%0 Generic %1 citeulike:137147 %A Adamic, Lada A. %A Adar, Eytan %D 2004 %K application community sna %T How to search a social network %U http://arxiv.org/abs/cond-mat/0310120 %X We address the question of how participants in a small world experiment are able to find short paths in a social network using only local information about their immediate contacts. We simulate such experiments on a network of actual email contacts within an organization as well as on a student social networking website. On the email network we find that small world search strategies using a contact's position in physical space or in an organizational hierarchy relative to the target can effectively be used to locate most individuals. However, we find that in the online student network, where the data is incomplete and hierarchical structures are not well defined, local search strategies are less effective. We compare our findings to recent theoretical hypotheses about underlying social structure that would enable these simple search strategies to succeed and discuss the implications to social software design.

@misc{citeulike:137147, abstract = {We address the question of how participants in a small world experiment are able to find short paths in a social network using only local information about their immediate contacts. We simulate such experiments on a network of actual email contacts within an organization as well as on a student social networking website. On the email network we find that small world search strategies using a contact's position in physical space or in an organizational hierarchy relative to the target can effectively be used to locate most individuals. However, we find that in the online student network, where the data is incomplete and hierarchical structures are not well defined, local search strategies are less effective. We compare our findings to recent theoretical hypotheses about underlying social structure that would enable these simple search strategies to succeed and discuss the implications to social software design.}, added-at = {2006-09-25T12:54:00.000+0200}, author = {Adamic, Lada A. and Adar, Eytan}, biburl = {https://www.bibsonomy.org/bibtex/20f695a72a5ccaa986dbdfac5e8126ae3/grahl}, citeulike-article-id = {137147}, comment = {"For the developers of social software it is important to understand how differ- ent data collection techniques (automated, implicit versus manual, explicit) impact the resulting social network and how these networks relate to the real world. Where the data is incomplete or reflects non-hierarchical struc- ture, tools that support social search should assist users by either providing a broader view of their local community or directly assisting users through a global analysis of the network data." --- dataset: hp emails, hp filtered emails, network of friends (explicit) Which expert finding strategy should be recommended to the users, depending on the kind of network (power law VS poisson network) Three search strategies: ("If you want to reach sombody, who would you pass the messege next?") 1) best connected 2) closest to target in the organizational hierarchy 3) located in closest physical proximity to the target 1) is best for power law networks, where 2) is best for poisson nets.}, eprint = {cond-mat/0310120}, interhash = {f84de93ef4b02a3853420d18e8b7f6cb}, intrahash = {0f695a72a5ccaa986dbdfac5e8126ae3}, keywords = {application community sna}, month = {November}, priority = {0}, timestamp = {2007-07-25T11:36:55.000+0200}, title = {How to search a social network}, url = {http://arxiv.org/abs/cond-mat/0310120}, year = 2004 }