A supervised multinomial classification framework for emotion recognition in textual social data

Wani, Abid Hussain; Hashmy, Rana

doi:10.1504/ijaip.2023.128080

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2023

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“…The DEAP (Database for Emotion Analysis using Physiological Signals) [33]. In addition to this, the general problem has been stirred-up by several research efforts in the community (e.g., [58,12,40,57,32]).…”

Section: Introductionmentioning

confidence: 99%

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2023

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The development and diffusion of Internet of Things, Artificial Intelligence, Business Intelligence and Visual Analytics solutions has brought new paradigms to exploit Big Data analytics into Decision Support Systems. The increasing requirements of automating Decision Support Systems and making them more efficient and reliable represent a research field which has recently attracted a lot of interest and efforts. The main challenges are represented by the initial black-box nature of machine learning and deep learning methods, which often cannot deal with the necessity to provide explainable results, which is a critical aspect when dealing, for instance, with automated decision processes in legal and administrative contexts. This paper presents a study of the main concepts and requirements for enhancing Decision Support through big data visual analytics, presenting the Snap4City solution and describing some real use cases in which it has been and is currently being exploited.

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