%0 Conference Paper %1 Gilbert:2012:PTS:2145204.2145360 %A Gilbert, Eric %B Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work %C New York, NY, USA %D 2012 %I ACM %K done reticollab1213 %P 1047--1056 %R 10.1145/2145204.2145360 %T Predicting tie strength in a new medium %U http://doi.acm.org/10.1145/2145204.2145360 %X We have friends we consider very close and acquaintances we barely know. The social sciences use the term tie strength to denote this differential closeness with the people in our lives. In this paper, we explore how well a tie strength model developed for one social medium adapts to another. Specifically, we present a Twitter application called We Meddle which puts a Facebook tie strength model at the core of its design. We Meddle estimated tie strengths for more than 200,000 online relationships from people in 52 countries. We focus on the mapping of Facebook relational features to relational features in Twitter. By examining We Meddle's mistakes, we find that the Facebook tie strength model largely generalizes to Twitter. This is early evidence that important relational properties may manifest similarly across different social media, a finding that would allow new social media sites to build around relational findings from old ones. %@ 978-1-4503-1086-4

@inproceedings{Gilbert:2012:PTS:2145204.2145360, abstract = {We have friends we consider very close and acquaintances we barely know. The social sciences use the term tie strength to denote this differential closeness with the people in our lives. In this paper, we explore how well a tie strength model developed for one social medium adapts to another. Specifically, we present a Twitter application called We Meddle which puts a Facebook tie strength model at the core of its design. We Meddle estimated tie strengths for more than 200,000 online relationships from people in 52 countries. We focus on the mapping of Facebook relational features to relational features in Twitter. By examining We Meddle's mistakes, we find that the Facebook tie strength model largely generalizes to Twitter. This is early evidence that important relational properties may manifest similarly across different social media, a finding that would allow new social media sites to build around relational findings from old ones.}, acmid = {2145360}, added-at = {2012-10-08T01:39:35.000+0200}, address = {New York, NY, USA}, author = {Gilbert, Eric}, biburl = {https://www.bibsonomy.org/bibtex/23f692489f4c22aa206a13039d951824a/lanubile}, booktitle = {Proceedings of the ACM 2012 conference on Computer Supported Cooperative Work}, description = {Predicting tie strength in a new medium}, doi = {10.1145/2145204.2145360}, interhash = {479436e7024f745b5f11af2b0f16bd7b}, intrahash = {3f692489f4c22aa206a13039d951824a}, isbn = {978-1-4503-1086-4}, keywords = {done reticollab1213}, location = {Seattle, Washington, USA}, numpages = {10}, pages = {1047--1056}, publisher = {ACM}, series = {CSCW '12}, timestamp = {2013-09-23T15:37:42.000+0200}, title = {Predicting tie strength in a new medium}, url = {http://doi.acm.org/10.1145/2145204.2145360}, year = 2012 }