Social computing — the effect of group dynamics and interpersonal interaction on adoption behaviour

A few weeks ago I suggested, by adapting Maslow’s Hierarchy of Needs, that because people have social needs, some are motivated to fulfil those needs through using social computing tools. Not everyone blogs though. Li, Bernoff, Fiorentino and Glass [1] have shown that the sorts of activities they involve themselves with vary greatly: some people blog, some people comment and contribute, while some just watch and others don’t engage at all. This variety of behaviour has got me thinking.

At a fundamental level, humans think about the social groups they belong to in terms of “us” vs “them”, or the groups that “I am in” (in-groups) and those that “I am not in” (out-groups) [2]. Dryer, Eisbach and Ark [3] suggest that, if social computing tools are associated with an out-group, the technology itself may be a powerful marker in identifying group membership. If your group doesn’t use technology, or is even anti-technology, the in-group dynamic will result in its members looking toward other channels for meeting social needs. Coupled with pervasive, negative social stereotypes, like “geek”, and the influences of the group dynamic on the adoption of social computing tools become more obvious.

The influence of the group, however, is only half the story — the drive for interpersonal communication is the other influence. Some would argue [4] that true interpersonal interactions can only result if technology is not part of the interaction because human moments require physical presence and emotional and intellectual attention. This assumes, though, that social needs require instant gratification and that only interpersonal interaction can fulfil it. Just as the people wrote letters in the 19th century, however, or receive email in the 21st century, social intercourse can be time-delayed and without overt emotional or physical cues, and still be seen to help connect people and deliver social benefits when delivered by a computer [5].

While there is no disagreement that people are social animals who have a need to be social, there is, therefore, a complex interactions between external social influences, the group-norm, personal perception of their interactions (at either a conscious or unconscious level) that influence a person’s choice of behaviour for fulfiling their social needs.

These influences include:

Personal perception

• Accessibility: Do people believe that the tool is easy to use and do they understand easily how it works?
• Familiarity: Is the tool familiar and appropriate for the context of its use?
• Sharing: Does the tool help people to give advice and take information away easily and naturally?
• Relevance: Do people who both use it and don’t use it think its useful?

In-group norms

• Appeal: Is being seen to use the tool, or advertising the fact, attractive to those who use it or don’t use it?
• Disruption: Does the tool disrupt individuals’ natural social behaviors, such as referring to shared information while interacting?
• Perceiver distraction: Does using the device create noise or otherwise create a distraction for nonusers?

Esteem needs

• Power: To what extent does use put one person more “in charge” than another person? To what extent does participation communicate a difference in status?

Belonging needs

• Identification: Does the tool appear to include or exclude individuals from certain communities? Do nonusers see themselves as persons who would use the device?
• Communication: Does it make communication among persons easy, especially the sharing of important social information such as appointments and contact information?
• Social application: Does the device support rich social interactions, such as through interest matching, meeting facilitation, or social networking?

The resultant picture, according to the taxonomy of social computing, suggests that roughly 50% of people choose a virtual channel for fulfilling their social needs. If the experience is positive, and the burst of social computing over the last 12 months or so suggests it has been, this will influence how both individuals perceive social computing and how society perceives it, and these numbers will grow.

For people like Lauren, who don’t yet get social computing, the suggestion of this model is that, eventually, they will.

M
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[1] Li, C., Bernoff, J., Fiorentino, R. and Glass, S. (2007) Mapping Participation In Activities Forms The Foundation Of A Social Strategy. Social Technographics. Online at: http://www.forrester.com/…7211,42057,00.html, accessed on 6 July 2007.

[2] Sherif, M. (1956) Experiments inGroup Conflict, Scientific American 195, No. 5.

[3] D. C. Dryer, D.C., Eisbach, C. & Ark, W. S. (1999) At what cost pervasive? A social computing view of mobile computing systems. IBM Systems Journal, vol 38, no. 4. Online at: http://www.research.ibm.com…dryer.pdf, accessed on 6 July 2007.

[4] Hallowell, E. M. (1999) The Human Moment at Work, Harvard Business Review, 58–66, January–February.

[5] D. C. Dryer, D.C., Eisbach, C. & Ark, W. S. (1999) At what cost pervasive? A social computing view of mobile computing systems. IBM Systems Journal, vol 38, no. 4., p660 Online at: http://www.research.ibm.com…dryer.pdf, accessed on 6 July 2007.

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