جستجوی مقالات مرتبط با کلیدواژه "vod" در نشریات گروه "مدیریت"

With the advent of digital technologies and the emergence of VOD media services, the landscape of cultural and creative industries has undergone a dramatic transformation. In particular, the market of these media in Iran has witnessed significant growth and offers a diverse range of content to meet the preferences of Persian-speaking audiences around the world. This research deals with the social assessment of Iranian VOD media and their opinion analysis among Persian Twitter users. The purpose of this study is to measure the influence and dynamics of Iranian VODs in the framework of Persian Twitter using data mining methods, computational social sciences, sentiment analysis and theme analysis. Through thematic analysis, six overarching themes were extracted: 1. Dark strains of VOD, 2. Broadcasting monitoring of VOD, 3. Popularity of VOD and its effective factors, 4. Filter and closure of VOD, 5. Actors appearing on VOD after riots in 1401, and 6. Purchasing VOD subscriptions. These themes reflect diverse views and conversations about Iranian VODs.Using social science computational methods, sentiment analysis, and user surveys, a deeper insight into the social measurement of Iranian VODs is obtained. Sentiment analysis of tweets showed that negative sentiments towards these media among Persian Twitter users were 59%, positive sentiments 39%, and neutral sentiments 2%. In addition, data mining techniques were used to investigate the percentage of attention towards Iranian VODs and the feelings of users towards each of them.

The accurate awareness of the users as the most vital need for media has always been a concern for communication researchers. Given the emergence of new media, traditional techniques no longer have the ability to meet this need, and the use of modern methods is essential in understanding users' behavior. This research used the Social Network Analysis (SNA) technique to investigate the user's behavior of VOD platforms. In this research, the site of Cinemamarket selected as the sample, and a dataset of its user’s purchases formed. Using Gephi software, the dataset visualized and the members clustered based on logical algorithms. By analyzing three detected communities, two different strategies were founded for the development of the users of this platform. Based on these strategies, platform managers can adapt their media policies to load new content on the platform and offer targeted content; as a result, they can meet their user's needs.