Find related topics. | Discover entities. | See connections. | Build a topical map.
Building topical map: Starting…
Data broker: Companies & Art
A data broker is an individual or company that specializes in collecting personal data (such as income, ethnicity, political beliefs, or geolocation data) or data about people, mostly from public records but sometimes sourced privately, and selling or licensing such information to third parties for a variety of uses. Sources, usually Internet-based since…
Use the mouse wheel or two fingers (on touchscreens) to zoom in and out of the map.
More settings
Data broker topic overview
The analysis highlights Companies and Art as prominent areas in the source structure around Data broker.
Related topics
130
Source areas
4
Connected nodes
134
Extracted relationships
129
Concept neighborhoods
36
Bridge connections
134
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 · 91 topics
Privacy issues and regulation · 23 topics
Fiction · 12 topics
Professional associations · 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.
Explore all related topics Closing gaps
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 Data broker 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 Data broker shows recurring relationship patterns in the source. For example, Data broker → Arrowverse, Baccano, Calculator, Carol, Central Intelligence Corporation, Chloe Sullivan, Daily Days, DC Comics, Durarara, Elean Duga, Examples, Felicity Smoak, Germain, Gustav St, In, Information, Izaya Orihara, Mass Effect, Neal Stephenson's, Nicholas Wayne Another extracted example is Data broker → Acxiom, CoreLogic, Data, Datalogix, Epsilon, Exactis, Experian, Fair Credit Reporting Act, FBI, Homeland Security, In, Intelius, Investigation, LiveRamp, Oracle, PeekYou, Recorded Future, Spokeo, The, The Federal Bureau. Use these groups to spot repeated connection types before inspecting the individual relationships.
Data broker
Top relations
related to Fiction· 27
Data broker → Arrowverse, Baccano, Calculator, Carol, Central Intelligence Corporation, Chloe Sullivan, Daily Days, DC Comics, Durarara, Elean Duga, Examples, Felicity Smoak, Germain, Gustav St, In, Information, Izaya Orihara, Mass Effect, Neal Stephenson's, Nicholas Wayne
related to In the United States· 26
Data broker → Acxiom, CoreLogic, Data, Datalogix, Epsilon, Exactis, Experian, Fair Credit Reporting Act, FBI, Homeland Security, In, Intelius, Investigation, LiveRamp, Oracle, PeekYou, Recorded Future, Spokeo, The, The Federal Bureau
related to overview· 14
Data broker → Credit, During, Fee-Based Information Services, How, However, IB, In, Information, Journal, Kelly Warnken, Operate Your Own Fee-based, Service, Start, The Information Brokers
related to Criticisms, consumer rights and breaches· 12
Data broker → Collection, Consumer Data, Data, Data Broker Industry, It, Marketing Purposes, Review, Sale, Their, Today, United States Senate Committee, Use
related to Privacy issues and regulation· 11
Data broker → European Union, Explicit, GDPR, General Data Protection Regulation, In, Information, The, There, Under GDPR, United States, US
related to Services· 11
Data broker → Brokers, Clients, Federal Trade Commission, Gartner, IBs, Information, Internet, It, Their, They, US
related to Further reading· 5
Data broker → Beckett, Everything, June, Lois, ProPublica
is a· 1
Data broker → individual or company that specializes in collecting personal data
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.
Data broker 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 129 structured relationships around Data broker. Examples in this analysis include Data broker → is a → individual or company that specializes in collecting personal data and the development of the Internet → instance of → technological developments. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Data broker
is a
individual or company that specializes in collecting personal data
0.90
text
the development of the Internet
instance of
technological developments
0.80
text
increasing computer processing power
instance of
technological developments
0.80
text
and declining costs of data storage made it much easier for companies to collect
instance of
technological developments
0.80
text
analyze
instance of
technological developments
0.80
text
store
instance of
technological developments
0.80
text
transfer large amounts of data about individuals
instance of
technological developments
0.80
text
product registrations
instance of
ranging from the daily communications of an individual to more specialized data
0.80
text
patents
instance of
ranging from the daily communications of an individual to more specialized data
0.80
text
copyright data
instance of
ranging from the daily communications of an individual to more specialized data
0.80
text
mostly from publicly available sources
instance of
ranging from the daily communications of an individual to more specialized data
0.80
text
usually obtained from online databases
instance of
ranging from the daily communications of an individual to more specialized data
0.80
text
No triples extracted yet.
Related concept clusters Concept neighborhoods
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 Data broker bring nearby vocabulary together. In this analysis, examples include Brokers, Information and Data. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Data broker
Brokers
Information
Data
States
Business
United
Consumer
Privacy
People
Also
Federal
Us
data broker
Brokers
Information
Data
Consumer
States
Business
United
Company
Privacy
Us
People
Also
personal data
Brokers
Information
Records
Variety
States
Federal
United
Consumer
Companies
Advertising
Political
Sometimes
geolocation data
Brokers
Information
States
United
Consumer
Also
Federal
Us
Companies
Consumers
May
Acxiom
information specialists
Brokers
May
Companies
Also
Business
Privacy
States
Variety
Often
Us
Consumer
United
data storage
Brokers
Information
States
United
Consumer
Also
Federal
Us
Companies
Consumers
May
Acxiom
aggregate that data
Brokers
Information
States
United
Consumer
Also
Federal
Us
Companies
Consumers
May
Acxiom
scientific data
Brokers
Information
States
United
Consumer
Also
Federal
Us
Companies
Consumers
May
Acxiom
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 Data broker, one of the stronger structural bridges in this analysis connects Data broker 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.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Data broker
Nodes135
Edges134
Triples129
Avg. degree1.99
Density0.014815
Components1
Source & methodology
TTTA analyzes the structure around Data broker to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Companies & Art, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
