Data Analysis Method of Intelligent Analysis Platform for Big Data of Film and Television

Based on cloud computing and statistics theory, this paper proposes a reasonable analysis method for big data of film and television. The method selects Hadoop open source cloud platform as the basis, combines the MapReduce distributed programming model and HDFS distributed file storage system and other key cloud computing technologies. In order to cope with different data processing needs of film and television industry, association analysis, cluster analysis, factor analysis, and K-mean + association analysis algorithm training model were applied to model, process, and analyze the full data of film and TV series. According to the film type, producer, production region, investment, box office, audience rating, network score, audience group, and other factors, the film and television data in recent years are analyzed and studied. Based on the study of the impact of each attribute of film and television drama on film box office and TV audience rating, it is committed to the prediction of film and television industry and constantly verifies and improves the algorithm model.

Analysis on the Countermeasure of China’s IP Drama Importing to Vietnam under the New Media Environment

With the arrival of the new media era and the continuous development of China’s domestic IP dramas, the downturn in domestic TV dramas has been broken, more and more IP dramas obtain higher audience rating rely on the Internet, and it becomes a phenomenon hot style. Vietnam is geographically adjacent to China, and they have similar cultures. A lot of Vietnamese culture is derived from Chinese culture, and they are heavily influenced by the values and lifestyle of Confucius in the past, Chinese film and television is a literary genre familiar to Vietnamese, which is one of the most important components of daily entertainment. This paper will research on how to use the Internet to strengthen the import of film and television culture to Vietnam, so that Chinese IP dramas can also increase the audience rating in Vietnam and enhance the cultural export.

DETERMINING FACTORS OF CZECH FILM ATTENDANCE IN THE YEARS 2003–2017

The paper analyzes the determining factors affecting Czech film attendance in the years 2003–2017 and places this topic into the context of the information asymmetry faced by film-goers. Using the regression (OLS) model and a unique population-level dataset (415 observations), the hypothesis of a positive relationship between film attendance and audience rating is confirmed. The increase in audience ratings by Czech-Slovak Film Database website’s users by one percentage point is, ceteris paribus, associated with an increase in attendance by 1.8%. Factors which have proven to determine film attendance also include: specific genres; film sequels; casting of a popular actor, actress or director; the personality of the director Zdeněk Troška; the Czech Lion Awards; and a premiere in certain years. In the decision-making process of a viewer who faces information asymmetry one can rely on these determinants as economic signals and on viewer ratings as information from an intermediary.

Evaluation of news communication effect based on cognitive neuroscience

Based on the development of cognitive neuroscience and communication science at home and abroad, this study introduces the application of cognitive neuroscience experiments in communication researches at home and abroad, including the research and application of communication effects in advertising, picture, video, web design and animation culture. This study discusses the important significance of relevant frontier achievements to the development of news communication science. The rise of cognitive neuroscience provides a new perspective for understanding the psychological cognitive mechanism of the audience and optimizing the communication effect of service media. On the basis of introducing the status quo of cognitive neuroscience in audience rating evaluation of news broadcast, this study introduces the advantages and functions of this method in audience rating evaluation of news broadcast with eye movement experiment as an example, which provides a new method and empirical case for seeking audience rating evaluation of news broadcast.

Prediction of Television Audience Rating Based on Fuzzy Cognitive Maps with Forward Stepwise Regression

The television audience rating is an important indicator of the quality of television programs and important reference for decision-television operator. As many factors that affect the ratings and the trends are complex, the article proposes a television rating mining predictive model based on fuzzy cognitive maps (FCMs) with forward stepwise regression. The FCMs use the causal relationship among various concept nodes to simulate the fuzzy reasoning, and enhance the dynamic behavior of the simulation system with its feedback mechanism, which is suitable for system to predict the trend of television audience rating. A FCM-based model for predicting television audience rating is proposed in this paper. The forward stepwise regression algorithm is used to obtain concept nodes of coarse weight matrix for FCMs, and then a training weight algorithm is used to refine the coarse weight matrix model. The FCM model is applied to mine the television audience rating, realizing to predict the television playback volume. The experimental result shows that the modeling method is effective.

The Impact of the Soccer Schedule on TV Viewership and Stadium Attendance

In the past decade, television (TV) broadcasters have been investing a huge amount of money for the Belgian Pro League broadcasting rights. These companies pursue an audience rating maximization, which depends heavily on the schedule of the league matches. At the same time, clubs try to maximize their home attendance and find themselves affected by the schedule as well. Our article aims to capture the Belgian soccer fans’ preferences with respect to scheduling options, both for watching matches on TV and in the stadium. We carried out a discrete choice experiment using an online survey questionnaire distributed on a national scale. The choice sets are based on three match characteristics: month, kickoff time, and quality of the opponent. The first part of this survey concerns TV broadcasting aspects. The second part includes questions about stadium attendance. The choice data are first analyzed with a conditional logit model which assumes homogenous preferences. Then a mixed logit model is fit to model the heterogeneity among the fans. The estimates are used to calculate the expected utility of watching a Belgian Pro League match for every possible setting, either on TV or in the stadium. These predictions are validated in terms of the real audience rating and home attendance data. Our results can be used to improve the scheduling process of the Belgian Pro League in order to persuade more fans to watch the matches on TV or in a stadium.