Utilization of Multimedia in Student News Video Projects on Praktik Jurnalistik Media Televisi Course

This article aims to explain the use of multimedia in the form of the kinemaster application in the learning process of making news videos in the Praktik Jurnalistik Media Televisi course. The method used is a descriptive method with a qualitative approach. Data were collected from field findings, participant data, and researcher reflections. Sources of data obtained from direct experience, the results of interviews, observations, and documentation from lecturers who are in charge of the Praktik Jurnalistik Media Televisi course at the Indonesian Language and Literature Education Study Program, STKIP PGRI Sumatera Barat. Based on the findings, the kinemaster application helps students in producing news videos. After the data, news scripts, and voices that have been recorded are complete, they take advantage of this application to combine video, sound and images. This application provides a fairly complete video editing feature and can directly edit it on the spot without having to move to another application. Thus, the use of learning resources in the form of multimedia applications in the Praktik Jurnalistik Media Televisi will increase the effectiveness of learning, so that learning becomes more meaningful for students to get direct experience in the use of technology.

News Video Classification Model Based on ResNet-2 and Transfer Learning

A large amount of useful information is included in the news video, and how to classify the news video information has become an important research topic in the field of multimedia technology. News videos are enormously informative, and employing manual classification methods is too time-consuming and vulnerable to subjective judgment. Therefore, developing an automated news video analysis and retrieval method becomes one of the most important research contents in the current multimedia information system. Therefore, this paper proposes a news video classification model based on ResNet-2 and transfer learning. First, a model-based transfer method was adopted to transfer the commonality knowledge of the pretrained model of the Inception-ResNet-v2 network on ImageNet, and a news video classification model was constructed. Then, a momentum update rule is introduced on the basis of the Adam algorithm, and an improved gradient descent method is proposed in order to obtain an optimal solution of the local minima of the function in the learning process. The experimental results show that the improved Adam algorithm can iteratively update the network weights through the adaptive learning rate to reach the fastest convergence. Compared with other convolutional neural network models, the modified Inception-ResNet-v2 network model achieves 91.47% classification accuracy for common news video datasets.

Coverage of Cultural Issues on the Video Portal Orengrad Open TV Online

The article discussed video news reporting of cultural events on the video portal "Orengrad Oren TV. online". The article analyzed relevant materials that were produced using modern media technologies and public response. The study of the videos revealed the succession between the OREN TV channel and the portal " Orengrad Oren TV. online", which it was transformed into in 2020. Considering various aspects of cultural issues, new media journalists employ the potential of a specific video genre that combines both the features of a television news product and print resources, which distinguishes modern convergent media. The author employed content analysis of news stories to determine what influenced the audience, representatives of the public, and the cultural figures, who adjusted their goals and objectives in accordance with large-scale projects, grant competitions, and creative festivals. The study found that journalists used themed programs to report on the successes and achievements in the area of regional Orenburg culture, whereas the stories that required immediate intervention were covered in brief news video reports.

The effects of constructive television news reporting on prosocial intentions and behavior in children: The role of negative emotions and self-efficacy

To reduce negative emotional responses and to stimulate prosociality, constructive journalism promotes the inclusion of positive emotions and solutions in news. This study experimentally tested whether including those elements indeed increased prosocial intentions and behavior among children, and whether negative emotions and self-efficacy are mediators in this regard. To this end, children (N = 468; 9 to 13 years old) were exposed to an emotion-based, solution-based, or non-constructive news video. Results showed that emotion-based and solution-based news reduced children’s negative emotions compared to non-constructive news. No direct effects for prosocial intentions were found, but solution-based news led to less prosocial behavior (i. e., money donated) than emotion-based and non-constructive news. Moreover, negative emotions served as a mediator, self-efficacy did not. The more negative emotions were elicited by a news story, the higher the prosocial intentions and behavior. In conclusion, a constructive style of reporting helps to reduce children’s negative emotional responses but subsequently hinders prosociality.

Automatic Topics Segmentation for News Video by Clustering of Histogram of Orientation Gradients Faces

TV stream is a major source of multimedia data. The proposed method aims to enable a good exploitation of this source of video by multimedia services social community, and video-sharing platforms In this work, we propose an approach to the automatic topics segmentation of news video. The originality of the approach is the use of Clustering of Histogram of Orientation Gradients (HOG) faces as prior knowledge. This knowledge is modeled as images which governs the structuring of TV stream content. This structuring is carried out on two levels. The first consists in the identification of anchorperson by Single-Linkage Clustering of HOG faces. The second level aims to identify the topics of news program due to the large audience because of the pertinent information they contain. Experiments comparing the proposed technique to similar works were carried out on the TREC Video Retrieval Evaluation (TRECVID) 2003 database. The results show significant improvements to TV news structuring exceeding 96 %.

Children’s Emotions after Exposure to News: Investigating Chat Conversations with Peers as a Coping Strategy

Hardly any research has been conducted regarding coping strategies that children can use in response to negative news, although they are frequently exposed to and emotionally affected by such news. Chat conversations with peers about the news could be a coping strategy for children in this regard. To investigate this, children (N = 307; 46.3% girls; Mage = 10.51; SDage = 0.98; range 8–13 years old) participated in a preregistered experiment in which their emotions were measured before and after exposure to a news video on a smartphone and also after a postexposure activity (i.e., chatting about the news as an experimental condition versus chatting about something else or solving a puzzle as control conditions). The results showed that the decrease in negative emotions and the increase in positive emotions were weaker for children who chatted about the news than for those in the control conditions. Thus, seeking social support in online chat conversations did not have the anticipated effect—and might even have an adverse effect.