Analysis of social voting patterns on digg Export

@inproceedings{lerman:voting, abstract = {The social Web is transforming the way information is created and distributed. Blog authoring tools enable users to publish content, while sites such as Digg and Del.icio.us are used to distribute content to a wider audience. With content fast becoming a commodity, interest in using social networks to promote and find content has grown, both on the side of content producers (viral marketing) and consumers (recommendation). Here we study the role of social networks in promoting content on Digg, a social news aggregator that allows users to submit links to and vote on news stories. Digg's goal is to feature the most interesting stories on its front page, and it aggregates opinions of its many users to identify them. Like other social networking sites, Digg allows users to designate other users as "friends" and see what stories they found interesting. We studied the spread of interest in news stories submitted to Digg in June 2006. Our results suggest that pattern of the spread of interest in a story on the network is indicative of how popular the story will become. Stories that spread mainly outside of the submitter's neighborhood go on to be very popular, while stories that spread mainly through submitter's social neighborhood prove not to be very popular. This effect is visible already in the early stages of voting, and one can make a prediction about the potential audience of a story simply by analyzing where the initial votes come from.}, address = {New York, NY, USA}, author = {Lerman, Kristina and Galstyan, Aram}, booktitle = {WOSN '08: Proceedings of the first workshop on Online social networks}, citeulike-article-id = {5225891}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1397735.1397738}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1397735.1397738}, doi = {10.1145/1397735.1397738}, isbn = {978-1-60558-182-8}, keywords = {online-social-networks, social-networks, web20}, location = {Seattle, WA, USA}, month = {August}, pages = {7--12}, posted-at = {2009-10-19 08:47:41}, priority = {2}, publisher = {ACM}, title = {Analysis of social voting patterns on digg}, url = {http://dx.doi.org/10.1145/1397735.1397738}, year = {2008} }

TY - CONF ID - lerman:voting L3 - citeulike-article-id:5225891 N2 - The social Web is transforming the way information is created and distributed. Blog authoring tools enable users to publish content, while sites such as Digg and Del.icio.us are used to distribute content to a wider audience. With content fast becoming a commodity, interest in using social networks to promote and find content has grown, both on the side of content producers (viral marketing) and consumers (recommendation). Here we study the role of social networks in promoting content on Digg, a social news aggregator that allows users to submit links to and vote on news stories. Digg's goal is to feature the most interesting stories on its front page, and it aggregates opinions of its many users to identify them. Like other social networking sites, Digg allows users to designate other users as "friends" and see what stories they found interesting. We studied the spread of interest in news stories submitted to Digg in June 2006. Our results suggest that pattern of the spread of interest in a story on the network is indicative of how popular the story will become. Stories that spread mainly outside of the submitter's neighborhood go on to be very popular, while stories that spread mainly through submitter's social neighborhood prove not to be very popular. This effect is visible already in the early stages of voting, and one can make a prediction about the potential audience of a story simply by analyzing where the initial votes come from. CY - Seattle, WA, USA SN - 978-1-60558-182-8 AD - New York, NY, USA EP - 12 TI - Analysis of social voting patterns on digg PB - ACM T2 - WOSN '08: Proceedings of the first workshop on Online social networks SP - 7 KW - online-social-networks KW - social-networks KW - web20 AU - Lerman, Kristina AU - Galstyan, Aram PY - 2008/August// UR - http://dx.doi.org/10.1145/1397735.1397738 ER -