Twitter sentiment analysis: fan engagement in esports matches

Sentiment analysis is used to gain an understanding of the opinions, emotions, and subjectivity of text. Twitter is a social networking service where millions of users post and interact with messages. For multiplayer video game competitions, known as esports, many fans use Twitter as a platform to react to the match progress and results. In this study, we utilize the Twitter API and analyze tweets relating to Overwatch League matches using TextBlob to compute the sentiment polarity based on POS tagging. Each tweet will be assigned a score in the range of -1 to +1. We hypothesized that tweets mentioning winning teams would include more positive sentiments on average than tweets mentioning losing teams, but our preliminary analysis (with limited data) indicates that the relationship between sentiment and match outcomes may be more complicated.