Case Studies: Marketing & Advertising

Marketing
& Advertising

The Challenge:

To predict the type of engagement (like, reply, retweet or retweet with comment) that a user will opt for in relation to a given tweet.

The Solution:

Using the text from tweets and anonymized account information, we created a deep learning model that could predict how users would interact or engage with tweets they see on Twitter.

The Outcome:

We built a system that could automatically predict the type and probability of engagement for a particular tweet by a specific user. We achieved a very similar PRAUC-RCE to the state of the art model. 

Tech Tools & Skills Applied:

The skills and tech stack that we used included: Apache Spark, Hadoop, TensorFlow, AWS EMR, AWS EC2 and AWS S3.

Results


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