In this section we contrast and compare online communities with offline communities. We consider the research on online communities to derive practical advice on how to join and contribute constructively to these digital communities. If you don’t have much experience with online communities, participate in the OERu course forums and become an active member of the OERu learning family.
Online versus real communities
Contrast and compare the similarities and differences between online and real communities. For example:
|Online and real communities both congregate around shared interests||In the absence of body language, it is hard to decipher emotional intent with written communications in online discussion forums.|
Share a similarity or difference you identified by posting a comment on WENotes, for example:
- Online communities are different because …
- Real communities are different because …
- Online and real communities are similar because …
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In the early years of the internet, there was a strong research interest in studying the differences between virtual and real communities. However, in more recent years, we have observed a blurring of the boundaries between online and real communities. Read the following article:
- Michalk, A. (2013, June 27). The difference between online & real life community? Retrieved July 6, 2017.
Research on online communities
Research on the efficacy of online communities provides insights on selecting productive communities and how to engage. Community contributors can be classified into three types (Mocus et al 2002):
- Core members are responsible for guiding the development of the community and have usually been involved with the community for a long time. These members have made significant contributions to the community’s evolution and have earned leadership status. Frequently they also play an active role in moderation of the group.
- Active members make regular contributions to the community.
- Peripheral members occasionally contribute to the discussions and the periods of engagement are short and sporadic. “Lurkers”, that is individuals seeking answers without making contributions, are normally associated with this group.
The nature of engagement in a community is influenced by the community’s life cycle stage (A. Iriberri and G. Leroy 2009):
|Life cycle stage||Characteristics|
|Inception stage||Focus is on determining the purpose, codes of conduct, funding and sustainability.|
|Creation stage||User-centred design and evolution including issues of privacy, anonymity, open versus closed communications.|
|Growth stage||Focus is on community building, for example: recruiting members, growth management, integrating new members, trust building, up-to-date content, interaction support, a few offline and online events and meetings.|
|Maturity stage||By this stage a community culture will have emerged with identifiable community leaders. Focus shifts to permeated management and control, recognition of contributions, recognition of loyalty, member satisfaction management and subgroup management.|
Additional factors identified by the research to keep in mind include:
- Network cohesion, that is the overall level of connections indicated by the network density has a positive impact on the core group as well as the success of the community (Toral et al 2010).
- Network structure. Successful communities need a critical mass of contributors, however there is no fixed number that determines success. Most communities can expect between 45 – 90% of non-active members, but communities with a strong and experienced core group will have a positive impact on success (Toral et al 2010). Moreover, the positive effects of network structure on participation persist irrespective of the life cycle stage of the community, and activity participation influences network structure (Igl 2014).
- Centralization. Communities with a high degree of centralisation and control exerts a negative impact on all participation variables. (Igl 2014).
There are many online communities, and it will be worth your effort in doing a little online research to determine the network cohesion and network structure of the community. You will be able to determine this by reviewing the archive history. Avoid communities with overly centralised control, in the long run, they are not likely to be productive.
When joining an online community, try to identify the life cycle stage by scanning the archive of posts. Young communities are likely to be more tolerant of newbie questions, as responses to these questions will provide support resources for new members in the future. It’s a good idea to search the forum for your answer before posting a question. Don’t be surprised if newbie questions go answered in mature communities, they may can even attract curt rebuttals. If you’re a long standing member of the community, post a tactful reply, for example, “Your question has already been answered” and post a link to the appropriate reply.
The best advice when joining a new community is to lurk for a while before introducing yourself so that you can become familiar with the culture and practices of the community. Fill out your profile page on the forum site, rather than posting a biography in the main discussion threads. Of course, if the community is in the creation phase, you may want to play a more active role in building the community and becoming part of the core contributors.
Read the following article which provides practical advice on selecting and engaging in an online community:
- Garcia, J. (2017, January 26). How to join a technical community. opensource.com. Retrieved July 6, 2017.
- Mockus, A., Fielding, R.T. and Herbsleb, J.D. (2002), “Two case studies of open source software development: Apache and Mozilla”, ACM Transactions on Software Engineering and Methodology, Vol. 11 No. 3, pp. 309-46.
- A. Iriberri and G. Leroy (2009), “A Life-Cycle Perspective on Online Community
Success,” ACM Computing Surveys, 41 (2), 11:1–11:29.
- Toral, S. L.; Martínez Torres, M. R., y Barrero, F. (2010).Analysis of Virtual Communities supporting OSS Projects using Social Network Analysis, Information and Software Technology. 52 (3), pp. 296-303.
- Igl, C. (2014). Dynamics in Online Communities – A Macro Level Investigation of Community Success (Dissertation). Technischen Universität München. Retrieved from http://mediatum.ub.tum.de/node?id=1218984