MUSIC FESTIVAL STUDY
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METHODOLOGY
For this analysis, our goal was to holistically understand music festivals through the lens of social media. We
approached this analysis with a multifaceted approach, one that relied on social listening, influencer analysis,
and an in-depth demographic and psychographic analysis of the people discussing music festivals.
PART 1: MUSIC FESTIVAL CONVERSATION ANALYSIS; PRE/DURING/POST EVENT CONVERSATION ANALYSIS
We started by analyzing the total social media conversation surrounding music festival season at large. We
accomplished this by constructing a complex Boolean framework that captured 181 major music festivals,
their branded and popular unbranded hashtags, as well as their Twitter handles when applicable. In addition
to this, we developed a complex Boolean framework designed to capture the entirety of unbranded music
festival conversation. We combined these two frameworks into a comprehensive Boolean aggregate, designed
to holistically capture all conversation surrounding music festivals at large. We used this aggregate framework
to study conversation from 8/6/13 through 8/5/14, capturing a full year’s worth of social media conversation
surrounding music festivals across Twitter, public Facebook, blogs, and forums.
Once the conversational results were returned from our aggregate Boolean framework, we analyzed the spikes
in conversation over time, identified the largest ones, and called out the festivals that drove these swells in
conversation. We then performed this same process again, to study where the conversation was geographically
coming from.
We took these results and sorted conversation that occurred before, during, and after a festival into three
separate thematic “buckets.” Our goal was to understand where in time conversation took place (at scale) in
relation to the events. Once we had organized a sample of conversation, we used our technology to replicate
our organizational judgement across the entirety of music festival conversation. We then analyzed the returned
results for accuracy, as well as actionable trends and insights.
We then replicated the process previously mentioned to discover what makes a music festival "loveworthy."
Again, we organized conversation into different thematic “buckets,” only this time we grouped them by different
drivers of positive sentiment. Our technology replicated our organization across music festival conversation at
large, and returned to us the breakdown of the most scalable drivers of music festival conversation.