What we listen to on a daily basis affects more than what you think it does. I wanted to create a program which allowed people to analyze the music they are listening to and how it affects their mental health.

What it does

Music Mood Determiner grabs the lyrics of any song and runs it against happy and sad word banks. Whichever words appear more is the mood of the song.

How we built it

With the use of the api lyricsgenius, I were able to scrap any lyrics found in Genius' database. From there, I ran through the word banks and compared them

Challenges we ran into

Some issues I ran into was compiling a wide enough word bank. One way I attempted to get words for happy and sad moods would be comparing two songs of the same mood and collecting any non-noise words. This would not always be as useful some words would come up in sad and happy moods. I believe if I were able to analyze the context of each word, the results of Music Mood Determiner would be more accurate. Unfortunately, I did not have enough time to use HTML and CSS to use it on a website. Considering this is my first time using python, I am proud of what I learned overnight even if it does not work as intended.

Accomplishments that we're proud of

I am really proud of being able to do this all myself. I usually have trouble completing school projects but this was easier as I was more interested in this. Another thing I am proud about is using my first API and being able to use python on the html website.

What we learned

I learned how to read API documentation and use API's. Another thing I learned was how to implement python in HTML with flask.

What's next for Music Mood Determiner

I want to advance Music Mood Determiner to analyze context of each word to determine whether a song is happy or sad. This script was built in less than a day so there is definitely more emotions to add and better ways to build the word banks which the script relies on. But I first want to make sure that the script works as intended!

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