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Microsoft Academic was a free internet-based academic search engine for academic publications and literature, developed by Microsoft Research in 2016 as a successor of Microsoft Academic Search. Microsoft Academic was shut down at the end of 2021. Both OpenAlex and The Lens claim to be successors to Microsoft Academic.
The analysis highlights Technology, History and Science as prominent areas in the source structure around Microsoft Academic.
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.
High-confidence facts extracted from structured source data. Use them as anchors for further research.
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.
The extracted context around Microsoft Academic shows recurring relationship patterns in the source. For example, Microsoft Academic → Asia, Aside, Bing, Microsoft, Microsoft Academic Search, Microsoft Research, REST, The, The Academic Knowledge API, Zaiqing Nie Another extracted example is Microsoft Academic → Google Scholar, However, Microsoft Academic Search, Preliminary, Science, Scopus, The, Web. 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.
academic microsoft search research engine openalex 2021 data publications shut also indexed information using project developed 2016 technology database launched
TTTA extracted 30 structured relationships around Microsoft Academic. Examples in this analysis include Microsoft Academic → Current status → Inactive (No longer accessible after Dec. 31, 2021) and Microsoft Academic → Launched → February 22, 2016; 10 years ago (2016-02-22). The table shows each extracted connection, where it came from and its confidence.
| Subject | Predicate | Object | Confidence | Src |
|---|---|---|---|---|
| Microsoft Academic | Current status | Inactive (No longer accessible after Dec. 31, 2021) | 1.00 | infobox |
| Microsoft Academic | Launched | February 22, 2016; 10 years ago (2016-02-22) | 1.00 | infobox |
| Microsoft Academic | Owner | Microsoft | 1.00 | infobox |
| Microsoft Academic | Registration | Optional | 1.00 | infobox |
| Microsoft Academic | Type of site | Bibliographic database | 1.00 | infobox |
| Microsoft Academic | URL | academic.microsoft.com | 1.00 | infobox |
| Microsoft Academic | related to External links | Project | 0.60 | section |
| Microsoft Academic | related to External links | Microsoft Research | 0.60 | section |
| Microsoft Academic | related to history | Google Scholar | 0.60 | section |
| Microsoft Academic | related to history | The | 0.60 | section |
| Microsoft Academic | related to history | Preliminary | 0.60 | section |
| Microsoft Academic | related to history | Microsoft Academic Search | 0.60 | section |
The concept neighborhoods around Microsoft Academic bring nearby vocabulary together. In this analysis, examples include Microsoft, Search and Research. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
For Microsoft Academic, one of the stronger structural bridges in this analysis connects Microsoft Academic 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 Microsoft Academic to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Technology, History & Science, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
Source: Wikipedia — Microsoft Academic · EN edition · Analysis: TopicsToTalkAbout