Case Study: Twitter Usage at Wordcamp SF

usage chart

One of my many hats is as an events organizer. Twitter has become an invaluable tool for me to gauge the mood of the attendees. Are they excited by the current speaker? Bored or excited at the latest news? Are they having a good time? And most important, are they making connections?

Pathable, an events social networking company, has posted an analysis on the use of Twitter at WordCamp SF. The above chart shows how 797 tweets were categorized by a Pathable intern. Disclosure: I am friends with the co-founders of Pathable and a proud advisor of the company.

Or as Pathable more broadly classifies them:

  • Tweets that are not directly relevant to the vast majority of event attendees (”Here’s what I’m doing / feeling”, “talking directly to someone else”) make up about 1/3 of the tweets sent.
  • Tweets that are useful to people who can’t physically be at the event (”Comments / Quotes about speakers”, “Announcements / Info / Questions related to event”) make up more than 1/3 of the tweets
  • Tweets that report people’s intended or actual location make up around 1/6 of the tweets (”Traveling to”, “At the event / session”)

And who do you think send those tweets?

While 258 total people sent at least one tweet, 20 people account for more than half of those. That’s consistent at a high-level with the “long-tail” notion of user-generated content (i.e., a large number of people contribute small amounts of content, but that content in aggregate accounts for a large proportion of the total content). The numbers, however, don’t fit cleanly in the 80/20 90/10 buckets that are often cited. Instead, it’s more like 50/50 (50% of the content is accounted for by a small number of high activity contributors, 50% by everybody else).

twitter events

What I find really interesting is the flow of Tweets before, during and after the event (shown above; colors do not correspond to the pie chart). I like seeing that slow build up to the event and the huge spike during.The large red band are tweets classified as “Here’s what I’m doing”, the blue band at the bottom are tweets directly related to the event, and the pea green are conversations. It seems like you’re lucky if there’s much discussion after the event.

This is great after the fact analysis and it got me thinking about what I would want in realtime. In addition to a hashtag search of the realtime tweets, I want a dashboard that shows me the state of the community. The community in this case is self-selected; it’s the people using event tags or interacting with the event Twitter identity. I’d want the following metrics

  • Community Pulse – What’s the mood of the attendees? Negative or positive? What’s the tag cloud look like?
  • Community Connectedness – How many retweets are there? How many people are following each other? Is that number growing over the course of the event?
  • Engagement – What percentage of tweets being sent out by the community are using the tag?
  • Growth – Are more people using the tag? How many new users are we gaining/losing per hour?
  • Influencers – Who are the most connected tweeters in the group?
  • Locations – Where do people claim they are? Or more likely, are from?