Blog

Nested Analysis Queries in PYLON

In this blog I'm going to introduce nested analysis queries in PYLON. These are queries that allow you to delve more than one level deep. The example I'll use will analyze authors by gender and then divide them further into age demographic ranges. PYLON is DataSift's privacy first technology that…

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Investigating Audience Snacking Habits with Facebook Topic Data

You might have seen our recent blog post where we highlighted some surprising findings about snacking habits based on research using Facebook topic data. In this post we'll take a look at how the research was carried using our platform. Testing long-held assumptions We're all increasingly looking…

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Important Announcement on API Versioning

As the DataSift platform continues to develop so does inevitably our API. As we have a full roadmap of new products and features coming up this feels like a good time to clarify how we version our API and how you can best keep up with the changes. You'll see below that we're planning to deprecate a…

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Validating Interaction Filters with Facebook Super Public Text Samples

DataSift PYLON for Facebook Topic Data allows you to analyze audiences on Facebook whilst protecting users' privacy. To help you build more accurate analysis we're introducing 'Super Public' text samples for Facebook. You can use Super Public text samples to validate your interaction filters to…

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Building Better Machine Learned Classifiers Faster with Active Learning

You might have seen our recent announcement covering many things including the announcement of VEDO Intent. You're probably aware that DataSift VEDO allows you to run machine-learned classifiers. Unfortunately creating a high-quality classifier relies on a good quantity and quality of manually…

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