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Data journalism or data-driven journalism (DDJ) is journalism based on the filtering and analysis of large data sets for the purpose of creating or elevating a news story.
The analysis highlights Emergence as a concept, Overview and Examples as prominent areas in the source structure around Data journalism.
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.
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.
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The extracted context around Data journalism shows recurring relationship patterns in the source. For example, Data journalism → Analysis, Data-based, Deep, Dissect, Explore, Highlight, Local, Many, Martha Kang, Megan Knight, Narrate, Profile, Simon Rogers, Specifically, Start Another extracted example is Data journalism → Afghan War Diary, Afghanistan, Data, Der Spiegel, England, Google Fusion Tables, Guardian, IED, Iraq War, The Guardian, The Guardian's, The New York Times, Three, WikiLeaks. Use these groups to spot repeated connection types before inspecting the individual relationships.
Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.
data journalism data-driven stories used new based information process reporting open public story analysis tools visualizations visualization many one use
TTTA extracted 69 structured relationships around Data journalism. Examples in this analysis include Data journalism → is a → research of large amounts of textual or financial data and data visualization → instance of → It involves a blending of journalism with other fields. The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Data journalism | is a | research of large amounts of textual or financial data | 0.90 | text |
| data visualization | instance of | It involves a blending of journalism with other fields | 0.80 | text |
| computer science | instance of | It involves a blending of journalism with other fields | 0.80 | text |
| and statistics | instance of | It involves a blending of journalism with other fields | 0.80 | text |
| open source software | instance of | Some see these as levels or stages leading from the simpler to the more complex uses of new technologies in the journalistic process.Many data-driven stories begin with newly av… | 0.80 | text |
| open access publishing | instance of | Some see these as levels or stages leading from the simpler to the more complex uses of new technologies in the journalistic process.Many data-driven stories begin with newly av… | 0.80 | text |
| open data | instance of | Some see these as levels or stages leading from the simpler to the more complex uses of new technologies in the journalistic process.Many data-driven stories begin with newly av… | 0.80 | text |
| while others are products of public records requests or leaked materials | instance of | Some see these as levels or stages leading from the simpler to the more complex uses of new technologies in the journalistic process.Many data-driven stories begin with newly av… | 0.80 | text |
| tables | instance of | One trend in the digital era of journalism has been to disseminate information to the public via interactive online content through data visualization tools | 0.80 | text |
| graphs | instance of | One trend in the digital era of journalism has been to disseminate information to the public via interactive online content through data visualization tools | 0.80 | text |
| maps | instance of | One trend in the digital era of journalism has been to disseminate information to the public via interactive online content through data visualization tools | 0.80 | text |
| infographics | instance of | One trend in the digital era of journalism has been to disseminate information to the public via interactive online content through data visualization tools | 0.80 | text |
The concept neighborhoods around Data journalism bring nearby vocabulary together. In this analysis, examples include Journalism, Stories and Data-driven. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Data journalism, one of the stronger structural bridges in this analysis connects Data journalism with Overview. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
TTTA analyzes the structure around Data journalism to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Emergence as a concept, Overview & Examples, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Data journalism · EN edition · Analysis: TopicsToTalkAbout
