Author(s)

Jean-Sébastien Vayre¹, Estelle Delpech², Aude Dufresne³, Céline Lemercier⁴

¹CERTOP (UMR-5044), University of Toulouse Jean Jaurès, Toulouse, France.
²Human Factors, Airbus, Blagnac, France.
³LRCM, University of Montréal, Montréal, Québec.
⁴CLLE (UMR-5263), University of Toulouse Jean Jaurès, Toulouse, France.

Along with the development of big data, various Natural Language Generation systems (NLGs) have recently been developed by different companies. The aim of this paper is to propose a better understanding of how these systems are designed and used. We propose to study in details one of them which is the NLGs developed by the company Nomao. First, we show the development of this NLGs underlies strong economic stakes since the business model of Nomao partly depends on it. Then, thanks to an eye movement analysis conducted with 28 participants, we show that the texts generated by Nomao’s NLGs contain syntactic and semantic structures that are easy to read but lack socio-semantic coherence which would improve their understanding. From a scientific perspective, our research results highlight the importance of socio-semantic coherence in text-based communication produced by NLGs.

Big Data, Natural Language Generation, Socio-Semantic Coherence, Cognitive Load, Reading, Eye Tracking

Vayre, J. , Delpech, E. , Dufresne, A. and Lemercier, C. (2017) Communication Mediated through Natural Language Generation in Big Data Environments: The Case of Nomao. Journal of Computer and Communications, 5, 125-148. doi: 10.4236/jcc.2017.56008.