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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 4, 2022.
Abstract: In these days, strategic decision making and im-mediate action are becoming a complex task for companies and policymakers, since the environment is subject to emerging changes that might include unknown factors. When facing these challenges, companies are exposed to opportunities for growth, but also to threats. Therefore, they seek to explore and analyze large amounts of data to detect emerging changes, or so-called weak signals, that can help maintaining their competitive advantages and shaping up their future operational environments. But due to the increasing volume of daily produced data, scalable and automated computer-aided systems are needed to explore and extract these weak signals. To overcome the automation and scalability challenges, and capture early signs of change in a big data environment, we propose a framework for weak signals detection relying on the network topology. It is implemented under the Cocktail project framework whose goal is to create a real-time observatory of trends, innovations and weak signals circulating in the discourses of the food and health sectors on Twitter. This method analyses quantitatively the network local structure using the graphlets (particular type of motifs) to find weak signals. It provides accordingly qualitative elements that contextualise the identified signals, which will allow business experts to interpret and evaluate their dynamics to determine which ones may have a relevant future. After testing this method on different types of networks (we present two of them in this paper), we proved that it is able to detect weak signals and provides a quantifiable signature that allows better decision making.
Hiba Abou Jamra, Marinette Savonnet and Eric Leclercq, “BEAM: A Network Topology Framework to Detect Weak Signals” International Journal of Advanced Computer Science and Applications(IJACSA), 13(4), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130402
@article{Jamra2022,
title = {BEAM: A Network Topology Framework to Detect Weak Signals},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130402},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130402},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {4},
author = {Hiba Abou Jamra and Marinette Savonnet and Eric Leclercq}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.