In 1982, a brilliant computer scientist built an algorithm to draw seemingly random points on a screen. He called it Perlin Noise. In 2008, another computer scientist built a totally different way to put seemingly random points to a screen. He called it Twitter.
Through just a glance at my Twitter feed, I can get a glimpse of the happenings on the Senate floor, catch breaking news from the Middle East, be updated about a disaster abroad and about an equally important mosquito situation on my friend’s arms. Here, it is clear what constitutes the noise, but it is not always so much so.
A study done in collaboration across Carnegie Mellon, MIT, University of Southampton and Georgia Institute of Technology aims to discover what makes a tweet noise, and what makes it worth reading? They asked 1,433 tweeters to rate 43,000 tweets, sorted into categories like Questions to Followers, Information Sharing, Self-Promotion, Random Thought, Opinion/Complaint, Me Now, Conversation and Presence Maintenance. Here is what they found:
Only 36% of the rated tweets were considered worth reading. The fact that the number is so low is funny, since people actively choose which accounts to follow.
Of the tweets deemed worth reading, 48% were informative and 24% were funny.
Also, the study found a pretty universal dislike for location service tweets, like automated posts from Foursquare, the use of @ mentions in the body of a tweet, and the overuse of hashtags obscuring the tweet’s content.
The researchers left a list of best practices for Twitter:
“[Posters should] embed more context in tweets (and be less cryptic); add extra commentary, especially if retweeting a common news source; don’t overuse hashtags and use direct messages (DMs) rather than @mentions if more appropriate; happy sentiments are valued and ‘whining’ is disliked, and questions should use a unique hashtag so followers can keep track of the conversation.”
Read the original study here.