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StopBadware: Art, Supporters & People
StopBadware was an anti-malware nonprofit organization focused on making the Web safer through the prevention, mitigation, and remediation of badware websites. It is the successor to StopBadware.org, a project started in 2006 at the Berkman Center for Internet and Society at Harvard University. It spun off to become a standalone organization, and dropped…
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StopBadware topic overview
The analysis highlights Art, Supporters and People as prominent areas in the source structure around StopBadware.
Related topics
32
Source areas
6
Connected nodes
38
Extracted relationships
80
Concept neighborhoods
14
Bridge connections
38
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.
Supporters · 14 topics
People · 8 topics
Activities · 4 topics
Overview · 4 topics
Defining "badware" · 1 topics
Google and StopBadware · 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.
Founded
2006
Location
Cambridge, Massachusetts, USA
Dissolved
2020
Founder
John Palfrey, Jonathan Zittrain
Key people
Vint Cerf, Esther Dyson
Type
501(c)(3)
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 StopBadware 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 StopBadware shows recurring relationship patterns in the source. For example, StopBadware → Alex Eckelberry, Ari Schwartz, Berkman Center, Board, Both, Brett McDowell, Chair, Eric Davis, Esther Dyson, Executive Director, Harvard University, John Morris, John Palfrey, Jonathan Zittrain, Law, Maxim Weinstein, Michael Barrett, Mike Shaver, Oxford Internet Institute, Paul Mockapetris Another extracted example is StopBadware → AOL, Badware Website Clearinghouse, Berkman Center, Consumer Reports WebWatch, Consumers Union, GFI Software, Google, Lenovo, Mozilla, MySpace, NSFocus, PayPal, Previous, Qualys, Some, Sun Microsystems, Trend Micro, Verisign, Verizon, Yandex. Use these groups to spot repeated connection types before inspecting the individual relationships.
StopBadware
Top relations
related to People· 25
StopBadware → Alex Eckelberry, Ari Schwartz, Berkman Center, Board, Both, Brett McDowell, Chair, Eric Davis, Esther Dyson, Executive Director, Harvard University, John Morris, John Palfrey, Jonathan Zittrain, Law, Maxim Weinstein, Michael Barrett, Mike Shaver, Oxford Internet Institute, Paul Mockapetris
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 80 structured relationships around StopBadware. Examples in this analysis include StopBadware → Dissolved → 2020 and StopBadware → Founded → 2006. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
StopBadware
Dissolved
2020
1.00
infobox
StopBadware
Founded
2006
1.00
infobox
StopBadware
Founder
John Palfrey, Jonathan Zittrain
1.00
infobox
StopBadware
Key people
Vint Cerf, Esther Dyson
1.00
infobox
StopBadware
Location
Cambridge, Massachusetts, USA
1.00
infobox
StopBadware
Type
501(c)(3)
1.00
infobox
StopBadware
Website
stopbadware.org at the Wayback Machine (archived 2021-11-02)
1.00
infobox
StopBadware
related to Activities
StopBadware's
0.60
section
StopBadware
related to Activities
Web
0.60
section
StopBadware
related to Activities
In
0.60
section
StopBadware
related to Activities
We Stop Badware
0.60
section
StopBadware
related to Activities
In June
0.60
section
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 StopBadware bring nearby vocabulary together. In this analysis, examples include Org, Badware and Google. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
StopBadware
Org
Badware
Google
Berkman
Center
Internet
Originally
Project
Also
Protect
Software
Web
stopbadware
Org
Badware
Google
Berkman
Center
Internet
Originally
Project
Also
Protect
Software
Web
badware
Website
Stopbadware
Also
Clearinghouse
Organization's
Providers
Software
Web
Org
Activities
Focused
Originally
defining "badware"
Website
Stopbadware
Also
Clearinghouse
Organization's
Providers
Software
Web
Org
Activities
Focused
Originally
google and stopbadware
Org
Badware
Google
Stopbadware
Berkman
Center
Website
Uses
Websites
Internet
Originally
Project
google
Stopbadware
Website
Uses
Websites
People
Internet
John
Originally
Palfrey
Supporters
Also
Blacklist
activities
People
Internet
John
Originally
Palfrey
Supporters
Also
Clearinghouse
Independent
Organization's
Web
Website
berkman center for internet and society
Center
Harvard
Internet
People
Project
University
Org
Activities
John
Originally
Palfrey
Supporters
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 StopBadware, one of the stronger structural bridges in this analysis connects StopBadware with Supporters. 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.
StopBadware
Nodes39
Edges38
Triples80
Avg. degree1.95
Density0.051282
Components1
Source & methodology
TTTA analyzes the structure around StopBadware to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Supporters & People, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
