Deep learning-based user experience evaluation in distance learning.

The Covid-19 pandemic caused uncertainties in many different organizations, institutions gained experience in remote working and showed that high-quality distance education is a crucial component in higher education. The main concern in higher education is the impact of distance education on the quality of learning during such a pandemic. Although this type of education may be considered effective and beneficial at first glance, its effectiveness highly depends on a variety of factors such as the availability of online resources and individuals' financial situations. In this study, the effectiveness of e-learning during the Covid-19 pandemic is evaluated using posted tweets, sentiment analysis, and topic modeling techniques. More than 160,000 tweets, addressing conditions related to the major change in the education system, were gathered from Twitter social network and deep learning-based sentiment analysis models and topic models based on latent dirichlet allocation (LDA) algorithm were developed and analyzed. Long short term memory-based sentiment analysis model using word2vec embedding was used to evaluate the opinions of Twitter users during distance education and also, a topic model using the LDA algorithm was built to identify the discussed topics in Twitter. The conducted experiments demonstrate the proposed model achieved an overall accuracy of 76%. Our findings also reveal that the Covid-19 pandemic has negative effects on individuals 54.5% of tweets were associated with negative emotions whereas this was relatively low on emotion reports in the YouGov survey and gender-rescaled emotion scores on Twitter. In parallel, we discuss the impact of the pandemic on education and how users' emotions altered due to the catastrophic changes allied to the education system based on the proposed machine learning-based models.

Rapid Growth of the World Population and Its Socioeconomic Results.

This article is mainly devoted to the study of socioeconomic opportunities and problems that may arise from the growth of the world's population. The article identifies the reasons for the increase in world population and analyzes the factors influencing on the process. The article examines the impact of changes on the world's demographics on socioeconomic development. As a result, the characteristics of possible problems were investigated and evaluated. The study analyzes the issues of demographic change in the world population, the current situation, and opportunities of the world economy in accordance with population statistics and its growth rate. The main purpose of the study is to determine the causes of world population growth, analyze the current demographic situation, and determine and assess the forecast of future growth dynamics. The study discusses, analyzes, and evaluates the problems that can be caused by the growth of the world's population. The main problem we raise in the study is the mismatch between the rapid growth of the world's population and the socioeconomic security of the people. That is, if the issue of socioeconomic security is not resolved, the growth of the world's population would be a global social problem.