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Article Dans Une Revue Social Network Analysis and Mining Année : 2024

ProxMetrics: modular proxemic similarity toolkit to generate domain-adaptable indicators from social media

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In this paper, we introduce ProxMetrics , a novel toolkit designed to evaluate similarity among social media entities through proxemic dimensions. Proxemics is the science that studies the organization of space and the effects of distances on behavior and interactions. It encompasses 5 core dimensions: Distance, Identity, Location, Movement, and Orientation. Adapting the principles of traditional physical proxemics to the digital world of social media, we present a method and a modular similarity function to determine proxemic similarity scores across heterogeneous social media entities ( users, groups, places, themes and times ) based on these dimensions. The approach used is intended to be modular and generic, ensuring adaptability across various application domains and requirements. The calculated scores act as indicators and offer valuable insights for stakeholders, aligning with distinct domain requirements. Empirical testing in the tourism domain highlights the toolkit’s extensive applicability across a variety of requirements.
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hal-04629357 , version 1 (29-06-2024)

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Maxime Masson, Philippe Roose, Christian Sallaberry, Marie-Noelle Bessagnet, Annig Le Parc-Lacayrelle, et al.. ProxMetrics: modular proxemic similarity toolkit to generate domain-adaptable indicators from social media. Social Network Analysis and Mining, 2024, 14 (1), pp.124. ⟨10.1007/s13278-024-01282-1⟩. ⟨hal-04629357⟩

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