Cognitive Processing of Visually Presented Data in Decision Making

Abstract

We hope these recommendations will improve intelligence analysis of sentiment information via a new system.

The effects of visualization on judgment and decision-making: a systematic literature review

“…Jolicoeur and Dell'Acqua (1999) show in their experiment that the perception of visualizations is subject to structural constraints in working memory capacity, and Allen et al (2014) manipulate cognitive load as a dependent variable to demonstrate that judgment accuracy and speed using visualizations decrease under higher cognitive load. Subsequently, psychology experiments provide evidence that visualizations improve decision performance by reducing cognitive load as a mediating factor, operationalized and measured either through pupil size and dilation (Smerecnik et al 2010;Toker and Conati 2017) or self-reported load (Cassenti et al 2019). In management research, Ajayi (2014) investigates this relationship in the context of a proprietary visualization tool for financial data but finds no effect of the visualization component on cognitive load or judgment accuracy.…”

“…The visualization of information is associated with effective communication in terms of clarity (Suwa and Tversky 2002), speed (Perdana et al 2018), and the understanding of complex concepts (Wang et al 2017). Research shows, for example, that visualized risk data require less cognitive effort in interpretation than textual alternatives and are therefore comprehended more easily (Smerecnik et al 2010), and complex sentiment data visualized in a scatterplot improve the accuracy in law enforcement decisions compared to raw data (Cassenti et al 2019).…”

The Application of Big Data in Enterprise Information Intelligent Decision-Making

“…Big data storage capacity of enterprise of this magnitude is more common in the modern business and scientific fields; 2) Based on the data information of modern enterprise management, the data content applied and derived from the production and life of enterprise has diverse form, the diverse characteristics of enterprise big data are mainly divided into structured and unstructured enterprise big data. Among them, the structured enterprise big data is derived in the process of enterprise's normal operation and can be processed according to the specified mode to complete data storage and recording [10], but there are differences between unstructured and structured enterprise big data. This data is derived network data when enterprise uses the Internet, or related data derived from the use of a certain management technology, and belongs to data derived from interaction between people and people, people and machines, or machines and machines; 3) In the application of enterprise big data, high-speed is a significant core feature, which plays is a central role in the enterprise big data generation and management.…”