Abstract
This paper describes the organisation and results of RepLab 2014, the third competitive evaluation campaign for Online Reputation Management systems. This year the focus lied on two new tasks: reputation dimensions classification and author profiling, which complement the aspects of reputation analysis studied in the previous campaigns. The participants were asked (1) to classify tweets applying a standard typology of reputation dimensions and (2) categorise Twitter profiles by type of author as well as rank them according to their influence. New data collections were provided for the development and evaluation of systems that participated in this benchmarking activity. © 2014 Springer International Publishing.
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Amigó, E., Carrillo-De-Albornoz, J., Chugur, I., Corujo, A., Gonzalo, J., Meij, E., … Spina, D. (2014). Overview of RepLab 2014: Author profiling and reputation dimensions for online reputation management. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8685 LNCS, pp. 307–322). Springer Verlag. https://doi.org/10.1007/978-3-319-11382-1_24
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