Picking the Brains of Strangers Helps Make Sense of Online Information
Science Daily carried this summary (the official abstract and link are below):
People who have already sifted through online information to make sense of a subject can help strangers facing similar tasks without ever directly communicating with them, researchers at Carnegie Mellon University and Microsoft Research have demonstrated.
This process of distributed sensemaking, they say, could save time and result in a better understanding of the information needed for whatever goal users might have, whether it is planning a vacation, gathering information about a serious disease or trying to decide what product to buy.
The researchers explored the use of digital knowledge maps — a means of representing the thought processes used to make sense of information gathered from the Web. When participants in the study used a knowledge map that had been created and improved upon by several previous users, they reported that the quality of their own work was better than when they started from scratch or used a newly created knowledge map.
“Collectively, people spend more than 70 billion hours a year trying to make sense of information they have gathered online,” said Aniket Kittur, assistant professor in Carnegie Mellon’s Human-Computer Interaction Institute. “Yet in most cases, when someone finishes a project, that work is essentially lost, benefitting no one else and perhaps even being forgotten by that person. If we could somehow share those efforts, however, all of us might learn faster.”
Three take away points:
- “people spend more than 70 billion hours a year trying to make sense of information they have gathered online”
- “when someone finishes a project, that work is essentially lost, benefitting no one else and perhaps even being forgotten by that person”
- using knowledge maps created and improved upon by others — improved the quality of their own work
At the current minimum wage in the US of $7.25, that’s roughly $507,500,000,000. Some of us make more than minimum wage so that figure should be adjusted upwards.
The key to success was improvement upon efforts already improved upon by others.
Based on a small sample set (21 people) so there is an entire research field waiting to explore. Whether this holds true with different types of data, what group dynamics make it work best, individual characteristics that influence outcomes, interfaces (that help or hinder), processing models, software, hardware, integrating the results from different interfaces, etc.
Distributed sensemaking: improving sensemaking by leveraging the efforts of previous users
by Kristie Fisher, Scott Counts, and Aniket Kittur.
We examine the possibility of distributed sensemaking: improving a user’s sensemaking by leveraging previous users’ work without those users directly collaborating or even knowing one another. We asked users to engage in sensemaking by organizing and annotating web search results into “knowledge maps,” either with or without previous users’ maps to work from. We also recorded gaze patterns as users examined others’ knowledge maps. Our findings show the conditions under which distributed sensemaking can improve sensemaking quality; that a user’s sensemaking process is readily apparent to a subsequent user via a knowledge map; and that the organization of content was more useful to subsequent users than the content itself, especially when those users had differing goals. We discuss the role distributed sensemaking can play in schema induction by helping users make a mental model of an information space and make recommendations for new tool and system development.