Real time Sentiment Analysis with Apache Storm and Python

Shaik Asifullah (~shaik2)




Data is everywhere. How much data can we process in real time? How twitter is managing this huge data? This talk will help in understanding Big Data better. Twitter uses Apache Storm. Take a dive into Apache storm and learn more about Twitter Sentiment Analysis in Real Time.

This will help you get started with Apache Storm with one use case of Sentiment Analysis. This talk will be very basic and intends to motivate the attendees towards Apache Storm and help them to understand Apache Storm better.

Apache Storm can process tens of thousands of messages in a second, and if properly configured it can process millions in a second. But we shall be using some dump of twitter tweets and use it for sentiment Analysis with simple Heuristics. And if time permits we will use tweepy library to get real time streaming from twitter.

I shall be using Petrel (a Python Library) to submit the Storm topologies that we together build in our talk session. If time permits, setting up of Apache Storm shall be demoed and run the sample Topology.


Basic Python Knowledge

Basic Awareness of NLP is a plus though not required

Content URLs:

Speaker Info:

Preetam Purbia:

Software Engineer at @WalmartLabs. With 6+ years experience and Currently working on BigData tech stack like Kafka, Spark, Storm. Also worked on retail fulfillment product with capabilities like order life cycle management, picking path optimization. Filed 3 Patents related to E-commerce Domain.

Shaik Asifullah:

Software Engineer at @WalmartLabs. Python Enthusiast with great interest in Big Data. Interned at Calfor Finance and worked under Dr. Sulkhan, CEO Calfor Finance, Teaching Assistant at University of Zurich. Also interned at GreyOrange Robotics. Worked extensively on Sentiment Analysis with Apache Storm. Loves Cycling, Meta Physics. Also working on a paper related to Psychology and Twitter Sentiment.

Speaker Links:

Preetam Purbia:

Shaik Asifullah:

Section: Data Visualization and Analytics
Type: Talks
Target Audience: Intermediate
Last Updated: