Science communication encompasses a wide range of activities that connect science and society. Common goals of science communication include informing non-experts about scientific findings, raising the public awareness of and interest in science, influencing people's attitudes and behaviors, informing public policy, and engaging with diverse communities…
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Science communication topic overview
The analysis highlights Culture, Science, Technology and Measurement as prominent areas in the source structure around Science communication.
Related topics
163
Source areas
5
Connected nodes
169
Extracted relationships
175
Concept neighborhoods
58
Bridge connections
169
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.
Science in popular culture and the media · 44 topics
Overview · 42 topics
Methods · 33 topics
Motivations · 23 topics
The public understanding of science movement · 21 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 Science communication 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 Science communication shows recurring relationship patterns in the source. For example, Science communication → ABC-CLIO, Baker, Bauer, Bristol, Bucchi, Cartwright, Cham, Chemistry, Communicating Science Effectively, Communication, Complete Science Communication, Connecting, Credibility, Culture, DC, Drake, Earth-Science Outreach, Engagement, Engineering, Fortenberry Another extracted example is Science communication → Age, Another, Because, Carl Sagan, Don't, Don't Be Such, He, However, In, Marine, Neil, Olson, Randy Olson, Science, Scientist, Style, Such, Talking Substance, The New York Times, This. Use these groups to spot repeated connection types before inspecting the individual relationships.
Science communication → Age, Another, Because, Carl Sagan, Don't, Don't Be Such, He, However, In, Marine, Neil, Olson, Randy Olson, Science, Scientist, Style, Such, Talking Substance, The New York Times, This
related to Motivations· 18
Science communication → Brian Wynne, By, Carina Cortassa's, Geoffery Thomas, Governments, Hilgartner, In, John Durant, Living, Massimiano Bucchi, More, Moreover, Public Understanding, Science, Steven Hilgartner, The, Understood, Writing
related to Imagining science's publics· 11
Science communication → Approaches, As, At, First, In, Many, Public Understanding, Richard Dawkins, Science, The Selfish Gene, Three
related to Evidence based practices· 9
Science communication → Alexander Gerber, Closer, Eric Jensen, Gerber, In, Ironically, Jensen, Similar, The
related to Inclusive communication and cultural differences· 9
Science communication → European, Inclusive, Indigenous, It, Linda Tuhiwai Smith, Māori, Science, The, Western
related to Science communication in contemporary media· 4
Science communication → According, Karen Bultitude, Science, University College London
related to Frame analysis· 2
Science communication → Science, Some
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.
Science communication relationships Subject–Predicate–Object triples
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 175 structured relationships around Science communication. Examples in this analysis include misinformation → instance of → and metaphors to connect with their audience's values and interests.Science communication also exists as an interdisciplinary field of social science research on topics and Turkish creationist Adnan Oktar → instance of → Journalist Robert Krulwich likewise argued in 2008 that the stories scientists tell compete with the efforts of people. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
misinformation
instance of
and metaphors to connect with their audience's values and interests.Science communication also exists as an interdisciplinary field of social science research on topics
0.80
text
public opinion of emerging technologies
instance of
and metaphors to connect with their audience's values and interests.Science communication also exists as an interdisciplinary field of social science research on topics
0.80
text
and the politicization
instance of
and metaphors to connect with their audience's values and interests.Science communication also exists as an interdisciplinary field of social science research on topics
0.80
text
polarization of science
instance of
and metaphors to connect with their audience's values and interests.Science communication also exists as an interdisciplinary field of social science research on topics
0.80
text
Turkish creationist Adnan Oktar
instance of
Journalist Robert Krulwich likewise argued in 2008 that the stories scientists tell compete with the efforts of people
0.80
text
Carl Sagan
instance of
MethodsScience popularization figures
0.80
text
Neil deGrasse Tyson are partly responsible for the view of science or a specific science discipline within the general public
instance of
MethodsScience popularization figures
0.80
text
the gender of those ticking
instance of
considering issues
0.80
text
Nature or National Geographic possessed a large readership
instance of
scientific journals
0.80
text
received substantial funding by the end of the nineteenth century as the popularization of science continued.Science communication in contemporary mediaScience can be communicated to the public in many different ways
instance of
scientific journals
0.80
text
Facebook
instance of
director of Scientific Career Development at Fred Hutchinson Cancer Research Center stressed the importance for scientists of using social networks
0.80
text
Twitter to establish an online presence.Kimberly Collins et al.
instance of
director of Scientific Career Development at Fred Hutchinson Cancer Research Center stressed the importance for scientists of using social networks
0.80
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 Science communication bring nearby vocabulary together. In this analysis, examples include Science, Public and Understanding. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
Science communication
Science
Public
Understanding
Research
Scientists
Scientific
Social
Also
Technology
Media
Society
Online
science communication
Science
Public
Research
Online
Understanding
Scientists
Scientific
Social
Also
Technology
Media
Communities
science
Public
Understanding
Research
Scientists
Scientific
Social
Also
Technology
Media
Society
Online
Work
public awareness of and interest in science
Public
Science
Understanding
Scientific
Scientists
General
Research
Social
Also
Technology
Media
Engagement
public policy
Science
Understanding
Scientific
Scientists
General
Research
Technology
Communities
Social
Media
Also
Engagement
public engagement with science
Public
Science
Understanding
Scientific
Scientists
Technology
General
Research
Using
Social
Also
Media
science journalism
Traditional
Public
Understanding
Research
Scientists
Scientific
Also
Online
Social
Technology
Media
Policy
health communication
Science
Research
Public
Online
Scientific
Scientists
Social
Communities
Also
New
Society
Outreach
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 Science communication, one of the stronger structural bridges in this analysis connects Science communication with Science in popular culture and the media. 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
Science communication — Science in popular culture and the media· splits 125 ⟂ 45Science communication — Overview· splits 127 ⟂ 43Science communication — Methods· splits 136 ⟂ 34Science communication — Motivations· splits 145 ⟂ 25Science communication — The public understanding of science movement· splits 148 ⟂ 22
Map overview Semantic statistics
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Science communication
Nodes170
Edges169
Triples175
Avg. degree1.99
Density0.011765
Components1
Source & methodology
TTTA analyzes the structure around Science communication to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Culture, Science, Technology & Measurement, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
