Machine learning & NLP at Goibibo: Keytopic extraction and contextual sentiment analysis of 20 million reviews, and a customer assistance bot

Dhruv Pathak (~dhruv58)




  • We, at Goibibo, extensively use Python as part of our app as well as data processing stack.
  • We receive a good volume of user generated content, and use natural language processing and machine learning to derive insights and data from them for our products.
  • The talk would cover how we build our user review analyzer system which extracts keytopics/keywords from 20 million user reviews and user sentiments about that keytopic. For example : How we detect that "the rooms were very spacious" is a positive experience for a consumer, or that a particular hotel has an amazing candle light dinner.

  • The talk would cover language processing in Python using inbuilt/installed python modules, and dedicated NLP libraries like NLTK and spaCy, and sentiment analysis/categorization done by Scikit-learn.

This feature can be viewed and experienced on Goibibo mobile apps ( Android/ iOS) and visiting a hotel's product page.

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  • Intermediate level knowledge of Python is beneficial, however the concepts are language agnostic .
  • Knowledge of NLTK , spaCy and scikit-learn is a plus.

Content URLs:

Talk presentation link :

Speaker Info:

I am Dhruv Pathak, a python enthusiast. I currently work at Goibibo as VP of Engineering, where we ship many evolving and high scale products using Python.

Speaker Links:


Section: Others
Type: Talks
Target Audience: Intermediate
Last Updated:


Please upload the talk presentation for review by the Pycon India team.


Gourav Chawla (~Gouravchawla)

Added in the proposal. Also pasting here for reference :

Dhruv Pathak (~dhruv58)

hello, can you please tell me all algorithms details which you used in this ... i am confused what to use for particular step of process.

Hiren Patel (~hiren)

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