%0 Conference Paper %1 citeulike:165142 %A McDonald, David W. %B Proceedings of the SIGCHI conference on Human factors in computing systems %C New York, NY, USA %D 2003 %I ACM %K cscw latent people-recommender recommender %P 593--600 %R 10.1145/642611.642714 %T Recommending collaboration with social networks: a comparative evaluation %U http://dx.doi.org/10.1145/642611.642714 %X Studies of information seeking and workplace collaboration often find that social relationships are a strong factor in determining who collaborates with whom. Social networks provide one means of visualizing existing and potential interaction in organizational settings. Groupware designers are using social networks to make systems more sensitive to social situations and guide users toward effective collaborations. Yet, the implications of embedding social networks in systems have not been systematically studied. This paper details an evaluation of two different social networks used in a system to recommend individuals for possible collaboration. The system matches people looking for expertise with individuals likely to have expertise. The effectiveness of social networks for matching individuals is evaluated and compared. One finding is that social networks embedded into systems do not match individuals' perceptions of their personal social network. This finding and others raise issues for the use of social networks in groupware. Based on the evaluation results, several design considerations are discussed. %@ 1-58113-630-7

@inproceedings{citeulike:165142, abstract = {{Studies of information seeking and workplace collaboration often find that social relationships are a strong factor in determining who collaborates with whom. Social networks provide one means of visualizing existing and potential interaction in organizational settings. Groupware designers are using social networks to make systems more sensitive to social situations and guide users toward effective collaborations. Yet, the implications of embedding social networks in systems have not been systematically studied. This paper details an evaluation of two different social networks used in a system to recommend individuals for possible collaboration. The system matches people looking for expertise with individuals likely to have expertise. The effectiveness of social networks for matching individuals is evaluated and compared. One finding is that social networks embedded into systems do not match individuals' perceptions of their personal social network. This finding and others raise issues for the use of social networks in groupware. Based on the evaluation results, several design considerations are discussed.}}, added-at = {2018-03-19T12:24:51.000+0100}, address = {New York, NY, USA}, author = {McDonald, David W.}, biburl = {https://www.bibsonomy.org/bibtex/21543a12d0c6be8778ef8274f29620053/aho}, booktitle = {Proceedings of the SIGCHI conference on Human factors in computing systems}, citeulike-article-id = {165142}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=642714}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/642611.642714}, doi = {10.1145/642611.642714}, interhash = {282e6a461da3454f8dd8bb6aea117f86}, intrahash = {1543a12d0c6be8778ef8274f29620053}, isbn = {1-58113-630-7}, keywords = {cscw latent people-recommender recommender}, location = {Ft. Lauderdale, Florida, USA}, pages = {593--600}, posted-at = {2010-09-02 17:04:45}, priority = {2}, publisher = {ACM}, series = {CHI '03}, timestamp = {2018-03-19T12:24:51.000+0100}, title = {{Recommending collaboration with social networks: a comparative evaluation}}, url = {http://dx.doi.org/10.1145/642611.642714}, year = 2003 }