Dealing with Information Overload
KSE 652 Social Computing Systems:
Design and Analysis
Uichin Lee
Oct. 10, 2013
Cognitive Overload
• Humans can only undertake a finite amount of informationprocessing tasks during a given period of time
• Cognitive overload happens due to multi-tasking,
interruption, and information overload
• Cognitive overload linked to:
– Too much info supply? (oversupply of push/pull info)
– Too much info demand? (too complex desire of info due to
uncertainty; e.g., filing, piling, learning, etc.)
– The need to deal with multi-tasking and interruption
– The inadequate tool support to help reduce metacognition
(mental effort of controlling one's cognitive processes)
A few thoughts on cognitive overload, David Kirsh, Intellectica 2000
Interactions in Social Systems
• Types of interactions
–
–
–
–
One-way (broadcasting); e.g., TV, radio style
Two-way/non-interactive: messages flow bilaterally
Reactive: later messages refer to one’s immediately preceding them
Responsive/interactive: later messages refers a series of preceding
ones
• Chat room example w/ two users: A and B
– Two-way/non-interactive: typing with no coherence/ack
– Reactive: B types in a response to a message posted by A
– Responsive/interactive : A  B; feedback that relates both to previous
messages and to the way previous messages related to those
preceding them
Networked interactivity, S. Rafaeli and F. Sudweeks, JCMC 1997
Interaction Space (Virtual Public)
• Processing load relates to a number of factors
– Rate, message size (frequency/density)
– Threaded interactions (consistency)
– Interactional coherence (diversity/entropy, disruption)
• Beyond a threshold load, stress zone is encountered, making
unsustainable interactions
• How do people deal with information overload?
–
–
–
–
Increasing efforts (say for a short period)
Learning new information management tools (if available)
Producing simpler responses, delaying till time allows
Ending participation (disengagement)
User Population and User Contributions to Virtual Publics, Quentin Jones, Sheizaf Rafaeli. In GROUP'99
User-Population/Contribution Model
• Critical mass has to be reached for group interaction to be sustained
• An increase in user population will not result in an equal increase in
interaction volume
• Individual cognitive-processing limits produce a constraint to volume
User-Population/Contribution Model
Group
chatting
News
Group
(Communication
density of a user;
e.g., # messages per user)
Empirical Evidence of Info Overload
(IRC Chatting Dataset)
Typical IRC User Interface (MIRC)
Yahoo Chat User Interface
Empirical evidence of information overload constraining chat channel community
interactions, Quentin Jones, Mihai Moldovan, Daphne Raban, Brian Butler, CSCW 2008
Message density = # messages / # users
Message density
Empirical Evidence of Info Overload
(IRC Chatting Dataset)
Total # of users (max) in a chat room
Empirical Evidence of Info Overload
(IRC Chatting Dataset)
density = # messages / # posters
posters/users ratio:
constant
14
posters/users ratio:
keep decreasing
Dealing with Info Overload
• Dormitory example
– Clustering residents in short hallways (w/ 20 people or less) were
found to be less stressful
• Residents knew more of their neighbors
– Vs. long hallways: unwanted interaction; lack of protective group
structure
• Structural design aspects of interaction space
– Structuring social interaction to make a densely occupied space feel
more like a set of small communities
• S/W tools
–
–
–
–
–
Automatic classification (or routing)
Filtering and scanning
Summarization
Cost-based interaction intervention (e.g., to prevent junks)
Moderation tools
Structuring computer-mediated communication systems to avoid information
overload, Starr R. Hiltz, Murray Turoff, CACM Volume 28 Issue 7, 680-689, July 1985
Dealing with Info Overload
• Real problem is understanding group objectives
and providing tools that allow individuals/groups
to structure their own communications
• Any process that limits overload by structuring
content will also destroy potential benefits
• Tools for limiting overload should be based on
structuring processes and should allow
individuals to control content
Structuring computer-mediated communication systems to avoid information
overload, Starr R. Hiltz, Murray Turoff, CACM Volume 28 Issue 7, 680-689, July 1985