Sentiment Analysis using TextBlob

Past summer I worked on a research project in Natural Language Procesing. To get my feet more into NLP, I decided to work on a Sentiment Analysis Project. My initial idea was to leverage twitter api and monitor tweets for a specific keyword. Then I can plot the subjectivity and polarity of the tweets in real time. I actually came to this end goal by discussing about Sentiment Analysis with Dr. Kennington. As I got to development, my idea mutated to include flask and create a web application. So now, the main parts of my project are : Flask, TextBlob, Web Dev

The file serverFunctions.py includes several functions which perform sentiment analysis using the textblob library. Using the textblob library was really easy. But I feel just using the library doesn’t give me knowledge of sentiment analysis, so I am currently reading papers on it and understanding how the textblob library functions. My app.py file is the where flask lives. I am not an expert in servers or web interaction, so I took time to read up on flask and how it routes to webpages. This project gave me the opportunity to dive further into web development. I focused on html, javascript and css for a week.

The product of dedicating my time to web development was that I was able to create web pages with forms, divs, articles. By this time, I decided to analyse user input too. I used forms to take in user input like this:

<form method="POST">
        <input name="text" size="30" style="color:black">
        <button type="submit"
                value="Submit"
                style="color:black">
            <b>Analyse</b>
        </button>
        <button type="submit" 
                value="Submit" 
                style="color:black" 
                formaction="/subject.html">
            <b>Graph</b>
        </button>
</form>