If you’d like to see how PYLON can help you get insights from Facebook topic data, then check out the video below. In the video you will get a taste of the different methods for building filters, how to record data to an index and how to extract insights from Facebook topic data.
You’ll see how to build filters to isolate the data you are interested in from the real-time feed of anonymized posts, comments and likes inside Facebook. For example, you could create a filter containing terms that are relevant to a brand and its competitors in order to understand an industry; or you could look for different web domains, to see what content is being shared. This can be done very easily using our query builder, but the more technically minded will probably want to use our CSDL language, which will enable them to make the most of our VEDO rules engine. VEDO allows you to use your IP (such as segmentation taxonomies or scoring systems) on Facebook data.
In order to start retrieving insights from the data you need to store the posts in an index. This index contains all the posts and engagements that are relevant to your filter. The index allows you to have low latency access to query all of the posts and engagements that have been collected and turn that into analysis results.
PYLON includes a data exploration tool that you can use to look at time series analysis and frequency distribution charts, but to get the most out of Facebook topic data you should use the analysis query API. This analysis stage is where the aggregation takes place; the outputs you receive from PYLON are aggregated and anonymized statistics. Being able to present and segment the data by sixty different criteria – including topics, demographics and sentiment – gives you a deep understanding of your results.
Interested in learning more about what kind of insights you can gain from Facebook topic data? Join us for our upcoming Facebook topic data webinar.