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Automatic analysis of online conversations as processes

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Abstract

The tremendous use of social media has changed the way society communicates and interacts nowadays, leading to a plethora of online conversations (Perrin et al., 2017). The increasing availability of these conversations as behavioral traces has enabled automatic approaches for behavior discovery and analysis. These approaches, grounded in machine learning, data mining and language processing have become effective predictive components and intelligent descriptive tools for many domains.
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Dates and versions

hal-01500497 , version 1 (10-04-2017)

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  • HAL Id : hal-01500497 , version 1

Cite

Elena Viorica Epure, Slavko Zitnik, Dario Compagno, Rebecca Deneckere, Camille Salinesi. Automatic analysis of online conversations as processes. JOURNÉES ANALYSE DE DONNÉES TEXTUELLES EN CONJONCTION AVEC EDA 2017, May 2017, Lyon, France. ⟨hal-01500497⟩
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