Twitter Sentiment Analysis to Estimate Happiness Level
Name
Nikolai Rol
Abstract
Happiness is something that people strive for. However, it has always been hard to measure and understand what happiness depends on. This paper investigates if sentiment analysis can be used to estimate how happy people are and if sentiment correlates with socioeconomic factors or with the news. For analysis, text processing techniques were applied to Twitter posts gathered over the period from November 2019 to May 2020. The study shows a weak correlation with socio-economic factors, whereas the strongest relationship was with Health Care Quality. After a closer look into the change in daily sentiment, it was found that certain topics were discussed more than others on the dates with peaks. To investigate this aspect, the correlation analysis between sentiments of Twitter posts and news was made, however, the coefficient appeared to be low. The conclusion is that the result of sentiment analysis over Twitter data does not show a high correlation with socioeconomic factors, but it might have a certain dependency on events, news, or global shocks.
Graduation Thesis language
English
Graduation Thesis type
Master - Innovation and Technology Management
Supervisor(s)
Rajesh Sharma
Defence year
2020