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Mayday PAC: Art, Targeted races in 2014 & Background
Mayday PAC is an American crowd-funded non-partisan Super PAC created by Harvard Law School professor and activist Lawrence Lessig. Its purpose is to help elect candidates to the Congress to pass campaign finance reform. It is notable for raising large sums from numerous contributors in a short span of time – nearly $11 million in 2014 – and was…
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Mayday PAC topic overview
The analysis highlights Art, Targeted races in 2014 and Background as prominent areas in the source structure around Mayday PAC.
Related topics
34
Source areas
4
Connected nodes
38
Extracted relationships
77
Concept neighborhoods
11
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.
Targeted races in 2014 · 14 topics
Overview · 9 topics
Background · 7 topics
Fundraising information · 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 Mayday PAC 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 Mayday PAC shows recurring relationship patterns in the source. For example, Mayday PAC → Act, Appel, Arizona House, As, August, AZ, Brown, CARD Act, Carol Shea-Porter, Citizens United Supreme Court, Congress, Consumer Protection Act, David Young, DISCLOSE Act, Each, FEMA, Formerly, Fred Upton, Government, Government By The People Another extracted example is Mayday PAC → Based, But, Congress, Dixville Notch, He, If, Ironic, Lawrence Lessig, Lessig, May, Nashua, New Hampshire, Super PAC, The, Then, We've, Yes. Use these groups to spot repeated connection types before inspecting the individual relationships.
Mayday PAC
Top relations
related to Targeted races in 2014· 56
Mayday PAC → Act, Appel, Arizona House, As, August, AZ, Brown, CARD Act, Carol Shea-Porter, Citizens United Supreme Court, Congress, Consumer Protection Act, David Young, DISCLOSE Act, Each, FEMA, Formerly, Fred Upton, Government, Government By The People
related to background· 17
Mayday PAC → Based, But, Congress, Dixville Notch, He, If, Ironic, Lawrence Lessig, Lessig, May, Nashua, New Hampshire, Super PAC, The, Then, We've, Yes
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 77 structured relationships around Mayday PAC. Examples in this analysis include Mayday PAC → is a → American crowd-funded non-partisan Super PAC created by Harvard Law School professor and activist Lawrence Lessig and Mayday PAC → related to background → Lawrence Lessig. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Mayday PAC
is a
American crowd-funded non-partisan Super PAC created by Harvard Law School professor and activist Lawrence Lessig
0.90
text
Mayday PAC
related to background
Lawrence Lessig
0.60
section
Mayday PAC
related to background
Super PAC
0.60
section
Mayday PAC
related to background
May
0.60
section
Mayday PAC
related to background
Lessig
0.60
section
Mayday PAC
related to background
Dixville Notch
0.60
section
Mayday PAC
related to background
Nashua
0.60
section
Mayday PAC
related to background
New Hampshire
0.60
section
Mayday PAC
related to background
He
0.60
section
Mayday PAC
related to background
Yes
0.60
section
Mayday PAC
related to background
Ironic
0.60
section
Mayday PAC
related to background
But
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 Mayday PAC bring nearby vocabulary together. In this analysis, examples include Election, Spent and Despite. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Mayday PAC
Election
Spent
Despite
Incumbent
Lost
Pac
Opponent
Campaign
Elections
United
Support
Finance
mayday pac
Election
Spent
Campaign
Despite
Incumbent
Lost
Pac
Finance
Reform
Super
Opponent
Politics
super pac
Campaign
Finance
Lessig
Reform
Pac
Super
Electing
Plan
Candidates
Politics
Spent
Elections
congress
Reform
Electing
Legislation
Races
Funds
Finance
Money
New
Announced
Replaced
Teachout
Plan
campaign finance reform
Finance
Reform
Pac
Candidates
Legislation
Super
Elections
Congress
Mayday
Announced
Electing
Plan
new hampshire
Hampshire
New
Politics
Money
Plan
Races
Funds
People
Replaced
Small
Teachout
Pac
lawrence lessig
Pac
Politics
Super
United
Money
Reform
Replaced
Teachout
Raise
Hampshire
Mayday
People
government by the people act
Small
Funds
Act
People
Support
Citizens
United
Politics
State
Legislation
Candidates
Opponent
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 Mayday PAC, one of the stronger structural bridges in this analysis connects Mayday PAC with Targeted races in 2014. 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.
Mayday PAC
Nodes39
Edges38
Triples77
Avg. degree1.95
Density0.051282
Components1
Source & methodology
TTTA analyzes the structure around Mayday PAC to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Art, Targeted races in 2014 & Background, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
