This article is an excerpt from the Shortform book guide to "Everybody Lies" by Seth Stephens-Davidowitz. Shortform has the world's best summaries and analyses of books you should be reading.
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What are the benefits of big data? Do you want to know how to use data well?
Despite all of the potential advantages, Seth Stephens-Davidowitz acknowledges that it’s easy to use big data ineffectively. To get the most out of big data, Stephens-Davidowitz says you should focus on its four main benefits: new types of information, unprecedented honesty, high resolution, and easy cause-effect analysis.
Keep reading for the four benefits of big data that are explained in Everybody Lies.
Benefit #1: New Types of Information
Stephens-Davidowitz says that one of the benefits of big data is that it opens our eyes to new types of information that weren’t previously available or that we might not previously have been able to study.
(Shortform note: While Stephens-Davidowitz is excited about how academic researchers can use text analysis—for example, he cites studies that use sentiment analysis to map narrative trajectories in works of fiction—most of the practical application of these techniques seems to take place in the business world. For example, businesses use text analysis and sentiment analysis to gauge customer interest and reactions, detect problems early, and improve customer service.)
Benefit #2: Honest Information
In addition to expanding the types and amounts of data we collect, Stephens-Davidowitz says that big data offers more honest information than we’ve ever had before. He points out that people tend to lie in traditional surveys. For example, people are unlikely to be totally honest about their sexual habits when talking to another person—even if that person is a stranger administering an anonymous survey.
Respondents will probably be more honest in an online survey than an in-person survey—but that still doesn’t solve the problem of self-deception. Stephens-Davidowitz argues that we’re often poor judges of our own thoughts and behaviors because we don’t want to acknowledge the less savory aspects of ourselves.
Benefit #3: High Resolution
Stephens-Davidowitz argues that one of the powers of big data is that it allows you to zoom in on specific subsets of data, which in turn allows new insights and new types of studies. (Shortform note: This benefit derives from another of the three Vs—volume.)
Benefit #4: Easy Cause-Effect Studies
The final benefit Stephens-Davidowitz says big data has is that it makes it easy to perform causal research. Scientific studies typically try to find cause-effect relationships by performing experiments that determine what impact a given variable has in a specific situation. In the social sciences, this research traditionally involves recruiting volunteers, dividing them into two or more groups, exposing some of the groups to the variable, and comparing those experimental groups to the control group.
Stephens-Davidowitz points out that this traditional experimental process requires a lot of funding, time, and other resources—and these factors limit the number of experiments researchers can do as well as the scope of those experiments. He says that big data research eliminates these problems, thereby vastly expanding the research we can do.
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Like what you just read? Read the rest of the world's best book summary and analysis of Seth Stephens-Davidowitz's "Everybody Lies" at Shortform .
Here's what you'll find in our full Everybody Lies summary :
- How people confess their darkest secrets to Google search
- How this "big data" can be used in lieu of voluntary surveys
- The unethical uses and limitations of big data
