%0 Conference Paper %1 citeulike:13029691 %A Muralidharan, Aditi %A Gyongyi, Zoltan %A Chi, Ed %B Proceedings of the SIGCHI Conference on Human Factors in Computing Systems %C New York, NY, USA %D 2012 %I ACM %K navigation-support rfpaws social-navigation social-search %P 1085--1094 %R 10.1145/2207676.2208554 %T Social Annotations in Web Search %U http://dx.doi.org/10.1145/2207676.2208554 %X We ask how to best present social annotations on search results, and attempt to find an answer through mixed-method eye-tracking and interview experiments. Current practice is anchored on the assumption that faces and names draw attention; the same presentation format is used independently of the social connection strength and the search query topic. The key findings of our experiments indicate room for improvement. First, only certain social contacts are useful sources of information, depending on the search topic. Second, faces lose their well-documented power to draw attention when rendered small as part of a social search result annotation. Third, and perhaps most surprisingly, social annotations go largely unnoticed by users in general due to selective, structured visual parsing behaviors specific to search result pages. We conclude by recommending improvements to the design and content of social annotations to make them more noticeable and useful. %@ 978-1-4503-1015-4

@inproceedings{citeulike:13029691, abstract = {{We ask how to best present social annotations on search results, and attempt to find an answer through mixed-method eye-tracking and interview experiments. Current practice is anchored on the assumption that faces and names draw attention; the same presentation format is used independently of the social connection strength and the search query topic. The key findings of our experiments indicate room for improvement. First, only certain social contacts are useful sources of information, depending on the search topic. Second, faces lose their well-documented power to draw attention when rendered small as part of a social search result annotation. Third, and perhaps most surprisingly, social annotations go largely unnoticed by users in general due to selective, structured visual parsing behaviors specific to search result pages. We conclude by recommending improvements to the design and content of social annotations to make them more noticeable and useful.}}, added-at = {2018-03-19T12:24:51.000+0100}, address = {New York, NY, USA}, author = {Muralidharan, Aditi and Gyongyi, Zoltan and Chi, Ed}, biburl = {https://www.bibsonomy.org/bibtex/2ef418c4030521381bfc883f05be88049/aho}, booktitle = {Proceedings of the SIGCHI Conference on Human Factors in Computing Systems}, citeulike-article-id = {13029691}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=2207676.2208554}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/2207676.2208554}, doi = {10.1145/2207676.2208554}, interhash = {830f569d895cd62a219a84aa1149ac5a}, intrahash = {ef418c4030521381bfc883f05be88049}, isbn = {978-1-4503-1015-4}, keywords = {navigation-support rfpaws social-navigation social-search}, location = {Austin, Texas, USA}, pages = {1085--1094}, posted-at = {2015-04-02 05:14:43}, priority = {2}, publisher = {ACM}, series = {CHI '12}, timestamp = {2018-03-19T12:24:51.000+0100}, title = {{Social Annotations in Web Search}}, url = {http://dx.doi.org/10.1145/2207676.2208554}, year = 2012 }