  In this article, we show how the mathematical object tensor can be used to
build a multi-paradigm model for the storage of social data in data warehouses.
From an architectural point of view, our approach allows to link different
storage systems (polystore) and limits the impact of ETL tools performing model
transformations required to feed different analysis algorithms. Therefore,
systems can take advantage of multiple data models both in terms of query
execution performance and the semantic expressiveness of data representation.
The proposed model allows to reach the logical independence between data and
programs implementing analysis algorithms. With a concrete case study on
message virality on Twitter during the French presidential election of 2017, we
highlight some of the contributions of our model.
