Least Squares

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Archive for April, 2011

Visual Attention and Microblog Consumption

Posted by Scott on April 13, 2011

“attention is the new pagerank”

 

I love this idea. For two reasons actually. First, it nicely captures a change in the way people consume information. We are now firmly entrenched in an “information stream” world that is at least augmenting the previously dominant modality of explicit information look-up via traditional search. What we attend to in that stream determines which pieces of information effect us. Second, it implies a primacy for human cognition over algorithm. That’s not inherently a positive (for me, anyway), but it does change the equation, so to speak, about the mediators of information on our lives.

 

To that end, we wanted to know just how much cognitive attention people give their information feeds, and how that attention relates to memory, perceived value of the content, and to attributes of the information environement itself. To study all this, we tracked the eye gaze of people while they read their Twitter feeds, and then followed up with various questionnaire items and a memory test. The full results are available in an upcoming ICWSM paper by myself and Kristie Fisher. Here is a short(er) summary. [BTW, the usual caveates are in the paper, but in particular, note that this was based on a sample of active, “professional” type Twitter users. Other groups, like teens, could show very different information consumption patterns.]

 

Heat map

 

Basic Numbers
People devote about 3 seconds to reading a tweet, and it’s hard to not give a tweet at least some attention. 15% of tweets are rated as highly interesting, and very few tweets would receive a measureable behavior such as a retweet. Memory for tweets was poor. We gave people a recall task, immediately after reading their tweets, on which they simply had to indicate which tweets they had seen only a few minutes earlier. Half they had seen, and half they hadn’t, so chance was 50%. On average, people scored below 70%.

 

Basic numbers

 

Do attention, interest, and memory align?
Ideally, the stuff you attend to is the same stuff you think is most interesting and are most likely to remember. Does this happen? Kind of, but imperfectly. Thankfully, highly rated content is an fact looked at longer and better remembered. Still, these data are relatively noisy.

 

Comparing measures

 

What properties of the information environment affect attention?
It turns out that many properties of tweets that we think of as conveying signal (e.g., a retweet is something someone thought was important enough to pass along) or expand the information quotient (e.g., including a link) actually decrease attention, interest, or memory. For instance, tweets with links we looked at almost a second less than tweets without links. Retweets were rated significantly less interesting than non-retweets. Tweets from people who tweet frequently are looked at more than a second less than tweets from people who don’t tweet frequently. Finally, tweets from personal contact are more likely to be remembered than those from organizations or celebrities.

 

 

Why does all this matter?
Significant research (in quantity and importance) addresses aspects of information contagion: viral videos, meme propagation, and so on. Returning to the importance of human cognition in the ‘attention is the new pagerank’ idea, these data provide some evidence for the role the individual consumer of (social) media plays in these processes. First, there is a considerable amount of content that people think is highly interesting that receives no measureable behavior, and thus is not captured by studies of information flow in networks. On the other hand, even content that is actually seen may not be remembered, thus reducing the effective reach of the information. Second, primary vehicles for information diffusion in Twitter -retweeting, frequency of tweeting, and link sharing- all show counterproductive results: retweets are not seen as more interesting, frequent tweeting reduces attention for any individual tweet, and including links decreases visual attention to a tweet. These suggest design directions that we discuss in the paper (e.g., better link previewing so consumers can decide more quickly and accurately if the link is worth clicking).

 

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