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A Semantics Extraction Framework for Decision Support in Context-Specific Social Web Networks

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Part of the book series: Lecture Notes in Business Information Processing ((LNBIP,volume 282))

Abstract

We are now part of a networked society, characterized by the intensive use and dependence of information systems that deals with communication and information, to support decision-making. It is thus clear that organizations, in order to interact effectively with their customers, need to manage their communication activities at the level of online channels. Monitoring these communications can contribute to obtain decision support insights, reduce costs, optimize processes, etc. In this work, we semantically studied the discursive exchanges of a Facebook group created by a strawberries’ seller, in order to predict, through Social Network Analysis (SNA) and semantic analysis of the posts, the quantities to be ordered by customers. The obtained results show that the unstructured data of the Web’s speech can be used to support the decision through SNA.

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Acknowledgments

This work has been supported by the Portuguese Foundation for Science and Technology (FCT) under project grant UID/MULTI/00308/2013.

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Correspondence to Manuela Freire .

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Freire, M., Antunes, F., Costa, J.P. (2017). A Semantics Extraction Framework for Decision Support in Context-Specific Social Web Networks. In: Linden, I., Liu, S., Colot, C. (eds) Decision Support Systems VII. Data, Information and Knowledge Visualization in Decision Support Systems. ICDSST 2017. Lecture Notes in Business Information Processing, vol 282. Springer, Cham. https://doi.org/10.1007/978-3-319-57487-5_10

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