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 couple of API versions over the coming months, so please take a moment to read about the changes.
We've created some new resources to help you stay up-to-date....
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Introducing Keyword Relationship Models
Identifying and expanding on keywords and terms is a key challenge when filtering, classifying and analyzing text data. We're always looking at how we can make this challenge easier. One area we've been researching is finding relationships between words using word2vec.
Today we've released a tool which allows you to explore relationships between words. We've also created our first Keyword Relationship Model for you to explore. This model represents over three million unique...
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Open Data Processing for Twitter - Now Available
Following Twitter's announcement to terminate their partnership with DataSift, we've been working hard to build a solution to help our customers fill gaps left by the transition to Gnip. We've now released an open-source connector for you to install on your infrastructure (or a platform such as AWS) which will take data from the Gnip API and feed this into the DataSift platform. Hopefully this component will make your transition as pain-free as possible.
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Transitioning to GNIP: Feature Gaps vs DataSift
Twitter has terminated their partnership agreement with DataSift, meaning that as of August 13th 2015, companies will need to license Twitter data directly from GNIP.
From our analysis, 80% of our customers leverage capabilities which are absent in GNIP. The goal of this post is to highlight the main functional areas that will be impacted by transitioning to GNIP, to enable our customers to evaluate the features that may need to deprecate from their products, or identify the...
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DataSift PYLON - The value of unified data processing
Applying CSDL and VEDO to Facebook topic data
You might have seen our recent announcement which enables developers to gain insights from Facebook topic data. No doubt you're eager to learn more! In this post we'll look at how easy it is to take CSDL you've fine-tuned for filtering data from networks such as Twitter or Tumblr, and apply this in PYLON both for not only filtering but also for classifying Facebook topic data. This demonstrates the simplicity of using a unified data...
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