extracted 46 structured relationships around Human Resource Machine. Examples in this analysis include Human Resource Machine → Artists → Kyle Gabler and Human Resource Machine → Artists → Kyle Gray. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Human Resource MachineArtistsKyle Gabler1.00infobox
Human Resource MachineArtistsKyle Gray1.00infobox
Human Resource MachineComposerKyle Gabler1.00infobox
Human Resource MachineDesignersKyle Gabler1.00infobox
Human Resource MachineDesignersKyle Gray1.00infobox
Human Resource MachineDeveloperTomorrow Corporation1.00infobox
Human Resource MachineGenrePuzzle1.00infobox
Human Resource MachineModeSingle-player1.00infobox
Human Resource MachinePlatformsMicrosoft Windows1.00infobox
Human Resource MachinePlatformsOS X1.00infobox
Human Resource MachinePlatformsWii U1.00infobox
Human Resource MachinePlatformsLinux1.00infobox
Human Resource MachinePlatformsiOS1.00infobox
Human Resource MachinePlatformsAndroid1.00infobox
Human Resource MachinePlatformsNintendo Switch1.00infobox
Human Resource MachineProgrammerAllan Blomquist1.00infobox
Human Resource MachinePublishersTomorrow Corporation1.00infobox
Human Resource MachinePublishersExperimental Gameplay Group (iOS)1.00infobox
Human Resource MachineReleaseNA: October 29, 20151.00infobox
Human Resource MachineReleaseEU: December 3, 20151.00infobox
Human Resource MachineReleaseNA: March 16, 20171.00infobox
Human Resource MachineReleasePAL: March 23, 20171.00infobox
Human Resource Machineis avisual programming-based puzzle video game developed by Tomorrow Corporation0.90text

Related concept clusters Concept neighborhoods

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

  • puzzle
    • Player
    • Avatar
    • Inbox
    • One
    • Tomorrow
    • Outbox
    • Programming
    • Puzzles
    • Task
    • Also
    • Instructions
    • Android
  • video game
    • Wii
    • Gabler
    • Little
    • Programming
    • Also
    • Human
    • Machine
    • Puzzle
    • Resource
    • Android
    • Ios
    • Linux
  • Human Resource Machine
    • Machine
    • Resource
    • Corporation
    • Tomorrow
    • Developed
    • Development
    • Concept
    • Gabler
    • Assembly
    • Visual
    • Game
    • Language
  • human resource machine
    • Machine
    • Resource
    • Corporation
    • Tomorrow
    • Developed
    • Development
    • Concept
    • Gabler
    • Assembly
    • Visual
    • Game
    • Language
  • visual programming
    • Programming
    • Visual
    • Assembly
    • Puzzles
    • Language
    • Human
    • Machine
    • Puzzle
    • Resource
    • Player
    • Developed
    • Sequel
  • tomorrow corporation
    • Tomorrow
    • Developed
    • Development
    • Sequel
    • Gabler
    • Human
    • Machine
    • Resource
    • Android
    • Ios
    • Linux
    • Microsoft
  • assembly language
    • Language
    • Office
    • Concepts
    • Instructions
    • Floor
    • Programming
    • Simple
    • Visual
    • List
    • Human
    • Machine
    • Resource
  • wii u
    • Android
    • Ios
    • Linux
    • Microsoft
    • Game
    • Development
    • Released
    • Sequel
    • Corporation
    • Gabler
    • One
    • Tomorrow

Connections between topic areas Semantic bridges

For Human Resource Machine, one of the stronger structural bridges in this analysis connects Human Resource Machine with Overview. 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
Human Resource Machine — Overview · splits 19 ⟂ 14
Human Resource Machine — Reception · splits 26 ⟂ 7
Human Resource Machine — Development · splits 27 ⟂ 6
Human Resource Machine — Gameplay · splits 28 ⟂ 5

Map overview Semantic statistics

Human Resource Machine

Nodes33
Edges32
Triples46
Avg. degree1.94
Density0.060606
Components1

Source & methodology

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

Source: Wikipedia — Human Resource Machine · EN edition · Analysis: TopicsToTalkAbout

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