This paper presents a Decision Support System (DSS) that helps companies with corporate reputation (CR) estimates of their respective brands by collecting provided feedbacks on their products and services and deriving state-of-the-art key performance indicators. A Sentiment Analysis Engine (SAE) is at the core of the proposed DSS that enables to monitor, estimate, and classify clients’ sentiments in terms of polarity, as expressed in public comments on social media (SM) company channels. The SAE is built on machine learning (ML) text classification models that are cross-source trained and validated with real data streams from a platform like Trustpilot that specializes in user reviews and tested on unseen comments gathered from a collection of public company pages and channels on a social networking platform like Facebook. Such crosssource opinion analysis remains a challenge and is highly relevant in the disciplines of research and engineering in which a sentiment classifier for an unlabeled destination domain is assisted by a tagged source task (Singh and Jaiswal, 2022). The best performance in terms of F1 score was obtained with a multinomial naive Bayes model: 0,87 for validation and 0,74 for testing.
The ever increasing technological developments and greater demands from our society for qualitative better, safer, sustainable products, processes and systems are pushing the boundaries of what is possible from an engineer’s perspective. Besides the (local) grand challenges in energy, sustainability, health and mobility the world is getting smaller due to advances in communication and digitalization. The exponential increase of complexity and data driven systems (big data) which are integrated and connected to different networks calls for rethinking and inventing new business models [1]. To stay competitive in the world OEM’s and SME’s have to develop breakthrough technological, innovative and advanced systems and processes. These changes have a major impact on engineering education. The industry needs engineers with different competences and skills to fulfil the challenges and demands mentioned earlier. Universities should follow up on these changes and can only deliver and prepare the engineers of the future by close collaboration with the high tech industry. Fontys University is fully aware of this and developed a Centre of Expertise in High Tech Systems & Materials (CoE HTSM) to close the gap between the university and industry. This CoE is a public-private cooperation where applied research, projects and educational programs for different curricula are being developed and executed. By making the industry partner and giving them a role within the university, the engineering education programs and the future engineering profile can be better aligned in a faster and more structural way.
The pace of introduction of new technology and thus continuous change in skill needs at workplaces, especially for the engineers, has increased. While digitization induced changes in manufacturing, construction and supply chain sectors may not be felt the same in every sector, this will be hard to escape. Both young and experienced engineers will experience the change, and the need to continuously assess and close the skills gap will arise. How will we, the continuing engineering educators and administrators will respond to it? Prepared for engineering educators and administrators, this workshop will shed light on the future of continuing engineering education as we go through exponentially shortened time frames of technological revolution and in very recent time, in an unprecedented COVID-19 pandemic. S. Chakrabarti, P. Caratozzolo, E. Sjoer and B. Norgaard.
