An information-analytical system for assessing the level of automated news content according to the population structure – A platform for media literacy system development

Abstract

An increasingly complicated communications environment, including artificially manufactured information, requires new skills. No research has designed a mechanism to assess public views and attitudes toward automated news material in this changing environment. This study used a fuzzy information–analytical system to assess public perceptions and attitudes toward automated news content as a tool for building a national and international media literacy system. Our two-stage innovative information approach uses three social indicators and eight criteria to assess public views toward artificially manufactured content. We defined the input–data processing system first. In the second stage, we used a multiple-criteria fuzzy model to assess public opinion on artificially manufactured information. We modified a generalized logical conclusion to varied query answers. For multiple criteria evaluation, we employed matrix multiplication and multidimensional membership functions to determine public opinion toward artificially manufactured content for different social indicator groups. Aggregated ratings and public attitude toward artificially manufactured content were the output. Experimental data from 1041 Czech respondents supported the information–analytical system's efficacy. With this knowledge, national and institutional decision-makers and other stakeholders can analyze citizens of different social and economic backgrounds' public attitudes toward artificially created content and create information security-related decision-making support scenarios.