Microsoft Academic - Detailed Review
Research Tools
Microsoft Academic - Product Overview
Microsoft Academic: An Overview
Primary Function
Microsoft Academic was a free internet-based academic search engine developed by Microsoft Research. It was launched in 2016 as a successor to Microsoft Academic Search. The primary function of Microsoft Academic was to provide a comprehensive platform for searching academic publications and literature, making it a valuable resource for researchers, scholars, and students.
Target Audience
The target audience for Microsoft Academic included researchers, scholars, students, and anyone involved in academic research. It was particularly popular in the field of computer science, where it had the most complete indexing of information. However, its scope extended to various academic disciplines, making it a useful tool for a broad range of users.
Key Features
- Comprehensive Indexing: Microsoft Academic indexed over 260 million publications, including 88 million journal articles. This extensive database made it a significant competitor to other academic search engines like Google Scholar, Web of Science, and Scopus.
- Author and Organization Profiling: The platform profiled authors, organizations, keywords, and journals, providing detailed information and making the dataset available as open data.
- Citation Information: It offered advanced citation analysis, including metrics such as the number of sources, *g*-index, and *h*-index.
- Semantic Search Technologies: Microsoft Academic used machine learning, semantic inference, and knowledge discovery to improve search results. The data was crawled and indexed by the Bing search engine.
- API and Tools: The Academic Knowledge API allowed for advanced research purposes, providing information retrieval from the underlying database using REST endpoints.
Closure
Microsoft announced the retirement of the Microsoft Academic website and APIs on December 31, 2021. However, the dataset was merged into OpenAlex, ensuring the continuity of the academic data resource.
Microsoft Academic - User Interface and Experience
User Interface of Microsoft Academic
The user interface of Microsoft Academic, a research tool within the AI-driven product category, is crafted to provide a seamless and informative experience for users.Search and Query Interpretation
The homepage features a prominent search box that utilizes semantic query interpretation to guide users to relevant information quickly. For non-signed-in users, the search box demonstrates the semantic search language and offers query suggestions through a dropdown menu. If no semantic interpretation is possible, the query defaults to a keyword-matching algorithm.Search Results and Filters
The search results page is laid out to facilitate easy information processing. It displays 10 results per page, an increase from the previous 8, and includes whitespace and visual effects to enhance readability. The results are accompanied by filters that highlight topics and entities within the result set, ranked by relevance. If semantic entities are identified in the query, they are presented in cards on the right side, helping users see how their query has been interpreted and offering additional areas for exploration.Entity-Specific Pages
Each entity in the Microsoft Academic Graph, such as papers, authors, institutions, journals, and conferences, has its own dedicated page. For example, viewing a paper provides details like references, citations, and related papers, all of which are filterable. Institution pages display publication data along with analytics for top authors, journals, and conferences. Journals and conferences also have specific data, including publishing statistics and important dates, respectively.Analytics and Data Visualization
The platform offers extensive analytics features, including rankings and trending data for authors, institutions, journals, and conferences. These analytics are presented in charts, and the data behind them is downloadable, allowing users to further analyze or visualize the information. This feature enhances the user experience by providing valuable insights and the ability to customize data visualizations.Ease of Use
The interface is designed to be user-friendly, with clear and intuitive navigation. The use of semantic search and query suggestions helps users find relevant information quickly, even if they are not familiar with the exact terminology. The visual layout and filters make it easy to sift through results and identify key information.Overall User Experience
The overall user experience is enhanced by the integration of the Microsoft Academic Graph, which provides a vast amount of data and insights. The ability to explore related entities and view detailed analytics makes the platform valuable for researchers and academics. The downloadable data and customizable visualizations add to the user’s ability to engage deeply with the information, making Microsoft Academic a comprehensive and engaging research tool. Microsoft Academic - Key Features and Functionality
Microsoft Academic Overview
Microsoft Academic, now part of Microsoft’s research tools, is a sophisticated academic search engine that leverages AI to streamline and refine the search process for researchers. Here are the main features and how they work:
Semantic-Based Searches
Microsoft Academic 2.0 integrates semantic search capabilities, allowing users to search for papers by topic, author’s home institution, venue of publication, title, and author name. This AI-driven feature enhances the accuracy and relevance of search results, making it easier for researchers to find specific information.
Microsoft Academic Graph (MAG)
The platform uses the Microsoft Academic Graph (MAG), which shows citation relationships among publications and authors. This graph helps in visualizing the connections between different research works and authors, facilitating a deeper analysis of academic networks and citation patterns.
Academic Knowledge API
The Academic Knowledge API allows users to combine the indexing power of Bing with the MAG to receive a histogram of related publications, journal entries, presentations, and authors. This API provides a user-friendly interface for accessing and analyzing large amounts of academic data.
Citation List Feature
Microsoft Academic includes a “Cite” feature that enables users to collect multiple papers on a citation list and then download or copy them as a batch. The citations can be exported in formats like ECAM-376 for Microsoft Word (.xml file) and BibTex, or copied in MLA, APA, and Chicago styles. This feature simplifies the process of managing references and integrating them into documents using Microsoft Word.
Integration with Microsoft Word
The citation list can be easily imported into Microsoft Word, leveraging Word’s integrated reference manager. This integration supports various citation styles and allows users to save their work directly to the cloud, making it accessible on any device.
AI-Powered Search and Indexing
Microsoft Academic uses AI to “discover and index” new information, growing its database which currently includes over 210 million entries. This continuous updating ensures that researchers have access to the latest academic content.
User-Friendly Interface
The platform offers a user-friendly interface that makes it easy to search, manage, and analyze academic data. The interface is designed to be intuitive, allowing researchers to focus on their work rather than learning complex search techniques.
Conclusion
In summary, Microsoft Academic leverages AI to enhance search accuracy, provide comprehensive citation management, and offer a seamless integration with other Microsoft tools like Microsoft Word. These features make it a valuable resource for researchers, helping them to find, organize, and analyze academic information more efficiently.
Microsoft Academic - Performance and Accuracy
Evaluating the Performance and Accuracy of Microsoft Academic
Evaluating the performance and accuracy of Microsoft Academic, a free academic search engine and citation index, reveals several key points and areas for improvement.
Accuracy in Document Retrieval
Microsoft Academic’s accuracy in retrieving journal articles is significant, but it has its limitations. The optimal method for finding journal articles with DOIs involves searching by title and then filtering out those with incorrect DOIs, which yields a recall of 89.6% on average.
For articles without DOIs, the best approach is to search by title and then filter out matches with dissimilar metadata, such as publication year, author, or journal name, achieving an average recall of 89.1%.
Citation Accuracy and Correlation
Microsoft Academic’s citation counts show a high correlation with those from Scopus and Web of Science. For instance, Microsoft Academic’s citations were found to be similar to those of Scopus (97% correlation) and Web of Science (108% correlation), although they were lower compared to Google Scholar (59% correlation).
However, the h-index, a measure of an author’s impact, was comparable to Scopus but only 77% of that from Google Scholar and 113% of that from Web of Science.
Data Quality and Limitations
While Microsoft Academic is effective, it has some data quality issues. For example, only about 89.5% of the journal articles had the correct publication years listed.
Additionally, the database may not cover all fields equally well, and the recall figures can vary significantly across different fields. The recall for title-only queries ranged from 67.0% to 100% across various fields.
User Experience and Usability
Initial versions of Microsoft Academic 2.0 faced usability issues, such as the lack of tutorials or instructions, which confused first-time users. However, Microsoft has been working to improve this by integrating a social network for academics to share information and instructions.
Data Collection and Indexing
Microsoft Academic uses data from publishers and the Bing web search engine to create its database. It employs data mining techniques to extract information such as authors, institutions, and publication venues. However, this process can be error-prone, particularly in author name disambiguation and document matching.
Future Directions and Discontinuation
As of December 31, 2021, the Microsoft Academic website and Project Academic Knowledge were no longer accessible. Microsoft Research encouraged users to transition to other equivalent services, indicating a shift towards community-driven approaches for academic research.
Conclusion
In summary, Microsoft Academic demonstrates strong performance in retrieving journal articles and correlating citation counts with other major academic databases. However, it faces challenges in data quality, particularly with publication years and author disambiguation, and has undergone significant changes in its availability and user interface.
Microsoft Academic - Pricing and Plans
Free Options for Students and Educators
Microsoft offers free access to Office 365 Education for students and educators through their institutions. This includes web versions of Word, Excel, PowerPoint, OneNote, Microsoft Teams, and Microsoft 365 Copilot Chat, along with additional AI-based tools for learning and work. Students need a valid school email address to access these tools.
Microsoft 365 Education Plans
For faculty and institutions, Microsoft provides several subscription plans:
- Microsoft 365 A3 for Faculty: This plan costs $69.00 per year and includes a comprehensive suite of tools such as Office apps, Microsoft Teams, and other educational resources.
- Microsoft 365 A5 for Faculty: This plan is priced at $129.00 per year and offers more advanced features, including additional security and compliance tools.
Specific Tool Subscriptions
There are also subscriptions available for specific tools:
- Microsoft 365 Apps for Faculty: This plan is $27.60 per year and includes access to Office applications.
- Microsoft Visio Online Plan 1: Priced at $12.00 per year, this plan provides online diagramming and design tools.
- Microsoft Visio Online Plan 2: At $26.40 per year, this plan offers more advanced features for diagramming and design.
- Microsoft Project Online Plan 3 and Plan 5: These plans are priced at $72.00 and $132.00 per year, respectively, and provide project management tools.
Security and Mobility Plans
Additional plans focus on security and mobility:
- Microsoft Enterprise Mobility Security A3 and A5: These plans cost $22.80 and $36.00 per year, respectively, and include security and mobility management tools.
- Microsoft Intune for Education: This plan is $8.28 per year and provides device management capabilities.
Other Educational Tools
Other tools like Minecraft Education Edition are available at $6.20 per year, which integrates game-based learning into educational curricula.
Azure AI Services
While not specifically categorized under academic pricing, Azure AI services are available for educational institutions. However, the pricing for these services is not tailored specifically for academic use and varies based on the service selected. For example, Azure AI services include options like Azure OpenAI Service, Azure AI Search, and Azure AI Vision, each with its own pricing structure.
Summary
In summary, Microsoft’s academic pricing is largely centered around providing free or discounted access to essential tools for students and educators, with various tiered plans available for faculty and institutions based on their specific needs.
Microsoft Academic - Integration and Compatibility
Integration and Compatibility of Microsoft’s Academic Tools
When discussing the integration and compatibility of Microsoft’s academic tools, particularly those within the Microsoft 365 Education suite, it’s clear that these tools are designed to be highly integrative and compatible across various platforms and devices.
Learning Management System (LMS) Integrations
Microsoft 365 Education tools, such as Microsoft Teams, OneDrive, and other Microsoft 365 applications, can be seamlessly integrated with popular Learning Management Systems (LMS) like Canvas, Schoology, Blackboard, D2L/Brightspace, and Moodle. These integrations are facilitated through the Learning Tools Interoperability (LTI) standard, ensuring secure and compliant interactions. For example, the Microsoft OneDrive LTI app allows educators to attach Microsoft 365 files, distribute cloud assignments, and collaborate on documents in real-time, all from within their LMS.
Microsoft Teams and OneDrive Integration
Microsoft Teams can be integrated with LMS systems to manage course content, create assignments, and facilitate hybrid learning. This integration enables educators to assign tasks, grade assignments, and conduct meetings directly from the LMS interface. The OneDrive LTI app enhances this by allowing users to access and organize their personal and course files, and to collaborate on shared documents.
Cross-Platform Compatibility
Microsoft 365 Education services, including Office 365, Microsoft Teams, OneDrive, and SharePoint, are compatible across various devices and platforms. These services can be accessed via web browsers, desktop applications, and mobile apps, ensuring that users can work efficiently regardless of their device or operating system.
Microsoft Copilot Integration
While Microsoft Copilot is not specifically labeled as an “academic” tool, it integrates well with the Microsoft 365 suite, which is widely used in academic settings. Copilot can assist users in generating content, providing suggestions, and automating tasks within Microsoft applications such as Word, PowerPoint, and Excel. It also integrates with Microsoft Teams to suggest responses, translate languages, and summarize meetings, making it a valuable tool for both educators and students.
Administrative and Deployment Support
Microsoft provides comprehensive support for IT administrators to deploy and manage these integrations. Detailed guides are available for deploying Microsoft OneDrive LTI, Teams Meetings LTI, and Class Teams LTI across different LMS platforms, ensuring a smooth and secure integration process.
Conclusion
In summary, Microsoft’s academic tools are highly integrated with various LMS systems and are compatible across a range of devices and platforms, making them versatile and efficient for educational use. However, specific details about a dedicated “Microsoft Academic” product in the Research Tools AI-driven category are not available in the provided resources, suggesting that such a product may not be explicitly defined or may be part of the broader Microsoft 365 Education suite.
Microsoft Academic - Customer Support and Resources
Microsoft Academic Overview
When it comes to Microsoft Academic, which is a research tool within the Microsoft ecosystem, the primary focus is on providing a comprehensive search and analysis service for scholarly works rather than traditional customer support options.
Key Features and Resources
Search and Analysis
Microsoft Academic offers an extensive database of scholarly articles, conference papers, patents, theses, and more. It allows users to search and filter results by date range, author, affiliation, field of study, journal, and conference.
Analytical Tools
The platform includes tools for visualizing citation graphs, identifying influential authors, and exploring academic trends and collaborations. Users can create profiles to showcase their publications, citations, and collaborations, facilitating networking among researchers.
Integration with Microsoft Office
Microsoft Academic seamlessly integrates with Microsoft Office tools like Word and PowerPoint, enabling easy import of citations, creation of bibliographies, and management of references.
Support and Resources
While Microsoft Academic itself does not offer dedicated customer support in the form of phone or chat services, users can rely on several general resources:
Microsoft Support Services
For general issues related to Microsoft products, users can access support through the Microsoft Office Support home page or other Microsoft support channels. However, these are not specific to Microsoft Academic.
Community and Forums
Users might find help through community forums and support pages related to Microsoft products, although these may not be specifically tailored to Microsoft Academic.
Documentation and FAQs
The Microsoft Academic service likely includes documentation and FAQs within its interface, but detailed customer support options are not explicitly outlined for this specific tool.
Conclusion
In summary, Microsoft Academic is more of a self-service research tool with integrated analytical features and Microsoft Office compatibility, rather than a product with extensive customer support options. For any broader support needs, users would need to rely on general Microsoft support services.
Microsoft Academic - Pros and Cons
Advantages of Microsoft Academic
Comprehensive Coverage and Metadata
Microsoft Academic 2.0 offers broad coverage of academic literature, similar to Google Scholar, and provides structured and rich metadata, comparable to Scopus and Web of Science. This combination makes it a powerful tool for bibliometric, scientometric, and informetric analyses.Semantic Search Capabilities
The platform features a semantic search engine that allows for more accurate and refined searches. Users can use semantics-based queries to streamline their results, making the search process more efficient and accurate.Citation Accuracy
Microsoft Academic 2.0 includes only validated citations, dropping those deemed not credible. This ensures a higher level of citation accuracy compared to some other databases. For instance, its citations were shown to be similar to those of Scopus and Web of Science, although less than those of Google Scholar.User-Friendly Features
The platform integrates features from various other academic research tools, such as a social network for academics similar to ResearchGate. It also offers tools for analyzing citations and frequency distributions through the Academic Knowledge API, which is relatively inexpensive at $0.25 per 1,000 queries.H-Index and Citation Metrics
Microsoft Academic 2.0 performs well in terms of the h-index, a measure of an author’s impact. It was comparable to Scopus and even outranked Web of Science in some metrics, although it fell short compared to Google Scholar.Disadvantages of Microsoft Academic
Initial Glitches and User Confusion
When first introduced, Microsoft Academic 2.0 lacked tutorials and instructions, leading to confusion among first-time users. The small icons and symbols were not defined, and users were not aware that they could use phrases instead of single words for queries.Data Limitations
Despite its improvements, the database still relies heavily on web pages for its data, which can lead to limitations in coverage. It is expected to improve with continued revisions and growth, but currently, it may not match the breadth of coverage offered by other established databases like Google Scholar.Bias and Accuracy Issues
Like other AI-driven tools, Microsoft Academic can inherit biases from the data it is trained on. If the data contains biases, the AI system may perpetuate them. Additionally, there is a risk of “hallucination” where the system generates information that is irrelevant, illogical, or entirely false.Dependence on Valid Data
The accuracy of Microsoft Academic’s metrics and analyses depends on the quality and validity of the data it indexes. If the data is flawed or incomplete, the results will reflect these shortcomings.Conclusion
Microsoft Academic 2.0 offers several significant advantages, including its comprehensive coverage, semantic search capabilities, and accurate citation metrics. However, it also faces challenges such as initial user confusion, data limitations, and potential biases. As the platform continues to evolve, addressing these issues will be crucial to its effectiveness and reliability. Microsoft Academic - Comparison with Competitors
Microsoft Academic
Microsoft Academic, particularly its 2.0 version, is distinguished by its semantic search capabilities and the use of the Microsoft Academic Graph (MAG). Here are some of its key features:Key Features
- Semantic Search: It uses semantic-based searches to provide more accurate results, allowing users to refine their searches based on authors, topics, journals, and conferences.
- Microsoft Academic Graph (MAG): This graph engine facilitates the discovery and indexing of new academic papers, including over 210 million entries, and shows citation relationships among publications and authors.
- Academic Knowledge API: This API allows users to combine the indexing power of Bing with MAG, providing detailed metadata and frequency distributions.
Alternatives and Comparisons
Consensus
Consensus is another AI-powered academic search engine that offers several features that differentiate it from Microsoft Academic:- Large Language Models (LLMs) and Vector Search: Consensus uses LLMs and vector search to deliver precise insights from over 200 million peer-reviewed papers. It includes features like the Consensus Meter, which shows the degree of agreement among studies on a particular topic.
- Advanced Filters: Users can filter results by study design, sample size, and methodology, making it highly suitable for literature reviews.
Connected Papers
Connected Papers is a tool that generates visual literature maps to help researchers explore related articles:- Visual Literature Maps: It creates graphs to illustrate how different papers are related, which is particularly useful for multi-disciplinary research.
- Free and Subscription Models: It offers free use for up to 5 graphs a month, with an academic subscription for unlimited use.
Inciteful
Inciteful provides related papers to key articles and illustrates their relationships:- Literature Relationships: It helps users see how different papers are connected, making it easier to identify key research in a field.
- Free to Use: Inciteful is free, making it an accessible alternative for researchers.
Perplexity AI
Perplexity AI is focused on providing concise, accurate answers with citations:- Citation-Driven Responses: It synthesizes information from multiple sources and provides citations, ensuring transparency and reliability.
- Free Access: As of now, Perplexity AI is free, making it a cost-effective option for researchers.
Unique Features and Choices
- Semantic Search vs. Vector Search: Microsoft Academic’s semantic search capabilities are unique but can be compared to Consensus’s use of vector search, which also provides precise insights but through different methodologies.
- Integration with Microsoft Ecosystem: Microsoft Academic’s integration with Bing and the Microsoft Academic Graph makes it a strong choice for those already using Microsoft tools. However, this also limits its utility outside the Microsoft ecosystem.
- Cost and Accessibility: While Microsoft Academic requires the use of the Academic Knowledge API (which has a cost associated with it), tools like Consensus, Connected Papers, and Perplexity AI offer various free and subscription models, making them more accessible to a broader range of researchers.
Microsoft Academic - Frequently Asked Questions
Here are some frequently asked questions about Microsoft Academic, along with detailed responses:
What is Microsoft Academic?
Microsoft Academic is a next-generation academic search tool that utilizes AI semantic search algorithms to identify key authors, topics, conferences, journals, and institutions across all disciplines. It scans publishers, societies, and open web content to provide comprehensive scholarly records.
What features does Microsoft Academic offer?
Microsoft Academic offers several key features:
- It contains over 252 million scholarly records and is growing quickly.
- It ranks top topics, descriptors, publication types, authors, journals, repositories, and institutions.
- It allows for sorting, alerting, downloading, and citation analysis tools.
- It includes powerful citation and disciplinary visualizations.
- It provides article “cited by” analysis lists.
- Users can manage saved citations, share lists, and receive notifications through personal account features.
- The service is straightforward and free to search.
How does Microsoft Academic’s search functionality work?
Microsoft Academic uses a semantic search engine that leverages entities associated with a paper, such as fields of study, journal, author, and affiliation. If semantic search fails, it resorts to traditional search terms. This approach returns relatively few but very accurate results. The search interface also offers various filtering and sorting options to refine results.
What is the Microsoft Academic Graph (MAG)?
The Microsoft Academic Graph (MAG) is the underlying data structure of Microsoft Academic. It is built by crawling the web for publisher websites, university repositories, researcher and departmental web pages, etc. The MAG contains over 150 million entities and billions of relationships, including citation relationships among publications and authors.
How can I access the raw data from Microsoft Academic?
The raw data from Microsoft Academic can be accessed through the Academic Knowledge API. This API allows users to retrieve structured and rich metadata, including aggregated citation counts and frequency distributions of citations, at a relatively low cost of $0.25 per 1,000 queries.
How does Microsoft Academic compare to other academic search engines?
Microsoft Academic combines features from various other academic research search engines:
- It offers broad coverage similar to Google Scholar.
- It provides structured and rich metadata similar to Scopus and Web of Science.
- It includes a social network aspect similar to ResearchGate.
Studies have shown that citation analyses with Microsoft Academic yield similar results to those from Scopus and Web of Science in terms of indicators like the h-index and rank correlations of citation counts.
Is Microsoft Academic free to use?
Yes, Microsoft Academic is free to search. Users can access its features without any cost, although using the Academic Knowledge API for accessing raw data requires a small fee.
What kind of data quality can I expect from Microsoft Academic?
While the data quality is generally good, there are some discrepancies. For example, 89.5% of the publication years are correct, 7.0% differ by ±1 year, and 3.5% feature larger differences. Additionally, 95.1% of the journal articles list the correct number of authors.
Can I refine my search results in Microsoft Academic?
Yes, you can refine your search results using various filters such as date range, author, affiliation, field of study, journal, and conference. The search interface also offers semantic query suggestions to help refine your search.
How does Microsoft Academic support citation analysis?
Microsoft Academic provides powerful citation analysis tools, including “cited by” analysis lists, citation visualizations, and the ability to calculate a wide range of bibliometric indicators such as the h-index and citation distributions through the Academic Knowledge API.
Microsoft Academic - Conclusion and Recommendation
Final Assessment of Microsoft Academic
Microsoft Academic, although it has undergone significant changes and is now transitioned to Open Researcher and Contributor ID (ORCID) and other platforms, had established itself as a formidable tool in the research and academic community. Here’s a summary of its strengths and who would benefit most from its features.Key Strengths
- Comprehensive Database: Microsoft Academic boasted an extensive database with over 194 million records, including preprints, working papers, and dissertations, making it a valuable resource for researchers across various fields, particularly in computer science, social sciences, and humanities.
- Advanced Search Interface: The platform offered a sophisticated search engine with ample filtering and sorting options, enabling users to refine their searches efficiently. It also utilized AI technologies to populate its database, making it faster at indexing new publications compared to traditional citation indexes like Web of Science and Scopus.
- Free Access to Data: The Microsoft Academic Graph provided free access to a huge, well-structured, and detailed dataset, which was a significant advantage over competitors like Google Scholar. This data was accessible via API or full data-dump, making it convenient for large-scale analysis of scholarly communication.
Who Would Benefit Most
- Researchers: Academics and researchers in various fields, especially those in computer science, social sciences, and humanities, would greatly benefit from the broad coverage and detailed metadata provided by Microsoft Academic.
- Commercial Enterprises: Companies involved in research and development, as well as those analyzing scholarly communication, could leverage the comprehensive and freely available data for their projects.
- Students and Educators: Students and educators could use the platform for literature reviews, research papers, and other academic tasks due to its ability to quickly find relevant publications and provide structured metadata.