| Summary: | International audience Background: Scientific work on the social dimensions of Flow seems to be increasing, but it is currently very fragmented. Moreover, most of them do not know each other. This is why it seems important to identify, collect and make available to the entire scientific community a corpus of academic papers via a freely accessible database. Aims: Our objective is to implement and optimize a generic method for identifying and classifying articles after lexical analysis of abstracts. Methods: We designed and ran a specially crafted search query (a specific combination of keywords and Boolean operators) that come under the notion of social flow, yielding thus a lower number of false-positive results. We were thus successful in identifying about 265 papers from 70 publishers, divided in 39 PhDs and 226 scientific contributions, spanning the last 20 years. Results: The firstTop-Down Hierarchical Clustering of vocabulary of all these abstracts highlight 4 main classes: (1) the different contexts of flow study in groups, (2) theoretical models used for flow study in groups (3) the effects of flow in groups and (4) the human consequences of flow in groups. The correspondence factor analysis allows in particular to identify very clearly the main authors related to each of these 4 classes. Conclusion: The development and optimization of this method will make it possible to strengthen the literature reviews and scoping reviews of researchers and PhD students. It can be a way to federate an international research network on the social dimensions of the optimal experience.
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