Macerich

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Macerich topic overview

The analysis highlights History, Measurement and Companies as prominent areas in the source structure around Macerich.

Related topics: 13
Source areas: 2
Connected nodes: 15
Extracted relationships: 22
Concept neighborhoods: 12
Bridge connections: 15

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 · 10 topics

Overview · 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.

Key facts & relationships

High-confidence facts extracted from structured source data. Use them as anchors for further research.

Founded: 1964; 62 years ago (1964)
Industry: Real estate investment trust
Headquarters: Santa Monica, California, U.S.
Founder: Mace Siegel Richard Cohen
Key people: Steven Hash (chairman of the Board) Jackson Hsieh (CEO) Scott Kingsmore (CFO) Ann C. Menard (CLO)
Net income: -$194 million (2024)

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

History

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 Macerich connects Entity context

The extracted context around Macerich shows recurring relationship patterns in the source. For example, Macerich → In, Mace Siegel, MaceRich Real Estate Company, New York, Richard Cohen, The Another extracted example is Macerich → NYSE: MAC, S&P 600 component. Use these groups to spot repeated connection types before inspecting the individual relationships.

Top relations

related to history · 6

Macerich → In, Mace Siegel, MaceRich Real Estate Company, New York, Richard Cohen, The

Traded as · 2

Macerich → NYSE: MAC, S&P 600 component

related to External links · 2

Macerich → GoogleReutersSEC, Official

Founded · 1

Macerich → 1964; 62 years ago (1964)

Founder · 1

Macerich → Mace Siegel Richard Cohen

Headquarters · 1

Macerich → Santa Monica, California, U.S.

Industry · 1

Macerich → Real estate investment trust

Key people · 1

Macerich → Steven Hash (chairman of the Board) Jackson Hsieh (CEO) Scott Kingsmore (CFO) Ann C. Menard (CLO)

Net income · 1

Macerich → -$194 million (2024)

Number of employees · 1

Macerich → 616 (2024)

Important terminology

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

Important terminology

company shopping centers billion real estate mace siegel richard cohen name ceo cfo investment trust 2024 million owner properties area

Macerich relationships Subject–Predicate–Object triples

TTTA extracted 22 structured relationships around Macerich. Examples in this analysis include Macerich → Founded → 1964; 62 years ago (1964) and Macerich → Founder → Mace Siegel Richard Cohen. The table shows each extracted connection, where it came from and its confidence.

Subject	Predicate	Object	Confidence	Src
Macerich	Founded	1964; 62 years ago (1964)	1.00	infobox
Macerich	Founder	Mace Siegel Richard Cohen	1.00	infobox
Macerich	Headquarters	Santa Monica, California, U.S.	1.00	infobox
Macerich	Industry	Real estate investment trust	1.00	infobox
Macerich	Key people	Steven Hash (chairman of the Board) Jackson Hsieh (CEO) Scott Kingsmore (CFO) Ann C. Menard (CLO)	1.00	infobox
Macerich	Net income	-$194 million (2024)	1.00	infobox
Macerich	Number of employees	616 (2024)	1.00	infobox
Macerich	Revenue	$918 million (2024)	1.00	infobox
Macerich	Total assets	$8.567 billion (2024)	1.00	infobox
Macerich	Total equity	$2.756 billion (2024)	1.00	infobox
Macerich	Traded as	NYSE: MAC	1.00	infobox
Macerich	Traded as	S&P 600 component	1.00	infobox
Macerich	Type	Public	1.00	infobox
Macerich	Website	www.macerich.com	1.00	infobox

Related concept clusters Concept neighborhoods

The concept neighborhoods around Macerich bring nearby vocabulary together. In this analysis, examples include Estate, Real and Billion. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

Macerich
- Estate
- Real
- Billion
- Founded
- Investment
- Property
- Trust
- Website
- Cohen
- Mace
- Name
- Richard
macerich
- Estate
- Real
- Billion
- Founded
- Investment
- Property
- Trust
- Website
- Cohen
- Mace
- Name
- Richard
real estate investment trust
- Real
- Trust
- Founded
- Investment
- Cohen
- Invests
- Mace
- Macerich
- Mayss-ritch
- Richard
- Siegel
- ˈmeɪsrɪtʃ
public company
- Macerich
- Cohen
- Estate
- Mace
- Name
- Real
- Richard
- Siegel
- Billion
- Monica
- Santa
- Trust
shopping centers
- Shopping
- Invests
- Mayss-ritch
- ˈmeɪsrɪtʃ
- Acquired
- Investment
- Macerich's
- New
- Owner
- Portfolio
- Trust
- Company
rochester, new york
- Acquired
- Macerich's
- Portfolio
- Website
- Real
- Richard
- Siegel
- Shopping
phoenix metropolitan area
- Properties
- Macerich's
- Million
- Owner
- Phoenix
- Portfolio
- Company
wilmorite properties
- Area
- Macerich's
- Million
- Owner
- Phoenix
- Portfolio
- Company

Connections between topic areas Semantic bridges

For Macerich, one of the stronger structural bridges in this analysis connects Macerich 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.

Min side: 3

Macerich — History · splits 5 ⟂ 11

Macerich — Overview · splits 12 ⟂ 4

Map overview Semantic statistics

Macerich

Nodes16

Edges15

Triples22

Avg. degree1.88

Density0.125

Components1

Source & methodology

TTTA analyzes the structure around Macerich 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 — Macerich · EN edition · Analysis: TopicsToTalkAbout