Sentiment Analysis Using Bidirectional Stacked LSTM
This article was published as a part of the Data Science Blogathon
Sentiment Analysis
Sentiment Analysis is the process of finding the sentiments of the text data. Sentiment Analysis falls under the text classification in Natural Language Processing. Sentiment Analysis would help us to know our customer reviews better. A sentiment denotes any one of the following, Positive, Negative, and Neutral. When we analyze the negative reviews of our products we can easily use those reviews to surmount the problems we face and provide a better product.
Benefits of using sentiment analysis include,
- Understand customer better
- Improvise the product features based on customer reviews
- We will be able to identify the mistakes in the features and resolve them to satisfy the customer.
Sentiment analysis can be done in two different ways,
- Rule-based sentiment analysis
- Automated sentiment analysis
In rule-based sentiment analysis, we define a set of rules, if the data satisfies those rules then we can classify them accordingly. For example, if the text