%0 Conference Paper %1 citeulike:14133895 %A Liu, Yiming %A Cao, Xuezhi %A Yu, Yong %B Proceedings of the 10th ACM Conference on Recommender Systems %C New York, NY, USA %D 2016 %I ACM %K recommender recsys2016 %P 269--272 %R 10.1145/2959100.2959141 %T Are You Influenced by Others When Rating?: Improve Rating Prediction by Conformity Modeling %U http://dx.doi.org/10.1145/2959100.2959141 %X Conformity has a strong influence to user behaviors, even in online environment. When surfing online, users are usually flooded with others' opinions. These opinions implicitly contribute to the user's ongoing behaviors. However, there is no research work modeling online conformity yet. In this paper, we model user's conformity in online rating sites. We conduct analysis using real data to show the existence and strength of conformity in these scenarios. We propose a matrix-factorization-based conformity modeling technique to improve the accuracy of rating prediction. Experiments show that our model outperforms existing works significantly (with a relative improvement of 11.72\% on RMSE). Therefore, we draw the conclusion that conformity modeling is important for understanding user behaviors and can contribute to further improve the online recommender systems. %@ 978-1-4503-4035-9

@inproceedings{citeulike:14133895, abstract = {{Conformity has a strong influence to user behaviors, even in online environment. When surfing online, users are usually flooded with others' opinions. These opinions implicitly contribute to the user's ongoing behaviors. However, there is no research work modeling online conformity yet. In this paper, we model user's conformity in online rating sites. We conduct analysis using real data to show the existence and strength of conformity in these scenarios. We propose a matrix-factorization-based conformity modeling technique to improve the accuracy of rating prediction. Experiments show that our model outperforms existing works significantly (with a relative improvement of 11.72\% on RMSE). Therefore, we draw the conclusion that conformity modeling is important for understanding user behaviors and can contribute to further improve the online recommender systems.}}, added-at = {2018-03-19T12:24:51.000+0100}, address = {New York, NY, USA}, author = {Liu, Yiming and Cao, Xuezhi and Yu, Yong}, biburl = {https://www.bibsonomy.org/bibtex/273aa7126de137b695d0c1ec078a875a1/aho}, booktitle = {Proceedings of the 10th ACM Conference on Recommender Systems}, citeulike-article-id = {14133895}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=2959141}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/2959100.2959141}, doi = {10.1145/2959100.2959141}, interhash = {aa52a7d7640a4a566602c2ef7e8ef548}, intrahash = {73aa7126de137b695d0c1ec078a875a1}, isbn = {978-1-4503-4035-9}, keywords = {recommender recsys2016}, location = {Boston, Massachusetts, USA}, pages = {269--272}, posted-at = {2016-09-18 20:04:22}, priority = {2}, publisher = {ACM}, series = {RecSys '16}, timestamp = {2018-03-19T12:24:51.000+0100}, title = {{Are You Influenced by Others When Rating?: Improve Rating Prediction by Conformity Modeling}}, url = {http://dx.doi.org/10.1145/2959100.2959141}, year = 2016 }