A Framework for Recommendation of Highly Popular News Lacking Social Feedback

dc.contributor.author Nuno Miguel Moniz en
dc.contributor.author Luís Torgo en
dc.contributor.author Eirinaki,M en
dc.contributor.author Paula Oliveira Branco en
dc.date.accessioned 2017-12-31T16:33:26Z
dc.date.available 2017-12-31T16:33:26Z
dc.date.issued 2017 en
dc.description.abstract Social media is rapidly becoming the main source of news consumption for users, raising significant challenges to news aggregation and recommendation tasks. One of these challenges concerns the recommendation of very recent news. To tackle this problem, approaches to the prediction of news popularity have been proposed. In this paper, we study the task of predicting news popularity upon their publication, when social feedback is unavailable or scarce, and to use such predictions to produce news rankings. Unlike previous work, we focus on accurately predicting highly popular news. Such cases are rare, causing known issues for standard prediction models and evaluation metrics. To overcome such issues we propose the use of resampling strategies to bias learners towards these rare cases of highly popular news, and a utility-based framework for evaluating their performance. An experimental evaluation is performed using real-world data to test our proposal in distinct scenarios. Results show that our proposed approaches improve the ability of predicting and recommending highly popular news upon publication, in comparison to previous work. © 2017 Ohmsha, Ltd. and Springer Japan en
dc.identifier.uri http://repositorio.inesctec.pt/handle/123456789/5189
dc.identifier.uri http://dx.doi.org/10.1007/s00354-017-0019-x en
dc.language eng en
dc.relation 4982 en
dc.relation 5934 en
dc.relation 5953 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title A Framework for Recommendation of Highly Popular News Lacking Social Feedback en
dc.type article en
dc.type Publication en
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
P-00M-VY0.pdf
Size:
2.08 MB
Format:
Adobe Portable Document Format
Description: