Some Literature Search on (Online) Community /Communities of Practice

1. Some Literature Search on (Online) Community /Communities of Practice Vincent Nov/2004

2. Survey on (Online) Community/Communities of Practice Keywords Related: Community (Communities) Online Community (Communities) Virtual Community (Communities) Communities of Practice (CoP) Computer Mediated Communication (CMC)

3. Survey on (Online) Community/Communities of Practice Keywords Search: of as a stopword; ___ the NASA Astrophysics Data System tokenize words in a phrase

4. Survey on (Online) Community/Communities of Practice • Some key conferences/journal related: • Communications of the ACM • CHI '(Year) extended abstracts on Human factors in computing systems • Journal of Computer-Mediated Communication (http://www.ascusc.org/jcmc/) • Active Research Centers: • HP Lab Information Dynamics ( http://www.hpl.hp.com/research/idl/) • (Complex) Network (http://www.nd.edu/~alb/)

5. Communities of Practice (COP) • Communities of Practice (COP) [proposed by E Wenger] • has been popularly mentioned in social science, physics literatures for a long time. COP are now going virtual/computer-mediated/online …… Many papers are dealing with online/virtual COP.

6. COP paper: • A. theories of COP are related to WWW studies: • "Power-Law Distribution of the World Wide Web". (Huberman, L. A. Adamic), Science, 287: 2115 (2000). • "Strong Regularities in World Wide Web Surfing", (Huberman, P. Pirolli, J. Pitkow and R. M. Lukose), Science, (1998). • "Evolutionary Dynamics of the World Wide Web", (Huberman, L. A. Adamic), Nature 401,131 (1999). • Modeling the Internet's large-scale topology Barabási PNAS 99, 13382-13386 (2002). • B. Specific COP issues: • “Finding Communities in Linear Time: a Physics Approach” (with Fang Wu), Eur.Phys. Journal B38, 331-338 (2004). • “Email as Spectroscopy: Automated Discovery of Community Structure within Organizations” (with J. Tyler and D. Wilkinson), in Communities and Technologies (2003). • How To Search a Social NetworkLada A. Adamic and Eytan Adar • Identifying communities of practice through ontology network analysis IEEE INTELL SYST 2003 C. Survey: 1. A survey of current research on online communities of practice (2001) Christopher M. Johnson

7. Some Featured Papers: • computer networks as social network wellman • computer netowrks are inherently social networks, linking people, organization, and knowledge. They should not be studied in isolation but as integrated into everyday lives.They have facilitated a deemphasis on group solidarities at work and in community and afforded a turn to networked societies that are loosely bounded and sparsely knit. • "New tools must be developed to help people navigate and find knowledge in complex, fragmented, networked societies“ social networks usually have complex topological properties and dynamical features that cannot accounted for by classical graph modeling ? Specifically, it is small-world properties and scale free degree distribution topology and correlations in structured scale-free network alexei vazquez the network is the least structured organization that can be said to have any structure at all Out of Control - kevin kelly

8. Some Featured Papers: • Discovering Shared Interests Among People Using Graph Analysis of global electronic mail traffic 1992 • wellman • heuristic algorithms to uncover shared interest relationships between people, based on the history of communications between people • algorithm can extract the implicit organizational structure from the graph • the densely interconnected nature of (email) communication graphs (due to small world phenomenon) allows one to perform shared interest analysis effectively on data collected at even a modest number of locations

9. Some Featured Papers: • information dynamics in the networked world Huberman, Adamic • review 3 studies of information flow in social networks that help reveal social structures, how information spreads, and why small world experiments work • 1st method: analyzing email communication automatically to expose community and their leaders; 2nd method: show the individuals associated by common interests influences the way of information spread [compared with viruses, information spreads quickly to relevant individuals,but cannot infect a population indiscriminately]; 3) individuals can use the structure of social networks to find short chains of acquaintances, which then results in the small world phonomena • email data for social network study is easy to get at low cost; the findings from email communication is claimed to be valid for other means social communication such as instant messenger systems, telephony system, verbal exchange • the Freeman's betweenness centrality algorithm is used to find communities/groups from large network. It can be a possible way to do clustering Paper B.3 Paper B.1, B.2 a betweeness centrality algorithm is developed to find communities within a graph representing the information (e.g. email) flow. It is effective at identifying true communities, both formal and informal, within these scale free graphs.

10. Some Featured Papers: self-similar community structure in organizations Guimera et al The formal structure in a organization is to handle routine and easily anticipated problems, but the formation of new ties should be achieved for extra tasks. Such informal networks behind the formal one is a key element for successful management. We analyse the complex e-mail network and determine its community structure. Our results reveal the emergence of self-similar properties that suggest that some universal mechanism could be the underlying driving force in the formation and evolution of informal networks in organisations, as happens in other self-organised complex systems. they show email network after the bulk emails are removed is exponential, which is contrast with the skewed degree distributions found in some technology based networks --- such as rough email networks, instant messaging network. But they correspond to the truncation of the scale free behavior in real world networks due to the existence of limitations or costs. They show the email network (hierachy/tree)sturcture demonstrated high self-similarity, and is analogous to river network structure, which can be more qualitatively studied by using some tools in river network literatures.Self-similarity is a fingerprint of the replication of the structure at different levels of organization, and might be the reusult of the trade-off between the need for cooperation and the physical constrains to establish connections at any organizational level. again, they only use the sender/receiver record to build the network instant messenging as a scale free network Reginald D. Smith 2002

11. Some Comments on COP Theoretical study in physics, case-study based social science research on communities have contributed a lot. They do a lot on how to under (online) COP…. Some forum-related communities have been studied too. COP can be further improved in function and organization, for example, combining topology and context. A topic can be augmenting the role of machine learners in building/maintaining a good online COP . And COP itself involves the behaviors of participants, which can also be an interesting issue to observe and study. By classifying COP as a special type of semistructured data (content + topology), more general issues are querying/mining/classifying/clustering/ranking the data. A type of problem in COP research is to find the communities which are somehow consistent with the underlying organization structure, or which have some meaning of some informal groups/ties. This research is tightly related with finding clusters from topological data. Actually the paper B.1 tries to build the spectral clustering method from a physics analogy, and claims to have liner time complexity O(V+E) by solving the problem iteratively. And the betweeness algorithm for finding communities is interesting. Communities are going virtual, the participants (learners) are going distributed. Observing/ Simulating the behaviors of multiple distributed learners is also important. They might provide hints to build ‘communities of machine learners’, eventually reach the functionality of human-based COP, which has the community knowledge as the core, in which the sum of this community knowledge is greater than sum of individual participant knowledge.

12. On Distributed Learning Keywords Search: