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Crowdsourcing: History, Community, Applications & Art

Crowdsourcing involves a large group of dispersed participants contributing or producing goods or services—including ideas, votes, micro-tasks, and finances—for payment or as volunteers. Contemporary crowdsourcing often involves digital platforms to attract and divide work between participants to achieve a cumulative result. Crowdsourcing is not limited…

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Crowdsourcing topic overview

The analysis highlights History, Community, Applications and Art as prominent areas in the source structure around Crowdsourcing. 1 topic appears in more than one source area, which can help identify connections that are less obvious in a linear reading.

Related topics
260
Source areas
7
Connected nodes
268
Extracted relationships
477
Concept neighborhoods
35
Bridge connections
268

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.

Historical examples · 63 topics
Overview · 62 topics
Applications · 59 topics
Methods · 51 topics
Limitations and controversies · 16 topics
Definitions · 7 topics
Demographics of the crowd · 3 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

Definitions

Historical examples

Applications

Methods

Demographics of the crowd

Limitations and controversies

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 Crowdsourcing connects Entity context

The extracted context around Crowdsourcing shows recurring relationship patterns in the source. For example, Crowdsourcing → Amazon Mechanical Turk, Berkeley, Bibliothèque, BP, British, By, C'était Paris, California, Canada, Caribbean, Casting, Children, China, Connecting, Current Charts, Deepwater Horizon, Deepwater Horizon Response, Did You Feel It, Do, Dream Another extracted example is Crowdsourcing → Amazon Mechanical Turk, Amazon's Mechanical Turk, An, Community-based, Complex, Creative, CrowdEC, Crowdshipping, Crowdsolving, Crowdsourcing-Based Optimization, Due, EC, GPS, However, It, Jim Gray, Macro-tasks, Macrowork, Mechanical Turk, Microwork. Use these groups to spot repeated connection types before inspecting the individual relationships.

Crowdsourcing

Top relations

related to Timeline of crowdsourcing examples · 108
Crowdsourcing → Amazon Mechanical Turk, Berkeley, Bibliothèque, BP, British, By, C'était Paris, California, Canada, Caribbean, Casting, Children, China, Connecting, Current Charts, Deepwater Horizon, Deepwater Horizon Response, Did You Feel It, Do, Dream
related to Other types · 34
Crowdsourcing → Amazon Mechanical Turk, Amazon's Mechanical Turk, An, Community-based, Complex, Creative, CrowdEC, Crowdshipping, Crowdsolving, Crowdsourcing-Based Optimization, Due, EC, GPS, However, It, Jim Gray, Macro-tasks, Macrowork, Mechanical Turk, Microwork
see also · 32
Crowdsourcing → Aggregation, Amateur, Citizen, Collaborative, Collection, Collective, Computer, Crowds, Digital-communication, European, Form, Google, Group, Internet, Intersection, James SurowieckiCrowdsource, Method, Model, NASACollaborative, Online
related to Other examples · 28
Crowdsourcing → Agriculture, Air, Australia, Boye Brogeland, Cheating, Crowdsource, Engineering, Geography, Healthcare, In, IOT, Libraries, Live, Many, National Library, Newspaper, OCR, Open-source, OpenStreetMap, PGI
related to Demographics of the crowd · 27
Crowdsourcing → Additionally, Amazon Mechanical Turk, American, Approximately, Bangladesh, Black, Close, Democrats, However, In, In November, India, Indian, Indonesia, Ipeirotis, Mechanical Turk, Microworkers, More, MTurk, Politics
related to Early competitions · 19
Crowdsourcing → Alkali, Devanagari, During, Fourneyron's, French, Great Depression, In, Indian, Leblanc, Longitude Prize, Mathematical Tables Project, Montyon Prizes, Nicolas Appert, One, Ra, The British, The French, These, Thousands
related to Inducement prize contests · 18
Crowdsourcing → An, Another, DARPA, Europe, IBM's, Innovation Jam, Internet-based, It, MIT, Netflix Prize, Netflix's, People, Tag Challenge, The, United States, US, US State Department, Web-based
related to Crowdvoting · 16
Crowdsourcing → Acme, Coca-Cola, Crowdvoting, Domino's Pizza, Heineken, In, One, Ranking, Sam Adams, Some, T-shirts, The Iowa Electronic Market, They, This, Threadless, What
related to Labor-related concerns · 14
Crowdsourcing → Amazon Mechanical Turk, Because, However, In, India, Mechanical Turk, MTurk, Overall, Some, They, United States, United States Turk, When Facebook, Workers
related to Definitions · 13
Crowdsourcing → Brabham, Daren, Guth, Howe, Internet, Jeff Howe, Kristen, Mark Robinson, Merriam-Webster, OED's, The, The Oxford English Dictionary, Wired

Important terminology

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

Important terminology

used ideas data project crowd also online research people workers users information projects large participants public turk work tasks mechanical

Crowdsourcing relationships Subject–Predicate–Object triples

TTTA extracted 477 structured relationships around Crowdsourcing. Examples in this analysis include Crowdsourcing → is a → portmanteau of and Crowdsourcing → is a → 2009 DARPA balloon experiment. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Crowdsourcingis aportmanteau of0.90text
Crowdsourcingis a2009 DARPA balloon experiment0.90text
Crowdsourcingis aESP game0.90text
Crowdsourcingis alack of collaboration tools0.90text
scienceinstance ofon topics0.80text
manufacturinginstance ofon topics0.80text
biotechinstance ofon topics0.80text
and medicineinstance ofon topics0.80text
Amazon Mechanical Turk or CloudResearch to aid their research projects by crowdsourcing some aspects of the research processinstance ofproductive manner.Researchers have used crowdsourcing systems0.80text
such as data collectioninstance ofproductive manner.Researchers have used crowdsourcing systems0.80text
parsinginstance ofproductive manner.Researchers have used crowdsourcing systems0.80text
and evaluation to the publicinstance ofproductive manner.Researchers have used crowdsourcing systems0.80text

Related concept clusters Concept neighborhoods

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

  • Crowdsourcing
    • Used
    • Research
    • Data
    • Also
    • Use
    • Public
    • Ideas
    • Work
    • Quality
    • Needed
    • Users
    • Allows
  • crowdsourcing
    • Used
    • Research
    • Data
    • Also
    • Use
    • Public
    • Ideas
    • Work
    • Quality
    • Needed
    • Users
    • Allows
  • digital platforms
    • Open
    • Platform
    • Online
    • Social
    • Work
    • Research
    • Data
    • Process
    • Use
    • Using
    • Participants
    • Mechanical
  • crowd
    • Problems
    • Work
    • Product
    • Contributions
    • Used
    • Social
    • Using
    • Public
    • Information
    • Online
    • People
    • Also
  • lego ideas
    • Idea
    • New
    • Work
    • Allows
    • Platform
    • People
    • Quality
    • Large
    • Platforms
    • Many
    • Often
    • Social
  • large emergency event digital information repository
    • Participants
    • Needed
    • Project
    • Problems
    • Crowdsourced
    • Data
    • Used
    • People
    • Citation
    • Projects
    • Ideas
    • Allows
  • online volunteers
    • Data
    • Participants
    • Platform
    • Platforms
    • Needed
    • Project
    • Public
    • Open
    • People
    • Research
    • Social
    • Projects
  • online community
    • Data
    • Participants
    • Platform
    • Platforms
    • Needed
    • Project
    • Public
    • Open
    • People
    • Research
    • Social
    • Projects

Connections between topic areas Semantic bridges

For Crowdsourcing, one of the stronger structural bridges in this analysis connects Crowdsourcing with Historical examples. 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
Crowdsourcing — Historical examples · splits 205 ⟂ 64
Crowdsourcing — Overview · splits 206 ⟂ 63
Crowdsourcing — Applications · splits 209 ⟂ 60
Crowdsourcing — Methods · splits 217 ⟂ 52
Crowdsourcing — Limitations and controversies · splits 252 ⟂ 17
Crowdsourcing — Definitions · splits 261 ⟂ 8
Crowdsourcing — Demographics of the crowd · splits 265 ⟂ 4

Map overview Semantic statistics

Crowdsourcing

Nodes269
Edges268
Triples477
Avg. degree1.99
Density0.007435
Components1

Source & methodology

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

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

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