PyCon Pune 2017

A conference on the Python programming language

Lalit Chauhan

@lalitc375

Opinion Extraction From Customer Reviews

Submitted Nov 13, 2016

When a review or a social media post talks about a product or service, the user might want to discuss multiple aspects or sub-topics related to the product or service.
For example, when a customer buys a laptop from Flipkart,the customer might have good things to say about the sound quality of laptop but he/she might be disappointed with the service offered to him/her by vendor and therefore might think that the Delivery Model needs to be revamped.
So a general sentiment analyser which is normally used might turn trivial for the overall sentiment drawn towards the product/service and hence might not be able to capture the full essence of the actual product.
My talk shall be about a need as well as implementation of improved Aspect-based Sentimental Analyser/Opinion Extraction for better and more fine-grained analysis of user feedback, which would enable service providers and product manufacturers to identify the certain business aspects that needs improvement.

Outline

Data/Reviews Acquisition
Data Preprocessing
Entity Extraction
Clustering
Advanced Sentimental Analysis
Result Visualisation
Future Work
Challenges

Speaker bio

I am a senior undergraduate at central India’s largest institution NIT Raipur.I was a research intern at Xerox research centre as well as IIT Gandhinagar.I have three years experience in software development with detailed expertise in programming languages like Python,JavaScript,AngularJS,Php.I am highly interested in machine learning,data mining ,natural language processing with particular reference to NLTK and Genism.If you would like to know more about me,you can visit http://lalitc375.github.io/

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