(101 Introduction To Social Analytics+ 201 Boolean Mastery)

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201.1 Introduction to Booleans

Please watch the video, read the lesson below and take a quiz at the end of this lesson (bottom of this page).


Booleans are a type of query used in many information databases to capture relevant mentions to your topic of interest. For example, if you type apple into your Google search engine, these are some of the results you might see:


However, if you search for apple AND fruit, you will see the following results which are related to apple the fruit, and not the brand:


Booleans are also used in social listening tools such as Radarr to help capture relevant mentions and to exclude irrelevant mentions. This includes posts from various platforms such as social media sites, forums, blogs, news sites, and more. In Radarr, mentions about COVID-19 within Singapore looks something like this:



However, what you don’t see is how these mentions were captured, which was through Boolean queries. The following Boolean query was used to capture the COVID-19 mentions:



While this may seem a little confusing, everything will come together once you learn more about the main components of a Boolean in the next section.

201.1B Components of a Boolean

There are 3 key components needed to form a Boolean query – your keywords, operators, and location.

We’ll be using the following case study to guide us through this section:

Sonya, a social analyst at Adidas has access to our social listening tool, Radarr. She is interested in seeing what people around Asia are saying about COVID-19 pandemic. Let’s look at how Boolean queries can help her do this.

1 .Keywords

Keywords refer to the terms you want to capture data around, including unique terms such as hashtags (e.g. #COVID19) or social media handlers (e.g. @CNN).

If Sonya wants to track mentions around COVID-19, some of the keywords she can include in her Boolean are:



While this is not an exhaustive list, it should provide you with an idea of the type of keywords to include when putting together keywords for your Boolean. It is important to thoroughly research the topic you want to track so that the keywords included in your Boolean are as comprehensive as possible. In the next section of this course, you will learn how to research and write your own Booleans queries.


Operators are used to connect keywords together to specify what type of mentions you are looking for. The main operators used in Radarr are OR, NOT, AND, parentheses (), and quotation marks “ ”.

In the following exercise, you will learn how these 7 posts about COVID-19 might be captured differently with each operator:




OR is used to capture mentions that contain any of the keywords specified in your Boolean, which typically broadens your search results.

If Sonya wants to capture mentions about COVID-19, it would be good to include variations of COVID-19 that might be used online. An example of a Boolean would be:

“COVID-19” OR “Coronavirus” OR “#COVID19”

All 7 posts contained at least one of the keywords in the Boolean, which means that all 7 posts will be captured by this Boolean query:



In Radarr, this Boolean query would capture over 1.5 million mentions.





AND is used to capture mentions that contain a specific combination of keywords, which helps to narrow down your search results.

If Sonya wants to capture mentions about COVID-19 lockdowns, an example of a Boolean she can create is:

“COVID-19” AND “lockdown”

This means that a post has to mention both “COVID-19” and “lockdown” in order to be captured by this Boolean. As such, only 5 of the posts would be captured:


In Radarr, this Boolean search would capture around 13,000 mentions – significantly lower than the 1.5 million mentions we previously captured.




NOT is used to exclude mentions that contain specific keywords, which helps to reduce the volume of irrelevant mentions you may capture.

If Sonya wants to view mentions about COVID-19 that are not about vaccines, she can create a Boolean like this:

“COVID-19” NOT “vaccine”

Out of the 7 posts, only 4 were captured by this Boolean:



In Radarr, this Boolean would capture just over 1 million mentions, which still reduced the number of irrelevant or unwanted mentions around vaccines.



“ ” Quotations Marks

Quotation marks are used to capture an exact phrase of more than 1 keyword (“COVID-19 vaccine”) and symbols such as hashtags (e.g. “#COVID19”) and social media handles (e.g. “@CNN”).

If Sonya is looking to track mentions that contain the exact phrase ‘COVID-19 lockdown’, she should create the following Boolean:

“COVID-19 lockdown”

Only 2 mentions were captured by this Boolean. Even though Post 2 and Post 5 contained the keywords COVID-19 and lockdown, they were not captured because they were not next to each other in the posts.



In Radarr, this Boolean captured around 5,000 mentions. This is a much smaller volume of mentions, since a post needs to contain an exact keyword phrase in order to be captured.



( ) Parentheses

Parentheses are used to group keywords together so that operators such as OR, AND, or NOT can be applied to all the keywords within the brackets. This is especially useful if you want to track variations of keyword combinations.

If Sonya wants to track mentions that contain COVID-19 in relation to Singapore, her Boolean may include variations of both keywords:

(“COVID-19” OR “#COVID19”) AND (Singapore OR “#Singapore”)

With this Boolean, 3 posts that contained either the basic keyword or hashtag of COVID-19 and Singapore were captured:



In Radarr, this Boolean captured 18,000 mentions:




The last component of a Boolean is the location. This refers to the countries where you want to capture data from.

In Radarr’s Boolean query builder, you simply need to select your countries of choice from a dropdown list as such:


The geolocation of a post is determined differently across websites and social media platforms. For example, Twitter’s geolocation data is based on the specified location in a user’s profile page.

In the next section, you will learn in more detail about the Boolean research and preparation process.