Sentiment Analysis: A Way To Improve Your Business

The contents of this blog post are as follows:

  1. Using Regex
  2. Using nltk
  1. APIs to web scraping
  2. Bags of Words
  3. TFIDF

What is Sentiment Analysis?

Why is a sentimental analysis of Giant E-commerce websites important?

Generalize approach for Sentiment analysis?

  1. The training process: In this process (a), the model learns to associate a particular text form to the corresponding output which can be recognized as a tag in the image. Tag is based on the test samples used for training. The feature extractor simply transfers the input of the text into a feature vector. Pairs of tags and feature extractor (e.g. positive, neutral, or negative) are fed into the machine learning algorithm to generate a model.
  2. The prediction process: The feature extractor used to transfer unseen text inputs into feature vectors. Then the feature vector fed into the model which simply generates predicted tags (positive, negative, or neutral).

Steps for sentiment analysis using the predefined library

Data collection via web scraping

Data Preprocessing (Cleaning)

Using Regex

Using nltk

Predicting the scores using predefined library SentimentIntensityAnalyzer

Code Snippet for General Approach

Discussion on custom sentimental analysis approach

Conclusion

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Paradise Techsoft grows into the potential of latest AI trends, Web design & development and Digital Marketing Techniques. Stay up to date http://bit.ly/2lZdMb2

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