[Whitepaper] Using AI-Processed News Datasets to Perform Predictive Analytics

_Bitvore White Paper Amazon H2Q Blog and Social 2 (1)

Making sense of massive amounts of unstructured data from news and other sources is complicated, but AI can be leveraged to process large datasets to make intelligent predictions. 

In this whitepaper, Greg Bolcer, Bitvore CDO, describes a predictive experiment set up through backtesting around Amazon’s HQ2 Selection competition for its second North America Headquarters:

  • To determine if, at each stage of the competition, it could be predicted which cities would advance to the next round.

  • To determine if the final location(s) of Amazon’s HQ2 could be predicted, before it became public information.

The resulting white paper, highlighting the predictive value of Bitvore’s AI-processed news datasets, includes the following:

  • Predictive Experiment Description

  • Experimental Design

  • Calibration & Prediction Methods

  • Scoring

  • Final Results

  • Predictive Model Validation

Download the white paper for a closer look at using AI processed news datasets to perform predictive analytics and to see if Bitvore Precision Intelligence data predicted Amazon’s HQ2 choices correctly.





Read more from our Chief Data Officer, Greg Bolcer.

Greg Bolcer, CDO Bitvore

Greg Bolcer, CDO Bitvore

Greg is a serial entrepreneur who has founded three angel and VC-funded companies. He's been involved at an early stage or as an advisor to at least half a dozen more. Greg has a PhD and BS in Information and Computer Sciences from UC Irvine and a MS from USC.

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