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October 7, 2017

Building Data Science with JS – Lifting the Curtain on Game Reviews

Filed under: Data Science,Javascript,Natural Language Processing,Programming,Stanford NLP — Patrick Durusau @ 4:52 pm

Building Data Science with JS by Tim Ermilov.

Three videos thus far:

Building Data Science with JS – Part 1 – Introduction

Building Data Science with JS – Part 2 – Microservices

Building Data Science with JS – Part 3 – RabbitMQ and OpenCritic microservice

Tim starts with the observation that the percentage of users assigning a score to a game isn’t very helpful. It tells you nothing about the content of the game and/or the person rating it.

In subject identity terms, each level, mighty, strong, weak, fair, collapses information about the game and a particular reviewer into a single summary subject. OpenCritic then displays the percent of reviewers who are represented by that summary subject.

The problem with the summary subject is that one critic may have down rated the game for poor content, another for sexism and still another for bad graphics. But a user only knows for reasons unknown, a critic whose past behavior is unknown, evaluated unknown content and assigned it a rating.

A user could read all the reviews, study the history of each reviewer, along with the other movies they have evaluated, but Ermilov proposes a more efficient means to peak behind the curtain of game ratings. (part 1)

In part 2, Ermilov designs a microservice based application to extract, process and display game reviews.

If you thought the first two parts were slow, you should enjoy Part 3. 😉 Ermilov speeds through a number of resources, documents, JS libraries, not to mention his source code for the project. You are likely to hit pause during this video.

Some links you will find helpful for Part 3:

AMQP 0-9-1 library and client for Node.JS – Channel-oriented API reference

AMQP 0-9-1 library and client for Node.JS (Github)

https://github.com/BuildingXwithJS

https://github.com/BuildingXwithJS/building-data-science-with-js

Microwork – simple creation of distributed scalable microservices in node.js with RabbitMQ (simplifies use of AMQP)

node-unfluff – Automatically extract body content (and other cool stuff) from an html document

OpenCritic

RabbitMQ. (Recommends looking at the RabbitMQ tutorials.)

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