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Smile: Culture & Cultures
A smile is a facial expression formed primarily by flexing the muscles at the sides of the mouth. Some smiles include a contraction of the muscles at the corner of the eyes, an action known as a Duchenne smile. Among humans, a smile expresses delight, sociability, happiness, joy, or amusement. It is distinct from a similar but usually involuntary…
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Smile topic overview
The analysis highlights Culture and Cultures as prominent areas in the source structure around Smile.
Related topics
53
Source areas
7
Connected nodes
60
Extracted relationships
76
Concept neighborhoods
25
Bridge connections
60
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.
Cultural differences · 21 topics
Overview · 10 topics
Other animals · 6 topics
Social effects · 6 topics
Dimples · 4 topics
Duchenne smile · 4 topics
Non-Duchenne smile · 2 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 Smile 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 Smile shows recurring relationship patterns in the source. For example, Smile → An, Belmont, California, Cambridge University Press, Cited, Conniff, Davidson, Emotional, Facial Expression, Fernandez-Dols, Friesen, II, ISBN, James Albert Russell, José Miguel Fernández-Dols, Journal, Ottenheimer, Paul, Personality, PMID Another extracted example is Smile → Asia, China, For, France, ID, In, It, Japan, Many, Researchers, Some, Soviet Union, This, Too, While. Use these groups to spot repeated connection types before inspecting the individual relationships.
Smile
Top relations
related to Further reading· 29
Smile → An, Belmont, California, Cambridge University Press, Cited, Conniff, Davidson, Emotional, Facial Expression, Fernandez-Dols, Friesen, II, ISBN, James Albert Russell, José Miguel Fernández-Dols, Journal, Ottenheimer, Paul, Personality, PMID
related to Cultural differences· 15
Smile → Asia, China, For, France, ID, In, It, Japan, Many, Researchers, Some, Soviet Union, This, Too, While
related to Non-Duchenne smile· 10
Smile → According, Botox, Chronic, Duchenne, It, Messenger, More, Pan Am, Research, The
related to Duchenne smile· 7
Smile → Duchenne, Dynasmile, French, Guillaume Duchenne, Recent, The Duchenne, While
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 76 structured relationships around Smile. Examples in this analysis include Smile → is a → facial expression formed primarily by flexing the muscles at the sides of the mouth and Smile → related to background → Primatologist Signe Preuschoft. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Smile
is a
facial expression formed primarily by flexing the muscles at the sides of the mouth
0.90
text
Smile
related to background
Primatologist Signe Preuschoft
0.60
section
Smile
related to background
The
0.60
section
Smile
related to Cultural differences
Researchers
0.60
section
Smile
related to Cultural differences
For
0.60
section
Smile
related to Cultural differences
France
0.60
section
Smile
related to Cultural differences
China
0.60
section
Smile
related to Cultural differences
Japan
0.60
section
Smile
related to Cultural differences
This
0.60
section
Smile
related to Cultural differences
ID
0.60
section
Smile
related to Cultural differences
It
0.60
section
Smile
related to Cultural differences
While
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 Smile bring nearby vocabulary together. In this analysis, examples include May, Major and Muscle. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Smile
May
Major
Muscle
Zygomatic
Humans
Botox
Example
Among
Also
Cheeks
People
Smiling
smile
May
Major
Muscle
Zygomatic
Humans
Botox
Example
Among
Also
Cheeks
People
Smiling
duchenne smile
Eyes
Smile
Botox
Muscles
Also
Cheeks
Known
Major
Muscle
Smiles
Zygomatic
May
non-duchenne smile
May
Major
Muscle
Zygomatic
Humans
Botox
Example
Among
Also
Cheeks
People
Smiling
guillaume duchenne
Eyes
Smile
Botox
Muscles
Also
Cheeks
Known
Major
Muscle
Smiles
Zygomatic
Animals
the expression of the emotions in man and animals
Used
Teeth
Facial
Cultural
Differences
Social
Also
Known
Photograph
Sign
Animals
Expression
smiling girl, a courtesan, holding an obscene image
Found
Many
Positive
United
Common
Social
Major
People
Photograph
Sign
Zygomatic
Botox
cultural differences
Cultural
Differences
Social
Also
Cultures
May
Animals
United
Used
Teeth
People
Smiling
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 Smile, one of the stronger structural bridges in this analysis connects Smile with Cultural differences. 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.
Smile
Nodes61
Edges60
Triples76
Avg. degree1.97
Density0.032787
Components1
Source & methodology
TTTA analyzes the structure around Smile to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Culture & Cultures, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Smile · EN edition · Analysis: TopicsToTalkAbout
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