natural language processing

Analysis of Diurnal and Seasonal Mood using Twitter Data

Collected over 60GB of twitter data of year 2016 Used VADER Sentiment Analysis to extract positive and negative affects from tweets Analyzed hourly diurnal mood change by day of the week Analyzed the relationship between mood change and number of friends/followers and device impact Calculated the top PMI words for morning/night