Note: This is Part V of our study of NHL Fan Quality. This week we will be ranking NHL teams/fans on the following dimensions: Fan Equity, Social Media Equity, Fan Equity Growth, Price Elasticity, Win Elasticity, and Social Media based Personality. For more details on our measures of quality, please click here. For Part I, click here. For Part II click here. For Part III click here. For Part IV click here.
Social media is increasingly being used as a market research tool, and we believe that it provides opportunities to develop some richer descriptions of NHL fan bases. The foundation for today’s analysis is something known as social media sentiment. The idea behind sentiment is that we look at the “tone” of tweets surrounding each team. In this study, we are examining the distribution of positive versus negative tweets for each team over the past three years.
Our actual approach uses a variety of statistics used to characterize distributions (e.g. mean, variance, skewness, kurtosis, etc.…), and then we employ a technique known as cluster analysis. We will avoid the details (feel free to contact us) but the general idea is to find teams that have similar distributions of social media sentiment. We use cluster analysis on team social media sentiment on Twitter over the past three seasons to dynamically segment fan bases (we allow fan bases to move across clusters over time). Perhaps, it is more accurate to describe what we are doing as segmenting the types of relationships fans have with their teams. Do fans have unconditional love for their team? Do they have violent mood swings?*
Based on our dynamic cluster analysis of Twitter sentiment, we are able to describe each NHL fan base. The chart below summarizes the social media “personality” of most NHL fan bases over the past three seasons.
*One caveat to this study is that since this is all based on Twitter data, the results reflect the opinions of fans on SOCIAL MEDIA only. Also, please note that unlike our previous study of NHL social media equity that was based on the size of each team’s following, this analysis is based on sentiment or tone.
Mike Lewis & Manish Tripathi, Emory University 2014.