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Social Computing

Human-Centered Computing

Social computing is an area of computer science concerned with the intersection of social behavior and computational systems, built around creating or fostering social conventions and social contexts through software and technology. Blogs, email, instant messaging, social network services, wikis and social bookmarking are all instances of what is often called social software and illustrate ideas from social computing, a field whose growth is attributed to the spread of personal devices and increased overall computing power letting more users share content and interact with one another. This description is adapted from Wikipedia contributors under CC BY-SA 4.0; changes were made. https://creativecommons.org/licenses/by-sa/4.0/

Facts
Origin Year
1994 1
Core Concern
Intersection of social behavior and computational systems, fostering social conventions through software 1
Connections

Associated With

Field-to-field association; both are standard neighbouring areas of computing

Social computing's own theoretical-foundations section frames it around the interaction between humans and computers.

Source Social Computing (Wikipedia)
Source Social Computing (Wikipedia)
Web Science, Fields
Sources
1. Social Computing (Wikipedia)
Wikimedia Foundation
  • Lead section, para 1
    Social computing is an area of computer science that is concerned with the intersection of social behavior and computational systems.
  • History section, Term appearance
    In 1994, the concept of social computing was first proposed by Schuler.
  • Associated With: Human Computer Interaction, Theoretical foundations section
    These systems result in new behaviors that occur as a result of the complex interaction between humans and computers and can be explained by several different areas of science.
  • Associated With: Recommender Systems, Paragraph on the TikTok content recommendation example
    One recent example of social computing is how platforms like TikTok use community engagement and user feedback to influence content recommendation algorithms, effectively blending algorithmic curation with social behavior.
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