Skip to main content
SpringerLink
Log in

Informational humidity model: explanation of dual modes of community for social intelligence design

  • Applications in Online Communities
  • Published:
AI & SOCIETY Aims and scope Submit manuscript

Abstract

The informational humidity model (IHM) classifies a message into two modes, and describes communication and community in a novel aspect. At first, a flame message, dry information vs. wet information, is introduced. Dry information is the message content itself, whereas wet information is the attributes of the message sender. Second, the characteristics of communities are defined by two factors: the message sender’s personal specifications, and personal identification. These factors affect the humidity of the community, which corresponds to two phases of knowledge creation. In a rather wet community, members easily specify other members. This is effective for managing memberships and changing knowledge from tacit to formal. In a rather dry community, members barely identify with other members at all. This method is suitable for the formal-to-tacit phase of knowledge creation. Finally, it is discussed how social intelligence should be designed and what features are needed to support knowledge-creating communities.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Azechi S (2000) Social psychological approach to knowledge-creating community. In: Nishida T (ed) Dynamic knowledge interaction. CRC Press, pp 15–57

  • Azechi S, Matsumura K (2001) Motivation for showing opinion on public opinion channel: a case study. In: Baba N, Jain LC, Howlett RJ (eds) Knowledge-based intelligent information engineering systems and allied technologies KES2001 69. IOS Press, pp 344–347

  • Azechi S, Matsumura K (2002) Interpersonal cognition in anonymous community. In: Damiani J, Howlett RJ, Jain LC, Ichalkaranje N (eds) Knowledge-based intelligent information engineering systems and allied technologies KES2002 82. IOS Press, pp 1321–1325

  • Cacioppo JT, Petty RE (1982) The need for cognition. J Pers Soc Psychol 42:116–131

    Article  Google Scholar 

  • Cartwright DP, Zander AF (1968) Group dynamics: research and theory, 3rd edn. Harper and Rowe, New York

    Google Scholar 

  • Dumber R (1998) Grooming, gossip, and the evolution of language. Harvard University Press, Cambridge

  • Fujihara N (2001) How to evaluate social intelligence design. In: Terano T, Nishida T, Namatame TA, Tsumoto S, Ohsawa Y, Washio T (eds) New frontiers in artificial intelligence—joint JSAI 2001 workshop post-proceedings. Lecture notes in artificial intelligence LNAI2253. Springer, Berlin Heidelberg New York

  • Fukuhara T, Matsumura K, Azechi S, Fujihara N, Terada K, Yamashita K, Nishida T (2002) Creating city community consanguinity: use of public opinion channel in digital cities. In: Tanabe M, van de Besselaar P, Ishida T (eds) Digital cities II: computational and sociological approaches. Lecture notes in computer science LNCS2362. Springer, Berlin Heidelberg New York, pp 270–282

  • Fukuhara T, Fujihara N, Azechi S, Kubota H, Nishida T (2003) Public opinion channel: a network-based interactive broadcasting system for supporting a knowledge-creating community. In: Howlett RJ, Ichalkaranje NS, Jain LC, Tonfoni G (eds) Internet-based intelligent information processing systems, chapter 7. World Scientific, pp 227–268

  • Joinson AN (2001) Self-disclosure in computer-mediated communication: the role of self-awareness and visual anonymity. Eur J Soc Psychol 31:177–192

    Article  Google Scholar 

  • Kiesler S, Siegel J, McGuire T (1984) Social psychological aspects of computer-mediated communications. Am Psychol 39:1123–1134

    Article  Google Scholar 

  • Lea M, O’Shea T, Fung P, Spears R (1994) “Flaming” in computer-mediated communication: observations, explanations, implications. In: Lea M (ed) Contexts of computer-mediated communication. Harvester Wheatsheaf, London, pp 89–112

  • Newcomb TM (1953) An approach to the study of communicative acts. Psychol Rev 60:393–404

    Google Scholar 

  • Nishida T, Fujihara N, Azechi S, Sumi K, Hirata T (1999) Public opinion channel for communities in the information age. New Gen Comput 17:417–427

    Google Scholar 

  • Nonaka I, Takeuchi H (1995) The knowledge-creating company: how Japanese companies create the dynamics of innovation. Oxford University Press, New York

  • Polanyi M (1966) The tacit dimension. Routledge and Kegan Paul, London

  • Project H (1993) Codebook. http://www.it.murdoch.edu.au/~sudweeks/projecth/index.html

Download references

Author information

Authors and Affiliations

  1. School of Business Administration, Asahi University, Hozumi 1851, Mizuho City, Gifu Prefecture, 501-0296, Japan

    Shintaro Azechi

Authors
  1. Shintaro Azechi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Shintaro Azechi.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Azechi, S. Informational humidity model: explanation of dual modes of community for social intelligence design. AI & Soc 19, 110–122 (2005). https://doi.org/10.1007/s00146-004-0304-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00146-004-0304-3

Keywords

Search

Navigation