%0 Conference Paper %1 Movshovitz-Attias:2013:ARS:2492517.2500242 %A Movshovitz-Attias, Dana %A Movshovitz-Attias, Yair %A Steenkiste, Peter %A Faloutsos, Christos %B Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining %C New York, NY, USA %D 2013 %I ACM %K social-QA social-information-access %P 886--893 %R 10.1145/2492517.2500242 %T Analysis of the Reputation System and User Contributions on a Question Answering Website: StackOverflow %U http://doi.acm.org/10.1145/2492517.2500242 %X Question answering (Q&A) communities have been gaining popularity in the past few years. The success of such sites depends mainly on the contribution of a small number of expert users who provide a significant portion of the helpful answers, and so identifying users that have the potential of becoming strong contributers is an important task for owners of such communities. We present a study of the popular Q&A website StackOverflow (SO), in which users ask and answer questions about software development, algorithms, math and other technical topics. The dataset includes information on 3.5 million questions and 6.9 million answers created by 1.3 million users in the years 2008--2012. Participation in activities on the site (such as asking and answering questions) earns users reputation, which is an indicator of the value of that user to the site. We describe an analysis of the SO reputation system, and the participation patterns of high and low reputation users. The contributions of very high reputation users to the site indicate that they are the primary source of answers, and especially of high quality answers. Interestingly, we find that while the majority of questions on the site are asked by low reputation users, on average a high reputation user asks more questions than a user with low reputation. We consider a number of graph analysis methods for detecting influential and anomalous users in the underlying user interaction network, and find they are effective in detecting extreme behaviors such as those of spam users. Lastly, we show an application of our analysis: by considering user contributions over first months of activity on the site, we predict who will become influential long-term contributors. %@ 978-1-4503-2240-9

@inproceedings{Movshovitz-Attias:2013:ARS:2492517.2500242, abstract = {Question answering (Q&A) communities have been gaining popularity in the past few years. The success of such sites depends mainly on the contribution of a small number of expert users who provide a significant portion of the helpful answers, and so identifying users that have the potential of becoming strong contributers is an important task for owners of such communities. We present a study of the popular Q&A website StackOverflow (SO), in which users ask and answer questions about software development, algorithms, math and other technical topics. The dataset includes information on 3.5 million questions and 6.9 million answers created by 1.3 million users in the years 2008--2012. Participation in activities on the site (such as asking and answering questions) earns users reputation, which is an indicator of the value of that user to the site. We describe an analysis of the SO reputation system, and the participation patterns of high and low reputation users. The contributions of very high reputation users to the site indicate that they are the primary source of answers, and especially of high quality answers. Interestingly, we find that while the majority of questions on the site are asked by low reputation users, on average a high reputation user asks more questions than a user with low reputation. We consider a number of graph analysis methods for detecting influential and anomalous users in the underlying user interaction network, and find they are effective in detecting extreme behaviors such as those of spam users. Lastly, we show an application of our analysis: by considering user contributions over first months of activity on the site, we predict who will become influential long-term contributors.}, acmid = {2500242}, added-at = {2017-03-14T16:02:30.000+0100}, address = {New York, NY, USA}, author = {Movshovitz-Attias, Dana and Movshovitz-Attias, Yair and Steenkiste, Peter and Faloutsos, Christos}, biburl = {https://www.bibsonomy.org/bibtex/285a9232708eaf78eab4256d55947c7f3/angrrr}, booktitle = {Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining}, description = {Analysis of the reputation system and user contributions on a question answering website}, doi = {10.1145/2492517.2500242}, interhash = {34ede42391ba282a50b058f37c8d5057}, intrahash = {85a9232708eaf78eab4256d55947c7f3}, isbn = {978-1-4503-2240-9}, keywords = {social-QA social-information-access}, location = {Niagara, Ontario, Canada}, numpages = {8}, pages = {886--893}, publisher = {ACM}, series = {ASONAM '13}, timestamp = {2017-03-14T16:02:30.000+0100}, title = {Analysis of the Reputation System and User Contributions on a Question Answering Website: StackOverflow}, url = {http://doi.acm.org/10.1145/2492517.2500242}, year = 2013 }