Under the hamburger menu (☰) in Google Scholar you'll find Advanced search which gives you a lot more control over your search.

Let's take a look at each of the options:

With all of the words

With the exact phrase

With at least one of the words

Without the words

Documents that mention the words you put in this box will be excluded from your results. If you had leonardo in any of the first boxes and dicaprio in this box you will get matches for any document mentioning leonardo so long as it doesn't also mention dicaprio:

Leonardo DiCaprio image CC BY-SA Christopher William Adach.

leonardo -dicaprio

Once you've run the search, you'll get the above in the search box. Here the minus sign - in front of "dicaprio" is serving as what we might call a NOT operator: leonardo NOT dicaprio. Most databases will actually use the word NOT for this, rather than the minus sign, but the minus sign remains common in internet search engines like Google.

If you were searching for information about York but kept getting results about New York, you could do a search for york -"new york" and this will filter out any documents mentioning "New York". But be careful... maybe a really good article about York also mentions New York somewhere in it.

The other options

Going beyond Google Scholar

Most of the above examples can also be used in other databases too...

Generally when we search, the search engine or database we're using will look for documents that match all of the terms we entered. But these terms could appear anywhere in the record. For instance, a search for university of york would find documents mentioning:

• "...the University of York..."
• "...the Faculty of Liberal Arts at York University, Ontario..."
• "...the State University of New York..."
• "...the School of the Arts at York St John University..."

All four results match our search terms, but only one of the results is an exact match for the terms in the arrangement they were written.

If we wanted to search only for cases where the words university, of, and york appear next to each other in that order we can make use of something called phrase searching... in other words, we can stick double quotes around our terms to make them into a single entity: "university of york" — with this search, the only one of those four results we're getting back is the first one.

Another example

Most databases allow you to enter elaborate controlled searches using special words and characters known as operators. Particularly powerful among these operators are wildcard characters. These work like jokers in a deck of playing cards, able to stand in for other content...

Truncation

Imagine you were searching for items relating to chewy sweets. Articles mentioning any of the following might be useful to your needs:

• chew
• chews
• chewing [...gum]
• chewy
• Chewits

In most of the databases we subscribe to, you can use an asterisk (*) to stand for any potential word endings (as well as for the word itself). This method is called truncation.

Let's consider a search for chew*:

There might be some examples there that we're not happy about, but on the whole it might be advantageous to take this approach rather than to try to incorporate every possible inflection of the word into our search.

Think carefully about where the asterisk goes. You need it in just the right place to capture the words you want and not too much that's irrelevant.

Placing the asterisk

Let's take a look at what effect we'd get by placing the asterisk at different points in a word...

When truncating, think about the different word endings you might expect to get. Not all words will truncate effectively; for instance, say you were searching for policy / policies...

polic* would find both policy and policies but it would also find police and policing. You might need to formulate your search in a different way.

Wildcards within words

If you wanted to search for yogurt there are some variant spellings to consider:

• yogurt
• yoghurt
• yoghourt

In some databases you could use a wildcard character to stand in for none, one, or sometimes even more characters in a word.

The exact rules (and the wildcard characters used) vary from database to database, but here's an example of the sort of thing you might be able to achieve:

yog✱urt

...might retrieve...

yogurt

yoghurt

yoghourt

Some wildcards can also stand for a single interchangeable letter, for instance:

carameli?e

...will often retrieve...

caramelise

caramelize

Here's a table of some of the main database providers and their wildcards of choice:

	Single letter replacement	No letter or one letter	No letter or any amount of letters	End-of-word truncation
EBSCO	wom?n	colo#r	do*nut	truncat*
Ovid	wom#n	colo?r		truncat*
ProQuest, Scopus & JSTOR	wom?n	colo*r	do*nut	truncat*
Web of Science	wom?n	colo?r	do*nut	truncat*

Most bibliographic databases have some sort of advanced search option. Even YorSearch has an advanced search, and we've looked in detail at Google Scholar's advanced search interface.

Generally, an advanced search interface will look something like this:

Rather than just the one search box to play with, there'll be two or three, and maybe even the option to add more. Each box might be able to search different parts of the catalogue record, and you will be able to combine the different rows of your search in different ways to achieve different effects. The result is a lot more powerful than a single search box searching everything.

Scope and limits

You can usually set the scope of your search with a dropdown next to the search box. By default you will probably be searching all of the fields within a catalogue record, but you can limit to an individual field such as the title, the author or any keywords or subject headings. If you were looking for books by Charlotte Brontë rather than about Charlotte Brontë, you could limit your search to just search the Author field.

There may be additional limits you can apply to your search, such as date ranges. These might be on the advanced search form itself, or available to apply once you've got your results. We'll look more closely at these fliter controls in our sifting section.

Combining your search

Each row of your search can be combined using a logical operator: usually AND, OR, or NOT...

AND

Connect two rows of your search with AND to require a match on both rows.

OR

Connect two rows of your search with OR to have it match either of the rows.

NOT

Connect two rows of your search with NOT to match the first row and exclude any matches for the second row.

You can use these "Boolean operators" within the search box too. And you can even put bits of your search in brackets (like you would with mathematical formulae) to clear up any ambiguities when using multiple terms. For instance you might search for scones AND (jam OR cream) to find items that mention scones and jam or that mention scones and cream. Indeed, when you run your search using an advanced search form like the one above, you might find it gets translated into a search string with various operators and brackets peppered through it.

An advanced search form may lead you to creating very complicated searches like...

The problem with a big search like this is that one misspelling can bring the whole thing down. It's therefore better to build up a search like this gradually.

Keep your searches as simple as possible to avoid getting tangled up. But don't be afraid to combine terms if you find it helpful. With an advanced search form it's best to treat each row as being separated by an AND, and maybe have more than one alternate term in each row by using OR.

Building a search using a search history

Some databases will keep a history of each search you conduct. Usually this is just retained for the session, but some databases will even let you create an account to save your searches to return to at a later date.

You can often use this search history to combine previous searches into a more complicated search.

In Scopus and Web of Science you can find your search history at the bottom of the "Advanced search" page and use the Combine controls there to merge searches. Here's a typical example, where rows 1 to 4 have been steadily combined over rows 5 to 7:

This approach is handy for spotting any mistakes along the way, like line 2 where we misspelled "puppy" or "puppies". Sometimes a misspelling will still pick up results, which is quite fun! We're all fallible.

Building up a search like this also gives you a good sense of what every part of your search is doing, and the type of numbers it's getting.

Proximity operators allow you to look for a word within a certain distance of another word.

Imagine you were searching for recipes for chocolate cake. You could perhaps use a search like...

...but are there any problems with that approach?

It's a good search in terms of finding chocolate cake and chocolate cakes along with mentions of the word recipe, but it's possible that you'd get recipes that mention chocolate cake as an aside, while missing recipes that insert a word between chocolate and cake:

We need a way of locating those results where chocolate cake is close to recipe, or chocolate is close to cake. That's where proximity operators come in...

Proximity operators usually sit between two search terms, and include a number which represents the maximum number of words permitted between the two terms. Even Google lets you use an asterisk (*) to stand for unknown words between terms.

Using proximity operators

An example

In this example we'll use the operator NEAR/n

The search chocolate NEAR/4 cake* will find cases where there are 4 words or less between the word chocolate and the word cake*...

	0	1	2	3	4	5	6
✔ n=0	chocolate	cake
✔ n=1	chocolate	orange	cake
✔ n=2	chocolate	mint	marble	cakes
✔ n=2	cake,	wine	and	chocolate
✔ n=3	caked	thick	with	dark	chocolate
✔ n=4	cakes	that	are	rich	in	chocolate
✘ n=5	cake	was	superb	and	the	rich	chocolate

chocolate NEAR/4 cake*

Some databases will let you search directly against subject headings or keywords. These might be submitted by the author, or in some cases will be standardised subject headings imposed by the database cataloguers. Standardised headings use a controlled vocabulary that will be applied uniformly across articles on the same topic, irrespective of the terminology used in those articles. For example: articles about cats, kittens, and moggies might all be indexed under the uniform subject heading "felines".

Databases may also have a thesaurus feature which will map a search term (e.g. "cat") to the subject heading used (e.g. "felines").

In certain cases, subject headings may even be arranged in a hierarchy, for example "mammals" > "felines" > "cats, domestic", and may enable you to either search on a single level alone, or to explode at a point in that hierarchy so as to include all branches beneath.

There's a lot of stuff to find. How can you find the things you really need? In this bitesized session, we show you some advanced literature searching tricks.

Forthcoming sessions on :

There's more training events at:

Finding a single journal article can lead you to more texts on the subject. The author will have referenced other work to support their arguments, so looking at the references of a text you've found should lead you to similar material. 

Some databases will index these references within the article record, making them easier to locate. Some (e.g. Google Scholar, Scopus and Web of Science) will even link to later articles which have gone on to cite the text you've found.

By tracing the cited and citing articles, you can follow an academic argument as it develops through time.

The number of times an article has been cited can act as an indicator of that article's perceived importance within a topic. Bear in mind that this may not be an indicator of its quality -- it may be a notorious paper for the wrong reasons! Also, bear in mind that the older a paper is, the more chance it's had to be cited. An article published this year is unlikely to have had chance to be cited.