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Sentinental-analysis-with-ecommerce-data

Proposed archeitecture

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Need of sentimental analysis

Amazon review sentimental analysis is the process of using machine learning to classify Amazon product reviews as positive, negative, or neutral. This can be done using a variety of techniques, including:

Lexicon-based: This approach uses a dictionary of words and phrases that have been associated with positive or negative sentiment. The sentiment score of a review is calculated by counting the number of positive and negative words and phrases it contains. Machine learning: This approach uses a trained machine learning model to predict the sentiment of a review. The model is trained on a dataset of labeled reviews, where each review has been assigned a sentiment score (positive, negative, or neutral). Amazon review sentimental analysis can be used for a variety of purposes, including:

Product development: Companies can use Amazon review sentimental analysis to identify areas where their products can be improved. For example, if a company sees that many customers are complaining about a particular feature of their product, they can address this issue in future versions. Customer service: Companies can use Amazon review sentimental analysis to identify customers who are unhappy with their products or services. They can then reach out to these customers and try to resolve their issues. Marketing: Companies can use Amazon review sentimental analysis to identify the most popular and well-regarded products in their category. They can then use this information to develop more effective marketing campaigns. There are a number of different tools and services available for Amazon review sentimental analysis. Some of these tools are free, while others require a subscription fee. The choice of tool will depend on the specific needs of the user.

Here are some examples of how Amazon review sentimental analysis can be used:

A company that sells smartphones might use Amazon review sentimental analysis to identify the features that customers are most satisfied and dissatisfied with. This information could then be used to develop new smartphones that better meet the needs of customers. A company that sells clothing might use Amazon review sentimental analysis to identify the styles and sizes that are most popular and in demand. This information could then be used to make sure that the company has enough of these products in stock. A company that sells software might use Amazon review sentimental analysis to identify the features that customers find most useful and the bugs that are causing them the most problems. This information could then be used to improve the software.

Overall, Amazon review sentimental analysis is a powerful tool that can be used to improve products, services, and marketing campaigns.

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