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Guest Editorial: Cognitive Analytics of Social Media for Industrial Manufacturing

Bashir, AK and Mumtaz, S and Menon, VG and Tsang, KF (2021) Guest Editorial: Cognitive Analytics of Social Media for Industrial Manufacturing. IEEE Transactions on Industrial Informatics, 17 (4). pp. 2899-2901. ISSN 1551-3203

Restricted to Repository staff only until 14 January 2023.

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The papers in this special section focus on cognitive analytics of social media for industrial manufacturing. Business innovation and industrial intelligence pave the way to a future in which smart factories, intelligent machines, networked processes, and big data are brought together to foster industrial growth and shift the modalities. Industry 4.0 or the Industrial Internet of Things (IIoT) is the latest catchphrase of technological innovation in manufacturing with the goal of increasing productivity in a flexible and efficient manner. Concurrently, the new collaborative Web (called Web 2.0) resiliently defines the notion of the techno-social system of computer-mediated, web/internet-based technologies and channels that have the primary objective of creating and enabling a collaborative and interactive virtual community of participants who can share or communicate information. These social technologies are essentially transforming the way we communicate, collaborate, consume, and create data and characterize one of the insurgent impacts of information technology on any industry, both within and outside industrial boundaries. Social media augments as a nontrivial element to this industrial value chain with the intent of making it more efficient. Collaborative sensing or crowd sensing can be used to help producers, suppliers, and customers understand and use insights learned from large amounts of sensing data in order to obtain competitive advantages

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