In this work we examine nine different sources for user similarity as reflected by activity in social media applications. We suggest a classification of these sources into three categories: people, things, and places. Lists of similar people returned by the nine sources are found to be highly different from each other as well as from the list of people the user is familiar with, suggesting that aggregation of sources may be valuable. Evaluation of the sources and their aggregates points at their usefulness across different scenarios, such as information discovery and expertise location, and also highlights sources and aggregates that are particularly valuable for inferring user similarity.
%0 Conference Paper
%1 1718928
%A Guy, Ido
%A Jacovi, Michal
%A Perer, Adam
%A Ronen, Inbal
%A Uziel, Erel
%B CSCW '10: Proceedings of the 2010 ACM conference on Computer supported cooperative work
%C New York, NY, USA
%D 2010
%I ACM
%K cscw2010 reticollab1011
%P 41--50
%R 10.1145/1718918.1718928
%T Same places, same things, same people?: mining user similarity on social media
%U http://portal.acm.org/citation.cfm?id=1718918.1718928&coll=&dl=acm&type=series&idx=SERIES296&part=series&WantType=Proceedings&title=CSCW&CFID=104944628&CFTOKEN=84854578
%X In this work we examine nine different sources for user similarity as reflected by activity in social media applications. We suggest a classification of these sources into three categories: people, things, and places. Lists of similar people returned by the nine sources are found to be highly different from each other as well as from the list of people the user is familiar with, suggesting that aggregation of sources may be valuable. Evaluation of the sources and their aggregates points at their usefulness across different scenarios, such as information discovery and expertise location, and also highlights sources and aggregates that are particularly valuable for inferring user similarity.
%@ 978-1-60558-795-0
@inproceedings{1718928,
abstract = {In this work we examine nine different sources for user similarity as reflected by activity in social media applications. We suggest a classification of these sources into three categories: people, things, and places. Lists of similar people returned by the nine sources are found to be highly different from each other as well as from the list of people the user is familiar with, suggesting that aggregation of sources may be valuable. Evaluation of the sources and their aggregates points at their usefulness across different scenarios, such as information discovery and expertise location, and also highlights sources and aggregates that are particularly valuable for inferring user similarity.},
added-at = {2010-10-08T18:01:25.000+0200},
address = {New York, NY, USA},
author = {Guy, Ido and Jacovi, Michal and Perer, Adam and Ronen, Inbal and Uziel, Erel},
biburl = {https://www.bibsonomy.org/bibtex/2813cfb9da6574b164156da7518c8c3c9/domenico79},
booktitle = {CSCW '10: Proceedings of the 2010 ACM conference on Computer supported cooperative work},
description = {CSCW: CSCW '10, Same places, same things, ...},
doi = {10.1145/1718918.1718928},
interhash = {99ea81cf4fa857bb4cf9d7b96e2fad50},
intrahash = {813cfb9da6574b164156da7518c8c3c9},
isbn = {978-1-60558-795-0},
keywords = {cscw2010 reticollab1011},
location = {Savannah, Georgia, USA},
pages = {41--50},
publisher = {ACM},
timestamp = {2010-10-08T18:01:25.000+0200},
title = {Same places, same things, same people?: mining user similarity on social media},
url = {http://portal.acm.org/citation.cfm?id=1718918.1718928&coll=&dl=acm&type=series&idx=SERIES296&part=series&WantType=Proceedings&title=CSCW&CFID=104944628&CFTOKEN=84854578},
year = 2010
}