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Broadcasting Hollywood: The Struggle Over Feature Films on Early Television uses extensive archival research into the files of studios, networks, advertising agencies, unions and guilds, theatre associations, the FCC, and key legal cases to analyze the tensions and synergies between the film and television industries in the early years of television. This analysis of the case study of the struggle over Hollywood’s feature films appearing on television in the 1940s and 1950s illustrates that the notion of  an  industry misunderstands the complex array of stakeholders who work in and profit from a media sector, and models a variegated examination of the history of media industries. Ultimately, it draws a parallel to the contemporary period and the introduction of digital media to highlight the fact that history repeats itself and can therefore play a key role in helping media industry scholars and practitioners to understand and navigate contemporary industrial phenomena.

Organizers of major sports events regularly report impressive multibillion TV audiences to emphasize the success of their competitions, yet such claims are seldom substantiated with hard evidence, nor is it usually made clear what the numbers actually stand for. The aim of this paper is to provide a better insight into the ambiguity of reported audience sizes for sports events and to beg the question: What is the TV audience size for a live sports broadcast? By detailing seven pitfalls, we critically discuss the problems associated with a correct understanding of TV audiences for live sports broadcasts. We substantiate our findings with specific examples for various sports events. The paper demonstrates the relevance of a correct understanding of how TV audiences for sports broadcasts are determined and communicated, and the analysis of the pitfalls uncovers misunderstandings about reported TV audiences that have been largely ignored before. We also discuss the relevance of our insights for the growing body of academic literature in this field.

This study analyzes the performance of the main news programs of the five largest television channels in Romania: TVR1, PRO TV, Antena 1, Kanal D, and Prima TV. By examining monthly average ratings over a five-year period (2018-2022), the study identifies key trends and performance disparities between these channels. The results highlight significant differences in the performance of TVR1's Telejurnal compared to its commercial competitors. While Telejurnal demonstrates stability with a loyal but relatively small audience, commercial channels like PRO TV, Antena 1, and Kanal D exhibit higher variability and significantly higher mean ratings, reflecting their ability to attract diverse and dynamic audiences. Seasonal patterns in Telejurnal's ratings reveal higher viewership in winter months, with declines in summer, but the overall trend remains stationary. These findings suggest that TVR1 operates in a distinct niche but faces significant challenges in competing with commercial channels.

PurposeSocial media (e.g., e-WOM) and traditional media (e.g., media coverage) serve different roles in a firm's marketing activities and also interact with each other, which in turn affect the market outcome. In addition, how market outcome affects the two types of media in turn has not been examined, which brings the need for a holistic framework. The rare study that examines this relation mostly relies on the volume of media rather than the valence. This study examines the interdependent relation between the volume and valence of social media, the volume of traditional media and TV ratings.Design/methodology/approachForty-one South Korean TV drama shows from October 2014 to March 2016 were analyzed using the 3SLS estimation to examine the interdependent relation between the variables.FindingsFirst, the volume of traditional media has a negative effect on the volume of social media. Second, ratings negatively affect the valence of social media. Third, the volume of traditional media is found to have a negative effect on ratings. This is explained by the displacement effect.Originality/valueThis study is one of the very few studies that examine the interdependent relation between various earned media and market outcomes in one framework. In addition, it has originality in that it considers the valence of social media, which is an important dimension in analyzing earned media. Our results show negative effects of news media on TV ratings and e-WOM, which diverge from common intuition.

Purpose The purpose of this paper is to investigate the relation between average ratings (viewership) and the volume and valence of electronic word of mouth (e-WOM) for early episodes of TV shows. Design/methodology/approach Linear regression was performed in which the dependent variable is average TV ratings and main independent variables are volume and valence of e-WOM. The study used a Breusch–Pagan test to detect heteroscedasticity. Accordingly, the model is analyzed using heteroscedasticity-consistent standard error estimators. Findings The results show that the volume of the early e-WOM does not significantly contribute to explaining average ratings, but the valence does. Originality/value Because the advertising revenue of television broadcasters is determined according to expected TV ratings, the average ratings should be predicted as early as possible. This study shows that analyzing early e-WOM helps predict average ratings.

Ridge regression is a biased estimated regressive method, which is traditionally used in collinearity data analysis. It is actually a modified Least Square method, which gains more rational and reliable regression coefficient by giving up the unbiasedness of Least Squares Estimation, reducing partial information and decreasing accuracy to overcome the over-fitting problems. This article presents an improved ridge regression algorithm and utilizes it to predict the audience rating for TV ratings. It is tested by 10 - fold Cross Validation. TV rating is an important indication to measure the quality and user experience, as well as one of the vital standards to state the value of a TV channel. The improved ridge regression algorithm is used to learn the model of weight matrix, which is trained by the error algorithm to predict the TV ratings. The extensive experimental results demonstrate the effectiveness of the proposed algorithm.

The purpose of this study is to control the ratio of programs of different genres when forming the broadcast grid in order to increase and maintain the rating of a channel. In the multichannel environment, television rating controls consist of selecting content, the ratings of which are completely restored after advertising. The hybrid approach to rule set refinement based on fuzzy relational calculus simplifies the process of expert recommendation systems construction. By analogy with the problem of the inverted pendulum control, the managerial actions aim to retain the balance between the fuzzy demand and supply. The increase or decrease trends of the demand and supply are described by primary fuzzy relations. The rule-based solutions of fuzzy relational equations connect significance measures of the primary fuzzy terms. Program set refinement by solving fuzzy relational equations allows avoiding procedures of content-based selective filtering. The solution set generation corresponds to the granulation of television time, where each solution represents the time slot and the granulated rating of the content. In automated media planning, generation of the weekly TV program in the form of the granular solution provides the decrease of time needed for the programming of the channel broadcast grid.

The current study examined the optimal period length using wavelet analysis assuming that TV audience ratings are indicators of field intensity that affects field random number generator (RNG) outputs. As TV programs around the New Year often have high ratings, we focused on these programs in 2012 in Japan. Using Psyleron, Rpg102, and Orion as physical RNG devices, the sum of squares of RNG outputs during 288 selected programs were decomposed into multiple levels from periods of 250 ms to 256 s through a Haar wavelet filter. Unexpectedly, the wavelet filter could not find sensitive periods, whereas an ANCOVA suggested that Rpg102 might detect audience rating effects over almost the whole range of wavelengths. Psyleron and Orion devices showed null results. These results suggest that RNG behavior cannot be described by physical signal modeling. There is a possibility of canceling effects in RNG outputs, and this may be a subject for a future study.

藉由台灣電視節目收視率、台股成交量與台股波動性的資料，本文利用Hausman（1978）檢定指出成交量為自變數來解釋股市波動的內生問題。我們可以用兩階段的工具變數法來克服這個問題並得到具一致性的估計結果。在工具變數的選取上，我們首度嘗試以「財經資訊分析」和「新聞播報節目」的收視率為候選變數，依據Stock and Watson（2003, p. 371）和Stock and Yogo（2005）所建議的準則，確認「財經資訊分析」的收視率為強工具變數；「新聞播報節目」的收視率為弱工具變數。接著，再以Sargan（1958）的外生性檢定確認「財經資訊分析」的收視率的外生性。本研究的工具變數法的估計結果顯示，成交量所帶動的股市波動遠大於以最小平方法所估得的結果。根據這樣的結果，本研究進一步模擬投資人在觀察到「財經資訊分析」的收視率以後，對股市的波動形成一致性的預期，並且透過台指選擇權的操作，形成一種可能的獲利空間。

PurposeThis study aims to examine entertainment TV shows' social media accounts to theoretically and practically explore the relationship between social media engagement and the performance (represented by ratings) of such shows.Design/methodology/approachBy using the data of a popular TV show in the USA, The Voice, the present study examined the messages on the Facebook fan page of the show and how these messages correlated with the ratings of the show. Social media usage data in the course of three seasons (Seasons 10–12, 82 episodes in total) were collected from Facebook (N = 1,192,722 messages). Both regression and sentiment analysis were performed.FindingsOverall, the findings revealed positive relationships of TV show ratings with both passive social media engagement (Facebook likes) and the number of official posts. However, active social media engagement was not positively related to show ratings.Originality/valueBy enhancing understanding of audience engagement with social media, our research extends knowledge related to the nature and development of viewer involvement with entertainment across different media platforms. Our results also help clarify how interpersonal communication (social media comments) and mass communication (TV programs) intersect. Practically, the findings could be applied to improve the interaction of TV audiences with show content, provide insights into the future of social TV development and inform decision-making amongst TV industry professionals.