Guest post by Andrea Ledesma
As someone who fancies herself a lurker on Twitter, I was a little intimidated heading into the MCN 2016. Would I be able to follow along? What exactly should I tweet? How fast would I need to type?
Luckily, someone’s made a script for that.
I tracked
#MCN2016 using TAGS v6.1. Developed by Martin Hawksey, Innovation Community & Technology Officer at the Association for Learning and Technology (@mhawksey), TAGS is a Google Sheets template that pulls data from Twitter. It runs directly through Twitter’s API.
In this instance, I set TAGS to search #MCN2016 every hour, on the hour starting November 1st. To control the archive, I only collected data from users with over 150 followers.
At the end of the conference, TAGS logged 9000+ tweets from over 1000 users. (Good work guys!)
The most compelling feature of TAGS is its TAGSExplorer. This maps tweets across a network graph with all the interactivity of d3 and JavaScript/JQuery with none of the headaches. Each edge represents an interaction. Each node represents a user. Rolling over a node reveals a feed of tweets, as well as a replay feature animating conversations as they unfolded over time. For those who like a bit of competition, TAGSExplorer also ranks users. Top tweets are based on number of tweets, conversationalists the number of interactions.
TAGS is not without its glitches. For one, it only allows users to reach as far back as 9 days from the date on which the sheet is activated. Also, the archive is a little messy, truncating tweets seemingly at random and distinguishing retweets with the classic “RT.” Most importantly, Hawksey himself recognizes that TAGS prioritizes “relevance” over “completeness.” Some researchers have found that his makes for a visualization that “over-represents the more central users and does not offer an accurate picture of peripheral activity.”
Still, armed with a predetermined window of activity and a hashtag to capture all the goings-on from the event of interest, TAGS proved the ideal tool for real-time, quick-and- dirty data analytics. As a first time MCN attendee this was invaluable. Sitting in my hotel room on the first night, I made and sifted through the first day’s network map forming a game plan the rest of the week. What were the conversations inspired by and happening around the conference? How would these develop over the course of the week? Who to follow? Who to talk to?
Now, looking at the web of nodes and edges in hindsight. There’s a material trace of #MCN2016’s major dialogue and debates, creations and critique to take us into #mcn50.