Abstract
The amount and variety of social media content such as status, images, movies, and music are increasing rapidly. Accordingly, the social curation service is emerging as a new way to connect, select, and organize information on a massive scale. One noticeable feature of social curation services is that they are loosely supervised: the content that users create in the service is manually collected, selected, and maintained. A large proportion of these contents are arbitrarily created by inexperienced users. In this paper, we look into social curation, particularly, the Storify website1. This is the most popular social curation for creating stories included in various domains such as Twitter, Flicker, and YouTube.We propose a machine learning method with feature extraction to filter these contents and to predict the popularity of social curation data.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Ahmed, M., Spagna, S., Huici, F., Niccolini, S.: A peek into the future: Predicting the evolution of popularity in user generated content. In: Proc. WSDM 2013 (2013)
Bandari, R., Asur, S., Huberman, B.A.: The pulse of news in social media: Forecasting popularity, CoRR, abs/1202.0332 (2012)
Cha, M., Mislove, A., Gummadi, K.P.: A measurement-driven analysis of information propagation in the Flickr social network. In: Proc. WWW 2009(2009)
Chang, C.C., Lin, C.J.: LIBSVM: A library for support vector machines. ACM Trans. Intelligent Systems and Technology 2 (2011)
Chen, Y.-W., Lin, C.-J.: Combining SVMs with various feature selection strategies. In: Guyon, I., Nikravesh, M., Gunn, S., Zadeh, L.A. (eds.) Feature Extraction. STUDFUZZ, vol. 207, pp. 315–324. Springer, Heidelberg (2006)
Duh, K., Hirao, T., Kimura, A., Ishiguro, K., Iwata, T., Au Yeung, C.-M.: Creating stories: Social curation on twitter messages. In: Proc. ICWSM (2012)
Greene, D., Sheridan, G., Smyth, B., Cunningham, P.: Aggregating content and network information to curate twitter user lists. In: Proc. ACM RecSys workshop, RSWeb (2012)
Hall, C., Zarro, M.: Social curation on the website Pinterest.com. In: Proc. ASIST 2012 (2012)
Hogg, T., Lerman, K.: Social dynamics of Digg, CoRR, abs/1202.0031 (2012)
Hong, L., Dan, O., Daviso, B.D.: Predicting popular messages in Twitter. In: Proc. WWW 2011 (2011)
Ishiguro, K., Kimura, A., Takeuchi, K.: Towards automatic image understanding and mining via social curation. In: Proc. ICDM 2012 (2012)
Jamali, S., Rangwala, H.: Digging Digg: Comment mining, popularity prediction, and social network analysis. In: Proc. WISM 2009 (2009)
Fincham, K.: Storify. The National Association for Media Literacy Educations Journal of Media Literacy Education (2011)
Kim, S.-D., Kim, S.-H., Cho, H.-G.: Predicting the virtual temperature of web-blog articles as a measurement tool for online popularity. In: Proc. CIT 2011(2011)
Lakkaraju, H., Ajmera, J.: Attention prediction on social media brand pages. In: Proc. CIKM 2011(2011)
Lee, J.G., Moon, S., Salamatian, K.: An approach to model and predict the popularity of online contents with explanatory factors. In: Proc. WI-IAT (2010)
Lee, J.G., Moon, S., Salamatian, K.: Modeling and predicting the popularity of online contents with Cox proportional hazard regression model. Neurocomputing (2012)
Lerman, K., Hogg, T.: Using a model of social dynamics to predict popularity of news. CoRR, abs/1004.5354 (2010)
Suh, B., Hong, L., Pirolli, P., Chi, E.H.: Want to be retweeted? Large scale analytics on factors impacting retweet in Twitter network. In: Social Computing, SocialCom (2010)
Szabo, G., Huberman, B.A.: Predicting the popularity of online content. Communications of the ACM 53, 80–88 (2010)
Tsagkias, M., Weerkamp, W., de Rijke, M.: News comments:Exploring, modeling, and online prediction. In: Gurrin, C., He, Y., Kazai, G., Kruschwitz, U., Little, S., Roelleke, T., Rüger, S., van Rijsbergen, K. (eds.) ECIR 2010. LNCS, vol. 5993, pp. 191–203. Springer, Heidelberg (2010)
YouTube Statistics, http://www.youtube.com/yt/press/statistics.html
Zarro, M., Hall, C.: Exploring social curation. D-Lib Magazine 18(11/12) (November/December 2012)
Van Zwol, R., Rae, A., Pueyo, L.G.: Prediction of favourite photos using social, visual, and textual signals. In: Proc. ACMMM (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Kieu, B.T., Ichise, R., Pham, S.B. (2015). Predicting the Popularity of Social Curation. In: Nguyen, VH., Le, AC., Huynh, VN. (eds) Knowledge and Systems Engineering. Advances in Intelligent Systems and Computing, vol 326. Springer, Cham. https://doi.org/10.1007/978-3-319-11680-8_33
Download citation
DOI: https://doi.org/10.1007/978-3-319-11680-8_33
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11679-2
Online ISBN: 978-3-319-11680-8
eBook Packages: EngineeringEngineering (R0)