Journal of Applied Journalism & Media Studies - Volume 12, Issue 3, 2023

Artificial Intelligence (AI) is being introduced to news routines. There is a need for theoretical framework to instruct the AI-adopting process and better integrate the cross-domain knowledge. This article attempts to explicate the major transformations AI brings to news systems, i.e., automated writing and personalization at scale. In light of the transformations, the tension between AI and human journalists has drawn attention. In order to unravel the accompanied conundrums, we propound a new notion – AI journalism, which is a trans-domain field of various categories, deriving from journalism automation. We propose to build AI journalism ontology that can manifest the emerging phenomenon in news ecosystem where intelligent machines and human journalists are coexisting. This article’s ultimate contribution is proffering a new framework and a transdisciplinary field to examine the integration of AI and associated technologies into journalism.

Television has remained the most prominent and influential form of the Kazakhstani mass media. According to the results of the study under consideration, 98 per cent of all households in the country have at least one television set. In this study, the author analyses data collected during a survey of the Kazakhstani population to assess gender differences relating to their habits of watching TV programmes to estimate levels of their TV consumption and their relationship to television in general. The collected data set also contained information about other related factors such as the administrative status of respondents (rural and urban), their age and occupation in order to identify a more nuanced profile of an average Kazakhstani television viewer.

The purpose of this article is to examine the quality of user comments on the Facebook posts of the Greek Public Broadcasting Corporation (ERT) with a view to acquiring an in-depth understanding of the way the users express themselves publicly. Moreover, the article has looked into which characteristics of the posts prompt the users to comment and whether post time is related to user comments. In all, 2547 user comments recorded on ERT digital platform have been analysed, the majority of which feature negative content. The posts that include a photo have a positive influence on users and result in increased interaction, while the relation between comments and post type is also ascertained.

The World Health Organization named suicide prevention a global imperative with the media playing an integral role in it. By employing the Precaution Adoption Process Model (PAPM) and Agenda-Setting Theory as the theoretical framework, this study aimed to examine the coverage on suicide by The Star, which is an English-language daily with the largest circulation in Malaysia. A five-year (2014–18) range of news coverage was assessed for its adherence to the Malaysian guidelines for media reporting on suicide. The findings showed that the coverage on suicide by The Star was mostly in the form of straight news, whereby articles performed the disseminator role of news media providing facts or quote sources, without including journalists’ interpretation on the suicide incidents. The most common source quoted in the coverage were authorities such as police and government officials. The overall adherence of The Star’s suicide coverage with Malaysian guidelines for media reporting on suicide was mixed. Adherence was adequate (>60 per cent) on some items of the guidelines but extremely low (<18 per cent) for other specific recommendations. The practical implications of the findings are discussed with regard to the implementation and monitoring of media guidelines for suicide reporting, as well as professional education and training of journalists and media–mental health professionals liaison.

The Ebola virus is a rare but often severe and fatal illness in humans. It spreads from animals to humans and then transgresses through human-to-human transmission. The 2014 Ebola virus disease outbreak captured substantial media attention around the world, which is the cornerstone of our study since it can inform us about the current news coverage on the COVID-19 pandemic. This article investigates the media coverage of Ebola in five pairs of English and Arabic international television media outlets (BBC, CNN, SkyNews, RT and France24) by examining the headlines of 298,559 news stories that the respective organizations posted on their official Twitter accounts. Methodologically, we extracted headlines from news outlets that addressed the news on the Ebola virus in two languages: English and Arabic. The media outlets include the following: CNN (English and Arabic), BBC (English and Arabic), SkyNews (English and Arabic), RT (formerly known as Russia Today) (English and Arabic) and France24 (English and Arabic) from late 2013 to early 2015 during which time the Ebola epidemic intensified. We then used descriptive statistics to understand the volume of news coverage and calculate the frequencies, percentages, mean, median and standard deviations for these channels. Further, we continued to model time series regression between the five pairs of news outlets using Granger causality tests. The findings show that over the course of approximately one year’s worth of coverage on these networks, Ebola was mentioned in the headlines of 4138 stories, which constitutes 1.38 per cent of the total news coverage of all media outlets. Building on the theory of intermedia agenda-setting that outlines the ways in which major news organizations influence the agendas of other news outlets, the findings reported here indicate strong, time-ordered patterns where English-language coverage consistently precedes and helps to significantly explain the distribution of Arabic media coverage. In addition to providing evidence of intermedia agenda-setting from a comparative perspective in this context, this article expands on this theory and suggests that it can be applied to multilingual outlets from the same news organizations.