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KIMT: History, Measurement & Companies
KIMT (channel 3) is a television station licensed to Mason City, Iowa, United States, serving North Central Iowa and Southeast Minnesota as an affiliate of CBS and MyNetworkTV. Owned by Allen Media Group, the station maintains studios on North Pennsylvania Avenue in downtown Mason City, with a news bureau on Highway 52 North in Rochester, Minnesota, and…
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KIMT topic overview
The analysis highlights History, Measurement and Companies as prominent areas in the source structure around KIMT.
Related topics
66
Source areas
4
Connected nodes
70
Extracted relationships
94
Concept neighborhoods
25
Bridge connections
70
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.
History · 48 topics
Overview · 12 topics
News operation · 5 topics
Subchannels · 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.
Owner
Allen Media Group · (Rochester TV License Company, LLC)
Affiliations
3.1: CBS · 3.2: Independent with MyNetworkTV · for others, see § Subchannels
Branding
KIMT 3; KIMT News 3 · my3.2 (3.2)
Call sign meaning
"Iowa Minnesota Television"
Channels
Digital: 24 (UHF) · Virtual: 3
City
Mason City, Iowa
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 KIMT 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 KIMT shows recurring relationship patterns in the source. For example, KIMT → AM, As, August, Bluefield, BY Communications, CBS, CBS Radio, Daily Telegraph Printing Company, DuMont, FCC, Federal Communications Commission, Florence, FM, Gary, Globe Gazette, However, In, In August, Indiana, Iowa Minnesota Television Another extracted example is KIMT → Fox, Game, Hampton Roads, Indiana, Kansas, Major League Baseball All-Star, Media General, Mediacom, North Iowa, On July, Terre Haute, This, Topeka, United States, Virginia. Use these groups to spot repeated connection types before inspecting the individual relationships.
KIMT
Top relations
related to history· 35
KIMT → AM, As, August, Bluefield, BY Communications, CBS, CBS Radio, Daily Telegraph Printing Company, DuMont, FCC, Federal Communications Commission, Florence, FM, Gary, Globe Gazette, However, In, In August, Indiana, Iowa Minnesota Television
related to July 2015 carriage dispute with Mediacom· 15
KIMT → Fox, Game, Hampton Roads, Indiana, Kansas, Major League Baseball All-Star, Media General, Mediacom, North Iowa, On July, Terre Haute, This, Topeka, United States, Virginia
related to News operation· 14
KIMT → Also, Although, Eventually, HD, Iowa, KIMT News, Midday, My, My Morning News, My Primetime News, MyNetworkTV-affiliated, On June, Since KIMT, This
Affiliations· 3
KIMT → 3.1: CBS, 3.2: Independent with MyNetworkTV, for others, see § Subchannels
Former affiliations· 3
KIMT → Both secondary:, DuMont (1954–1956), UPN (1995−2006)
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 94 structured relationships around KIMT. Examples in this analysis include KIMT → Affiliations → 3.1: CBS and KIMT → Affiliations → 3.2: Independent with MyNetworkTV. The table shows each extracted connection, where it came from and its confidence.
only major station licensed to the Iowa side of the market
0.90
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 KIMT bring nearby vocabulary together. In this analysis, examples include Iowa, Media and Station. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
KIMT
Iowa
Media
Station
Television
Would
Stations
Announced
Group
News
Million
Allen
June
kimt
Iowa
Media
Station
Television
Would
Stations
Announced
Group
News
Million
Allen
June
television station
Television
Minnesota
States
United
Stations
Mason
Million
First
Would
Group
Mynetworktv
Announced
mason city, iowa
Mason
Cbs
Minnesota
Mynetworktv
Rochester
States
United
Station
Group
North
Subchannels
Kimt
cbs
City
Mynetworktv
States
United
Mason
Iowa
Minnesota
Group
Channel
Rochester
Station
Subchannels
allen media group
General
Group
Announced
Stations
Rochester
Would
Media
Mason
City
Company
Minnesota
May
meyer, iowa
Minnesota
Station
Subchannels
Kimt
Affiliate
Cbs
Mediacom
North
First
Television
Digital
Mynetworktv
media general
General
Media
Announced
Stations
Would
Mediacom
Subchannels
North
Television
Part
Company
Digital
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 KIMT, one of the stronger structural bridges in this analysis connects KIMT with History. 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.
KIMT
Nodes71
Edges70
Triples94
Avg. degree1.97
Density0.028169
Components1
Source & methodology
TTTA analyzes the structure around KIMT to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as History, Measurement & Companies, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — KIMT · EN edition · Analysis: TopicsToTalkAbout
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