Inspiration
Desperation.
What it does
Aggregation of data from news and social media to perform sentiment analysis on given phrases and brand identities.
How I built it
Parsed Twitter and News APIs to aggregate the data. The data was then run through machine learning algorithms, and sentiment analysis was applied. An overall score is determined post processing and is interpreted by the user given a scale of -1 to 1 (-1 equating to a negative sentiment and 1 being a positive sentiment).
Challenges I ran into
Parsing API response data. Cleaning the response data. UI glitches (responsiveness).
Accomplishments that I'm proud of
Finished. Done in 12 hours. Peter - First hackathon.
What I learned
NLP, machine learning. Peter - Refined front end development skills. Learned how to make front end dynamic. Satchel - intricacies of Vue.js, Fundamentals of senitment analysis, REST API in Flask. Nina - Graphics in fast pace high pressure environments. Aditya - Learned fundamentals of Vue.js.
What's next for Octopus
See slide 8.
Number of github commits: 16
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