Available to the TASIS Community. Contact the US Librarian for log-in details or take a leaflet from the Library.
JSTOR is short for Journal Storage. Founded in the United States in 1995, JSTOR is an online database which provides access to full-text articles to hundreds academic journals, dating as far back as 1665. Subjects range from Archeology to Zoology.
JSTOR supports full-text keyword searching across all of the content on www.jstor.org. JSTOR generally includes all the content from articles, books, and pamphlets, cover to cover. This makes it possible to search front matter and back matter, letters to the editor, advertisements, and other types of material along with scholarly articles and book chapters. The default setting for search results is to show matches for only content licensed or purchased by the library.
Limiting a Search to a Specific Field
Use the drop-down boxes to limit search terms to the title, author, abstract, or caption text. Important to know:
- If you limit your search to the abstract field, you will search only a subset of the journal content on JSTOR. JSTOR doesn't create abstracts for content that was published without them; abstracts exist for only about 10% of the articles. Abstracts tend to be more common in certain disciplines (social sciences, sciences) and in more recently published content.
- Captions are searchable for much, but not all of the image content on JSTOR. Some images do not contain captions.
Combining Search Terms
Use the drop-down boxes to combine search terms using the Boolean operators, AND/OR/NOT and NEAR 5/10/25. The NEAR operator looks for the combinations of keywords within 5, 10, or 25 words places of each other. Important to know: the NEAR operator only works when searching for single keyword combinations. For example, you may search for cat NEAR 5 dog, but not "domesticated cat" NEAR 5 dog.
Narrowing a Search
Use the “Narrow by” options to search only articles, include/exclude book reviews, search for content published during a particular time frame, or in a particular language.
Limit an Article Search to a Specific Discipline(s)
You can focus an article search in specific disciplines and titles using the checkboxes in the discipline list under the "Journal Filter" section. Important to know: discipline searching is currently only available for searching journal content. Selecting this option will exclude ebooks from the search.
The format and display of search results is the same for Basic and Advanced searches.
- Use "Content Type" menu to filter results by journal articles, ebook chapters, and pamphlets.
- Use the "Subject" menu to limit results to journals related to specific subjects.
- Use the "Publication Date" menu to limit results to a certain publication time period.
- Use the "Access Level" menu to limit your results by tupe of access.
- Use the "Sort by" menu to view search results by relevance, oldest items, or newest items.
- Use the "Export Selected" menu to choose the export format
Relevance on JSTOR is a combination of many things. Key elements include:
- More unique terms in the text result in higher scores when searches contain those terms. For example, the keyword “epistemology" gets a greater boost than “university” because it is less common.
- Phrase matches are boosted higher than just keyword matches. A search for "the quick brown fox" will assign higher relevance to a document containing the exact words "the quick brown fox" than a document containing "the brown fox is quick."
- More recent content is given a slight boost.
1. JSTOR uses stop words, words that are too common so they will not be searched: IN AN AT THE A Do not use them unless they are preceded and followed by quotation marks (“ “).
2. When using quotation marks, JSTOR will search the terms as they appear. Therefore be sure of the correct order and spelling before using them.
3. Abstract: only 10% of articles in JSTOR have an abstract. Searching by abstract will greatly limit your search. Proximity search: the closer the words are, the more relevant they are to one another and to your search. Add fields for more complex connections. Think of synonyms when conducting your search. Eg. Gold Coast = Gana
4. Wildcard: the * replaces letters, thus broadening your search. e.g. afri* will give results containing: Africa, African, Africans African Africans Stem searching: use # symbol to found variations of a word. e.g. goose# will find articles with the words: goose, geese, goslings
5. You can select to only obtain results with images or contents TASIS can access (green tick).
6. You can limit your search by publication or subject. You can limit your search to any publication within one or more disciplines, by clicking the + next to the subject.
7. It helps to check multiple subjects for your first searches (then you can start to narrow them down). If you know a specific journal, you can select and search it, this will save you time. You can also view your search history. Once logged, you can check articles you are interested in and save citation. You can also email or export citation, by simply ticking the citations and selecting email or export options.
8. If you are struggling finding appropriate search terms, go to http://dfr.jstor.org
Use these guides as starting points for your research on JSTOR:
- Art and Art History Resources
- Ecology and Botany Resources
- Education Resources
- Exploring Rembrandt
- History Resources
- JSTOR Global Plants
- Language and Literature Resources
- Livingstone's Zambezi Expedition
- Mathematics and Statistics Resources
- Music Resources
- Political Science Resources
- Sociology Resources
- Sustainability Resources
- Understanding Shakespeare
- Understanding the U.S. Constitution
Click on the icon below to access the database:
For instructions on how to use the database and how to create an account, click HERE
Click on the icon above to access Text Analyser, or following this link.
Text Analyzer is a tool built by JSTOR Labs. With it, researchers can search for content on JSTOR just by uploading a document.
How it works
- Upload a document with text in it. This can be anything: a paper you are writing, an outline of a work in progress, an article you just downloaded, even a picture of a page of your textbook.
- The tool analyzes the text within the document to find key topics and terms used, and then uses the ones it deems most important — the "prioritized terms" — to find similar content in JSTOR.
- Review the results and download any articles you're interested in.
- Adjust the results you are seeing by adding, removing or adjusting the importance of the prioritized terms.
You can upload or point to many kinds of text documents, including: csv, doc, docx, gif, htm, html, jpg. If the file type you are using is not compatible, just cut and paste any amount of text into the search form to analyze it.
Hints and suggestions
- The more text within your document, the better.
- Be sure to use the controls to add, remove and adjust the importance of your prioritized terms. Add your own term or phrase if you're not seeing it.
- The results are created using only the prioritized terms: be sure to add any identified term you want included.
- If you access Text Analyzer using your phone, a camera icon will appear — use it to take a picture of any page of text and search with that.
- To run Text Analyzer on the text of a webpage — whether it's a Google Doc or a NY Times article — drag and drop or paste the URL into the search box.
- Get creative with the kinds of documents you search with: try your class syllabus, the webpage of a news article, or the first paragraph or outline of a paper you're writing.
Does uploading my paper to Text Analyzer mean that it is now in JSTOR? No. In fact, JSTOR does not even store the document you use with Text Analyzer. The tool analyses the text within the document and extracts the relevant terms without retaining the text itself.
I get some pretty weird recommended topics. What happened? What should I do? Text Analyzer is still in beta and is, frankly, a machine. It is not perfect. When it recommends strange topics, this can be because there was not as much text for it to analyse or because the text contains language (such as an extended metaphor) that "fools" Text Analyzer into thinking it's about something it's not. It can also happen if the topics covered or language used doesn't map well to the rest of the content in JSTOR. JSTOR has a wide variety of content and covers many disciplines, but it doesn't have everything. Usually, when Text Analyzer recommends a topic that is not what you are looking for, all you need to do is remove it from the "Prioritised Term" list. If you're still not seeing what you're looking for, try adding a few terms that are more on-point.
How does Text Analyzer *do* this? Getting to recommended articles is a multi-step process involving a number of different technologies. First, Text Analyzer extracts the text from the document or image. For Word or PDF documents (for example), it just pulls out the existing text. For images without embedded text (for example, a picture of a page of text), it performs Optical Character Recognition (OCR) to find the text. Next, the tool analyses the text to find topics (e.g. subjects) and entities (people, places and organisations) within it. The topics are found by using a "topic model," a tool used in natural language processing. In a topic model, a topic is composed of many individual terms that suggest the topic is being discussed. The higher the density of those terms in the document, the more likely that a particular topic is being discussed. For example: if the terms "carrots," "seed," "harvest," and "backyard" are used a lot, the topic model might suggest that the topic being discussed is "Gardening," even if the term itself is never used. The topic model used in Text Analyzer was created by analyzing all the scholarship in JSTOR. In doing so, we were able to leverage JSTOR Thesaurus, a controlled vocabulary of over 50,000 terms describing the content within JSTOR, for help in both naming the topics and in "training the content model." Last, the tool uses what it "thinks” are the most relevant topics and entities to find similar content in JSTOR. This similar content is presented on the results screen along with the topics and entities it found.