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LOL: Themes & History
LOL, or lol, is an acronym for "laughing out loud", and a popular element of Internet slang, which can be used to indicate amusement. It was first used almost exclusively on Usenet, but has since become widespread in other forms of computer-mediated communication and even face-to-face communication. It is one of many acronyms for expressing bodily…
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LOL topic overview
The analysis highlights Themes and History as prominent areas in the source structure around LOL.
Related topics
76
Source areas
4
Connected nodes
80
Extracted relationships
62
Concept neighborhoods
14
Bridge connections
80
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.
Variations on the theme · 48 topics
Overview · 11 topics
History · 10 topics
Analysis · 7 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 LOL 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 LOL shows recurring relationship patterns in the source. For example, LOL → Agricultural, August, Authority, Brian, Claim, Connery, Credibility, February, IMHO, In Porter, Internet Culture, Internet Message Boards, ISBN, January, Louisiana State University, Mechanical College, New York, Newsgroup, Retrieved December, ROTFLRyan Goudelocke Another extracted example is LOL → Although, Ben Zimmer, CMC, FidoNews, In, Instead, Laughing Out Loud, May, Naomi Baron, Out, Oxford English Dictionary, Pearson, The, Viewline, Wayne Pearson, World Wide Web. Use these groups to spot repeated connection types before inspecting the individual relationships.
LOL
Top relations
related to Further reading· 23
LOL → Agricultural, August, Authority, Brian, Claim, Connery, Credibility, February, IMHO, In Porter, Internet Culture, Internet Message Boards, ISBN, January, Louisiana State University, Mechanical College, New York, Newsgroup, Retrieved December, ROTFLRyan Goudelocke
related to history· 16
LOL → Although, Ben Zimmer, CMC, FidoNews, In, Instead, Laughing Out Loud, May, Naomi Baron, Out, Oxford English Dictionary, Pearson, The, Viewline, Wayne Pearson, World Wide Web
related to Analysis· 15
LOL → Fondiller, It's, Linguist John McWhorter, McWhorter, Nerone, Oh, Pragmatic, Scott Molski, Silvio Laccetti, Stevens Institute, Technology, The Lost Art, Unfortunately, We, Writing
instance of· 1
LOL → Pullum argues that even if interjections
Important terminology
Frequent words and multi-word phrases across the lead, headings, infobox and body. Useful for terminology coverage.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
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 62 structured relationships around LOL. Examples in this analysis include LMAO → instance of → including acronyms for more emphatic expressions of laughter and business communications → instance of → either in general or in specific contexts. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
LMAO
instance of
including acronyms for more emphatic expressions of laughter
0.80
text
business communications
instance of
either in general or in specific contexts
0.80
text
LOL
instance of
Pullum argues that even if interjections
0.80
text
ROFL were to become very common in spoken English
instance of
Pullum argues that even if interjections
0.80
text
their
instance of
Pullum argues that even if interjections
0.80
text
these
instance of
In cases
0.80
text
the abbreviation is not to be read literally
instance of
In cases
0.80
text
Kekistan
instance of
as well as memes
0.80
text
LOL
related to Analysis
Silvio Laccetti
0.60
section
LOL
related to Analysis
Stevens Institute
0.60
section
LOL
related to Analysis
Technology
0.60
section
LOL
related to Analysis
Scott Molski
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 LOL bring nearby vocabulary together. In this analysis, examples include Loud, Dictionary and English. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
LOL
Loud
Dictionary
English
People
Rofl
Used
Oxford
Stated
Way
May
Initialisms
Commonly
lol
Loud
Dictionary
English
People
Rofl
Used
Oxford
Stated
Way
May
Initialisms
Commonly
acronyms
Smileys
Abbreviations
Oxford
Business
Dictionary
English
Slang
Students
Communication
Emoticons
Use
Laughing
computer-mediated communication
Communication
Computer-mediated
Face-to-face
Forms
Smileys
Usenet
Students
Initialisms
Folk
Use
Acronyms
Abbreviations
internet slang
Terms
Students
Slang
Acronyms
Smileys
Abbreviations
Also
Meanings
Business
Found
Communication
Emoticons
emoticons
Folk
Abbreviations
Meanings
Usenet
Students
Forms
Smileys
Terms
Business
Dictionary
Found
Slang
usenet
Folk
Forms
Computer-mediated
Communication
Emoticons
Become
Face-to-face
Smileys
Abbreviations
Dictionary
First
Used
oxford english dictionary
Dictionary
English
Oxford
Acronyms
Folk
Lol
Abbreviations
First
Usenet
May
Emoticons
Loud
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 LOL, one of the stronger structural bridges in this analysis connects LOL with Variations on the theme. 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.
LOL
Nodes81
Edges80
Triples62
Avg. degree1.98
Density0.024691
Components1
Source & methodology
TTTA analyzes the structure around LOL to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Themes & History, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — LOL · EN edition · Analysis: TopicsToTalkAbout
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