Interview: Exploring Data Science at Brandwatch with Hamish Morgan
By Olivia SwainAug 23
Welcome to the fifth instalment of the Brandwatch tutorials. Today we are going to look not just at a single query, but at the main subjects of discussion around a whole industry or topic. If you want to monitor and manage a brand, it is crucial to understand the bigger picture, the context surrounding that brand, by analysing the global trends of the brand’s industry. Click here for the video that accompanies this post.
In Session 3 of the tutorial, we had a look at the themes surrounding one particular query. Let’s see how we can do the same not just for one query, but for its competitors too. We will use the same queries that we created in Session 2: Brighton, Lewes and Eastbourne are 3 cities from the South-East of England.
First, create a new empty workspace, and close its controls box. Then look in the list of components in the left-hand side of the screen. Components work on a single query by default, but some of them can also support multiple queries. By hovering your mouse over the component names, you will see small pop-up messages such as “Also available: Recurring Phrases for query groups”. Click on that precise link, and a new component will be added to your blank workspace. In the controls box of that component, pick your ‘Sussex towns’ query group, choose a date range (for example, the last 14 days), then click on ‘Load data’.
You will see a cloud of the most common phrases mentioned around your queries. In the snapshot above, you can see interesting phrases such as ‘Bonfire Night’ (a major event which happens every year in Lewes), NHS, police, and university-related stories, etc. The bigger the phrase, the more common it is. These are really quick insights into the online buzz surrounding the queries.
By clicking on ‘Change view’ and selecting ‘Data table view’, the display will change to a table with detailed metrics for each phrase: total volume across all queries and volume breakdown by site type.
In both the cloud and table views, clicking on a phrase name will open a pop-up, with the actual mentions containing that phrase. This can help you understand what the phrases are about, and who is mentioning them.
One query to join them all
One alternative approach is to create one single, generic query. Such a query can be defined using a combinations of brand names, for example:
brighton OR lewes OR eastbourne OR hove OR worthing
You can also use some more generic terms, which encompass the whole industry, such as ‘washing powder’ if you are monitoring a particular laundry product.
Once that single query is set up, you will be able to use all the single-query components to analyse the overall buzz for the whole industry. One caveat is that the bigger the single query is, the more complex and slower its analysis will be, and the likelihood of including less relevant data will be higher. So aim for a good compromise.
This is the end of the fifth tutorial, we hope you found it useful. Contact Us if you have any questions.