Modeling and predicting group activity over time in online social media Export

@inproceedings{DeChoudhury09, abstract = {This paper develops a probabilistic framework that can model and predict group activity over time on online social media. Users of social media sites such as Flickr often face the enormous challenge of which group to choose, due to the presence of numerous competing groups of similar content. Determining an empirical measure of significance of a group can help tackle this problem. The proposed framework therefore determines an optimal measure per group based on past user participation and interaction as well as likely future activity in the group. The framework is tested on a Flickr dataset and the results show that this method can yield satisfactory predictions of group activity. This implies that the computed measure of significance of a group can be used by end users to choose groups with rich activity.}, address = {New York, NY, USA}, author = {De Choudhury, Munmun}, booktitle = {HT '09: Proceedings of the 20th ACM conference on Hypertext and hypermedia}, citeulike-article-id = {5630177}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1557914.1557983}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1557914.1557983}, doi = {10.1145/1557914.1557983}, isbn = {978-1-60558-486-7}, keywords = {collaboration, flickr, online\_communities}, location = {Torino, Italy}, pages = {349--350}, posted-at = {2009-08-24 10:17:34}, priority = {2}, publisher = {ACM}, title = {Modeling and predicting group activity over time in online social media}, url = {http://dx.doi.org/10.1145/1557914.1557983}, year = {2009} }

TY - CONF ID - DeChoudhury09 L3 - citeulike-article-id:5630177 N2 - This paper develops a probabilistic framework that can model and predict group activity over time on online social media. Users of social media sites such as Flickr often face the enormous challenge of which group to choose, due to the presence of numerous competing groups of similar content. Determining an empirical measure of significance of a group can help tackle this problem. The proposed framework therefore determines an optimal measure per group based on past user participation and interaction as well as likely future activity in the group. The framework is tested on a Flickr dataset and the results show that this method can yield satisfactory predictions of group activity. This implies that the computed measure of significance of a group can be used by end users to choose groups with rich activity. CY - Torino, Italy SN - 978-1-60558-486-7 AD - New York, NY, USA EP - 350 TI - Modeling and predicting group activity over time in online social media PB - ACM T2 - HT '09: Proceedings of the 20th ACM conference on Hypertext and hypermedia SP - 349 KW - collaboration KW - flickr KW - online_communities AU - De Choudhury, Munmun PY - 2009/// UR - http://dx.doi.org/10.1145/1557914.1557983 ER -