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WhichStreams: A Dynamic Approach for Focused Data Capture from Large Social Media

Abstract : Due to the huge amount of data produced on large social media, capturing useful content usually implies to focus on subsets of data that fit with a pre-specified need. Considering the usual API restrictions of these media, we formulate this task of focused capture as a dynamic data sources selection problem. We then propose a machine learning methodology, named WhichStreams, which is based on an extension of a recently proposed combinatorial bandit algorithm. The evaluation of our approach on various Twitter datasets, with both offline and online settings, demonstrates the relevance of the proposal for leveraging the real-time data streaming APIs offered by most of the main social media.
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Contributor : Thibault Gisselbrecht Connect in order to contact the contributor
Submitted on : Tuesday, August 23, 2016 - 1:43:40 PM
Last modification on : Wednesday, January 12, 2022 - 3:47:19 AM


  • HAL Id : hal-01355397, version 1


Thibault Gisselbrecht, Patrick Gallinari, Sylvain Lamprier, Ludovic Denoyer. WhichStreams: A Dynamic Approach for Focused Data Capture from Large Social Media. Ninth International Conference on Web and Social Media, ICWSM 2015, May 2015, Oxford, United Kingdom. pp.130-139. ⟨hal-01355397⟩



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