ABSTRACT
In the recent decade OTT platforms, also known as "Over the top," have seen a tremendous rise in the number of consumers and also gained a huge market share in the entertainment industry. The OTT service most users probably interact with regularly is video OTT. Services like Netflix and Disney+ Hotstar are video OTT services that provide users with a number of programming options, both in terms of a licensed library of TV shows and films and original programming. The study's objective is to carry out a detailed study of OTT (over-the-top) platforms, and how and why OTT platforms are rising in India. This study also investigates OTT platforms at the time of the COVID-19 pandemic. We found that recent years have witnessed several films emerging as pan-India hits, and the rise of alternative platforms has only widened the opportunities for actors and filmmakers. This study concludes that there is no competition between theatres and digital platforms filmmakers must up their game. OTT has resulted in more opportunities and redefined viewership patterns. Films and other mediums will thrive together because the same actors and makers are exploring different platforms. Copyright © 2023 Ubiquity Press. All rights reserved.
ABSTRACT
Purpose: The sudden outbreak of COVID-19 has become a major public health emergency of global concern. Studying the Internet public opinion dissemination mechanism of public health emergencies is of great significance for creating a legalized network environment, and it is also helpful for managers to make scientific decisions when encountering Internet public opinion crisis. Design/methodology/approach: Based on the analysis of the process of spreading the Internet public opinion in major epidemics, a dynamic model of the Internet public opinion spread system was constructed to study the interactive relationship among the public opinion events, network media, netizens and government and the spread of epidemic public opinion. The Shuanghuanglian event in COVID-19 in China was taken as a typical example to make simulation analysis. Findings: Research results show three points: (1) the government credibility plays a decisive role in the spread of Internet public opinion;(2) it is the best time to intervene when Internet public opinion occurred at first time;(3) the management and control of social media are the key to public opinion governance. Besides, specific countermeasures are proposed to assist control of Internet public opinion dissemination. Originality/value: The epidemic Internet public opinion risk evolution system is a complex nonlinear social system. The system dynamics model is used to carry out research to facilitate the analysis of the Internet public opinion propagation mechanism and explore the interrelationship of various factors. © 2021, Emerald Publishing Limited.
ABSTRACT
The aim of the work is to use deep neural network models for solving the problem of image recognition. These days, every human being is threatened by a harmful coronavirus disease, also called COVID-19 disease. The spread of coronavirus affects the economy of many countries in the world. To find COVID-19 patients early is very essential to avoid the spread and harm to society. Pathological tests and Chromatography(CT) scans are helpful for the diagnosis of COVID-19. However, these tests are having drawbacks such as a large number of false positives, and cost of these tests are so expensive. Hence, it requires finding an easy, accurate, and less expensive way for the detection of the harmful COVID-19 disease. Chest-x-ray can be useful for the detection of this disease. Therefore, in this work chest, x-ray images are used for the diagnosis of suspected COVID-19 patients using modern machine learning techniques. The analysis of the results is carried out and conclusions are made about the effectiveness of deep machine learning algorithms in image recognition problems.