Identifying and Ranking the Effective Variables of Artificial Intelligence-based Media Platform Management

Subject Areas : Iranian Sociological Review

Yousof Hodaie ¹ , Nazanin Malekian ² , Akbar Nasrollahi ³

1 - Ph.D. Student in Media Management, Faculty of Humanities, West Tehran Branch, Islamic Azad University, Tehran, Iran
2 - Associate Professor, Department of Cultural and Media Studies, Central Tehran Branch, Islamic Azad University, Tehran, Iran
3 - Associate Professor, Department of Media Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

Received: 2024-04-16 Accepted : 2024-06-26 Published : 2024-09-25

Keywords: management of media platforms, artificial intelligence, social media, technology and information, foundation data,

Abstract :

In today's fast-paced digital world, the media landscape is constantly changing, with new technologies and developments shaping the way information is disseminated and consumed. One of the most important developments in recent years has been the integration of artificial intelligence (AI) into media management. Artificial intelligence has changed the way media organizations operate, from content production to distribution and audience attraction, control and monitoring of revenue. In this article, we will examine the impact of artificial intelligence on media management and how it will shape the media industry. This research is a descriptive-inductive type of research that deals with the qualitative method (foundation data) to discover, describe, describe and model their characteristics. In terms of how to collect the required data, the present research is classified in the "exploratory qualitative research" group. Since the participants in qualitative type of research are not determined before conducting the research, rather the interview process is carried out until no new data is obtained and data saturation is reached. Conducting interviews in the present study reached saturation with 18 people. All the indicators obtained from the open coding stage were determined in this stage and 15 main categories and 74 sub-categories were obtained and a paradigm model was discovered from it, the main categories include: laws and regulations of the country in order to apply technology, experience management and User satisfaction, analyzing and solving management challenges by artificial intelligence-based systems, government support, data and software infrastructure, public and social infrastructure

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