Analyzing of Product Reviews using Sentimental analysis

Project Code :TCMAPY406

Objective

The main of the project is to analyze the product reviews using sentimental analyses through Natural language processing.

Abstract

Social network, e-commerce sites, blogs are new emerging platforms for people to express their opinion. These sites contain huge amount of text which can be used for different purpose like Sentiment Analysis. Sentiment Analysis is a growing field in natural language processing. Sentiment analysis is major focused on company’s improvement. But sentiment analysis can be useful in recommendation system also. The NLP algorithm is used for sentiment analysis of reviews.  In proposed system, NLP algorithm shows outstanding performance. To create sentiment analysis a using the analysis of emotions, there is a need to use polarity obtained through the reviews and finally we shown the graph based on reviews and comparing two products reviews using natural language processing.

Keywords: NLP, sentiment analysis, e-commerce, product reviews.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

SOFTWARE SPECIFICATIONS:

  • Technology: Machine Learning, Application.
  • Libraries: Pandas, Numpy, Sklearn.
  • Version: Python 3.6+
  • Server-side scripts: HTML, CSS, JS
  • Frame works: Flask
  • IDE: Pycharm

HARDWARE SPECIFICATIONS:

  • RAM: 8GB, 64-bit os.
  • Processor: I3/Intel processor
  • Hard Disk Capacity: 128 GB +

Learning Outcomes

  • Machine learning algorithms.
  • Scope of Machine learning algorithms.
  • Benefits of machine learning over predictive analytics.
  • Importance of PyCharm IDE.
  • How ensemble models works.
  • Process of debugging a code.
  • The problem with imbalanced dataset.
  • Input and Output modules
  • How test the project based on user inputs and observe the output
  • Practical exposure to
    • Hardware and software tools.
    • Solution providing for real time problems
    • Working with team/ individual
    • Work on Creative ideas

 

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