Alejandra first developed the idea of building a Sentiment Analyzer to help small businesses better grow their company through the positive impact of data.

What it does

Creating a sentiment analyzer used for e-commerce sites to implement data visualization and to help small business owners understand how users feel about their products.

How we built it

We built the project using the following technologies: Front-End: React and D3 Back-End: Python and Falcon Sentiment Analyzer: Microsoft Text-Analyzer API

Challenges we ran into

Some of the challenges we faced was the planning and research of our idea. As well as finding the right data that fit our project. Initially, we wanted to use an Amazon Web Scraper or API that could read through Amazon Reviews, however, this feature was no longer supported by Amazon. We then also faced some issues learning about the Microsoft Text Analyzer API and how to implement it.

Accomplishments that we're proud of

We are very proud of being able to complete a project even though we did not start as confident in this project. We have a very good project idea that we were interested in pursuing and used new topics like Natural Language Processing and Sentiment Analysis.

What we learned

We learned important concepts of NL Processing and Data Mining. As well as how to access and work with an API, D3 for building graphs and an entire full-stack application.

What's next for Senti

We hope to create a plug-in for our project that can be used by any e-commerce site. The goal is to be able to read comments from many data platforms and provide more user-friendly data visualization for small business owners.

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