09-09-2016 04:59 AM - last edited 11-07-2016 16:13 PM
This Social Media Analysis Report captures data from the official Robot Wars Facebook page.
As a long-standing fan of the UK TV show “Robot Wars”, I was very excited when it came back on the air on BBC Two in the summer of 2016.
Since I am unlikely to ever build a robot myself, I thought the best way I could contribute to this momentous event was by using my expertise in data visualisation. I thought it would be interesting to analyse public reaction to the show. To do this, I decided to track activity on the show’s official Facebook page by capturing the community interactions (Likes, Comments and Shares) that stemmed from official posts made on this page.
The first page shows an in-depth analysis of community interactions. This can be filtered by Episode, allowing users to track how the level of interactions changes over time (please note that deselecting all Episodes from the menu will display outcomes for the full period from 1st June 2016).
The right-hand section of this page analyses the sentiment of the comments, using the Text Analytics API available from Microsoft Cognitive Services. This tool analyses text and returns a % score based on the sentiment expressed (i.e. whether it is a positive, negative or neutral reaction).
I need to credit DataChant here for his excellent tutorial on using the Text Analytics API to enable sentiment analysis of social media posts. If you're keen to replicate the kind of analytics I've used in this report, I strongly recommend reading his blog post.
Just a couple of things to note about this API.
Firstly, it needs to be able to identify sentiment-applicable content in order to derive a rating. Therefore, any comments that have no applicable content (e.g. those which are tagged to a Facebook user with no additional text) are ignored. This is why the number of comments in the chart on the right doesn’t always align with the number shown in the ‘Comments’ metric.
Secondly, the API can only process a maximum of 1,000 comments in a single run. Since there are more than 1,000 comments included in this report, we’ve directed it to process the most recent comments, to ensure that the data reflects all comments made during and after the air dates of the series. Some comments in the pre-season are therefore not analysed for sentiment.
The second page shows all official posts made on the site, along with a chart that tracks Likes and Comments against these posts over time.
There are three noticeable peaks on the top left chart showing the number of Comments. The first peak, on 23rd June, coincides with the official revealing of the new House Robots. The second, on 13th July, coincides with the official announcement about the air date of the first episode. And the third peak, on 24th July, coincides with the airing of Episode 1.
The number of Likes peaks on the 27th – 28th August, which was the weekend of the Grand Final.
This report is a simple but effective demonstration of how Microsoft Power BI can be used to derive intelligence from social media data.