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Communication dans un congrès

Towards A Twitter Observatory: A Multi-Paradigm Framework For Collecting, Storing And Analysing Tweets

Abstract : In this article we show how a multi-paradigm framework can fulfil the requirements of tweets analysis and reduce the waiting time for researchers that use computational resources and storage systems to support large-scale data analysis. The originality of our approach is to combine concerns about data harvesting, data storage, data analysis and data visualisation into a framework that supports inductive reasoning in multidisciplinary scientific research. Our main contribution is a polyglot storage system with a generic data model to support logical data independence and a set of tools that can provide a suitable solution for mixing different types of algorithms in order to maximise the extraction of knowledge. We describe the software architecture of our framework, the generic model and we show how it has been used in major projects and what characteristics have been validated.
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https://hal-univ-bourgogne.archives-ouvertes.fr/hal-01441580
Contributeur : Le2i - Université de Bourgogne <>
Soumis le : jeudi 19 janvier 2017 - 19:44:25
Dernière modification le : vendredi 17 juillet 2020 - 14:54:10

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  • HAL Id : hal-01441580, version 1

Citation

Ian Basaille, Sergey Kirgizov, Eric Leclercq, Marinette Savonnet, Nadine Cullot. Towards A Twitter Observatory: A Multi-Paradigm Framework For Collecting, Storing And Analysing Tweets. IEEE 10th International Conference on Research Challenges in Information Science, May 2016, Grenoble, France. pp.77-86. ⟨hal-01441580⟩

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