Saturday was the third and last day of ScienceOnline 2013. ScienceOnline is a non-profit organization that facilitates conversations, community and collaborations at the intersection of Science and the Web. They do this through online networks, projects and face-to-face events (both global and grassroots).
First, some statistics
The tweets were collected between 12:00am and 11:59pm on Saturday, February 2nd. In total, there were 6,719 tweets (14% more than day one and 5% more than day two) consisting of 120,655 words from 1,261 people. Just like #scio13 day one and #scio13 day two, the top tweeter was Janet Stemwedel (Twitter: @docfreeride) with 214 tweets! Here are the top 10 Twitter users and their number of tweets:
|Rank||Twitter user||Number of tweets|
Most conference attendees using Twitter actually tweeted very little: 1,076 people (85%) tweeted less than 10 times, one hundred fifteen people tweeted 10-20 times, 54 people tweeted 21-49 times, and 16 people tweeted over 50 times.
Let’s focus on retweets. Retweets are a way of saying “yeah, I like that” or “I agree!” and for the purposes of this analysis come in two forms: they can be a simple rebroadcast (e.g. RT: “original tweet”), which we’ll call a RT without conversation, or a retweet with comments back to the original tweeter (e.g. Agreed! RT: “original tweet”), which we’ll call a RT with conversation. Thirty nine percent (39%) of #SCIO13 day 3 tweets were retweets. Of those, 11% (300 of 2652) were a RTs with conversation. The top five retweeters were Bora Zivkovic (Twitter: @boraz) with 63 retweets, Janet Stemwedel (Twitter: @docfreeride) with 50 retweets, Chris Pires (Twitter: @jchrispires) with 42 retweets, Matthew Francis (Twitter: @drmrfrancis) with 38 retweets, and Adrienne Roehrich (Twitter: @fiainros) with 37 retweets.
#SCIO13 Day 3 tag cloud of tweets
From 120,655 words extracted from the #scio13 day 3 tweets, 9,193 were unique. I calculated the frequency of all 9,193 words and then “cleaned” the data, removing all words less than 4 characters, numbers, and words that were either common words (such as “that”, “from”, “with” or “have”) or gibberish (consisting principally of url strings from shared links).
Walter Jessen is a digital strategist, writer, web developer and data scientist. You can typically find him behind the screen something with an internet connection.