Introducing Tags - Categorise Data To Fit Your Model

The launch of DataSift VEDO introduced new features to allow you add structure to social data. These new features allow you to add custom metadata to social interactions, saving you post-processing work in your application. In this post I’ll introduce you to tagging, and explain why this will make working with social data a whole load easier. Tagging allows you to categorise data to match your business model. Keep watching this space as over the next few posts I’ll cover all...

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Announcing DataSift VEDO - Giving Structure To Social Data

Today we announced the arrival of DataSift VEDO. In this post I’ll outline what this means to you as a developer or analyst. DataSift VEDO gives you a robust solution to add structure to social data, solving one of the common challenges when working with unstructured ‘big data’. VEDO lets you define rules to classify data so that it fits your business model. The data delivered to your application needs less post-processing and is much easier to work with. The new features...

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Deprecating Historics "volume_info" Output Field

On December 2nd, 2013, we plan to remove the "volume_info" field from the DataSift Historics API call response. Please ensure that your application does not expect to receive this field from Historics API calls by this date. If you are using one of the official DataSift API client libraries, support for this has already been implemented in the following versions of the libraries: Java - 2.2.1+ Python - 0.5.4+ Ruby - 2.0.3+ PHP - 2.1.4+ .NET - 0.5.0+

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New delivered_at meta field for Push

DataSift is adding a new metadata field to each JSON object delivered via Push in the json_meta output format - a delivered_at timestamp. This new timestamp represents the time DataSift delivered this particular object. An example of a json_meta formatted Push delivery containing this new field can be seen below:   {"count":3, "hash":"4ede6111534c5e29145f", "hash_type":"historic", "id":"58802d124916ed826a08d58d791f85c5...

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Using Managed Sources

I've noticed some questions from clients who are using Managed Sources for the first time. In this blog I'm going to go through the steps to run a DataSift filter on a Managed Source: Create a token Create a Managed Source Create a CSDL filter for that Managed Source Start recording the output of the filter Start the Managed Source I'll use Facebook in my examples, but the process is similar for all the Managed Sources the platform offers. Suppose that...

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