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COMP 282: Data Structures & Algorithms

Basic Search Tips

Brainstorm Your Keywords

Unlike Google, Library Databases can't understand full sentences. Instead, you'll need to identify the most important ideas, or keywords, for your topic. 

Sample research question: 

How does algorithmic bias in machine learning impact people of color?

Next, you'll want to brainstorm similar and related terms for each of your keywords. There are usually several ways to search for the same concept, so including synonyms and other related terms will help you get a more complete picture of your topic. As you search, you might also want to take note of any specialized terminology that comes up in scholarly articles -- those can make great additional keywords.

  • algorithmic bias
    • algorithmic fairness
    • data bias
  • machine learning
    • artificial intelligence
    • AI
  • people of color
    • race
    • ethnicity


Screenshot of OneSearch Filters, with the locations of 'peer-reviewed journals,' 'available online at CSUN,' resource type,' and 'dates' highlighted and numbered

Filter Your Results

OneSearch has many built-in filters to help you narrow down your search results. To get started, locate the "Refine My Results" box on the left side of the screen.

Useful Filters:

  1. Resource Type
    • Filter results based on the type of resource (article, book, dataset, etc.)
  2. Date Range
    • Narrow your search results to sources published during a specific date range
  3. Peer-Reviewed
    • Limit your search to scholarly journals only
  4. Available Online at CSUN
    • Only view items that are fully available online

Evaluating Online Sources

Video Transcript

Sort Fact from Fiction Online with Lateral Reading: Video Transcript

What is Lateral Reading? We live in an era of information overabundance. This demands that we be more discerning. Instead of accepting information at face value, we should always ask this one important question. Who’s behind the information?

The Stanford History Education Group conducted a study with Stanford undergraduates, professors from four different universities, and professional fact checkers to determine the most effective methods for evaluating digital information. There were dramatic differences in how intelligent people looked at the Web.

Many smart undergrads and esteemed professors evaluated a site by reading vertically, staying on the site and reading it as if it were a printed document. They focused on the site’s look, its aesthetics, graphics, and overall appearance. They were deceived by an official-looking logo or the name of the organization. They attributed importance to the .org in the URL without realizing that .org is an open domain. Any individual or group can buy a .org domain without passing a character test or proving they’re working for social betterment. They examined scholarly references and research reports without realizing that unlike an academic journal, on the Web, anything goes. Intelligent people equipped with critical thinking skills were often taken in by slick web pages.

Professional fact checkers approach the web differently. They understood that on the Web, what you see is often not what you get. The Web is treacherous territory and you can’t let your eyes deceive you. Landing on an unfamiliar site, they didn’t waste precious time engaged in close reading. Instead, they opened new tabs in their browser and read laterally. Rather than spending time on a site like the Employment Policies Institute, they turned to the broader Web. They clicked on a New York Times article about the Employment Policies Institute entitled “Fight over Minimum Wage Illustrates Web of Industry Ties.” They scanned the Wikipedia entry, which describes the institute as “a fiscally conservative think tank, particularly aimed towards reducing the minimum wage.” “Its staff work for a public affairs firm owned by Richard Berman.” A search for Richard Berman leads to a 60 Minutes report which labels Berman as “Dr. Evil” for his use of nonprofit front groups that advocate on behalf of his corporate clients.

Only 40% of bright Stanford students were able to make the link to Berman. 100% of the fact checkers did, often in a fraction of the time. Lateral reading was the reason why. Our research studies have shown that lateral reading can be taught. Students in classes that completed civic online reasoning lessons significantly increase their ability to accurately judge websites compared to a control group. Lateral reading stands in sharp contrast to many methods for teaching digital literacy. These methods focus on long checklists of questions and keep students’ eyes on a single site before they’ve even established that the site is worth their time. Although the basic idea of lateral reading is simple, becoming skilled at it takes practice. Students need to see examples of lateral reading and practice it with a range of sources. They also need to know when they found a reliable news source or one that’s known for conspiracy theories.

Lateral reading helps students to find better information on line and to become informed and more thoughtful members of society.

Advanced Search Tips

Combining Search Terms Using Boolean Operators


Venn diagram labeled 'python' and 'code' with the overlapping area between the two circles highlighted

Search results must:


"Python AND Code"

Useful for narrowing search results and filtering out irrelevant results.


Venn diagram labeled 'python' and 'ruby' with both circles and overlapping area highlighted

Search results must:


"Python OR Ruby"

Useful for broadening search results and grouping together synonyms, variations, and similar keywords.


Venn diagram labeled 'python' and 'snake' with python circle minus the overlapping area highlighted

Search results must:


"Python NOT Snake"

Useful for removing irrelevant results, particularly for keywords that have multiple meanings.


Most databases allow you to use wildcard characters in your searches, allowing you to search for one or more unknown characters. This is particularly useful for keywords that share the same root or for variations in spelling. The most common wildcard character is the asterisk (*), although some databases use exclamation marks (!), question marks (?), or the hash symbol (#) instead. 


program* = program, programmer, programming, programmed, programmatic, etc.

data* = data, database, dataset, etc.

comput* = compute, computer, computation, etc.

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