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Communication Dans Un Congrès Année : 2016

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

Résumé

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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Dates et versions

hal-01441580 , version 1 (19-01-2017)

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  • HAL Id : hal-01441580 , version 1

Citer

Ian Basaille, Sergey Kirgizov 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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