Online Video Services Research Articles

“Strike with visual bullets”: Digitalized deep play and floating emotional public sphere in the Bilibili bullet comments

The bullet comment refers to a real-time built-in comment system attached to online video services on the Chinese Internet. It provides a mechanism transforming online spectatorship into an “audiencing” experience. This study interviews 16 bullet comment users to explore the digital media practices in bullet comments. We argue that the “audiencing” subjects are involved as players in the imagined communities through emotional invitations, implicit cultural “contract,” and diverse textual hijacking strategies. It is a digitalized subject deep play with the stake of cultural interpretation mastery. Based on space discourse deep play, the bullet comment forms a floating emotional public sphere through the flexible technological infrastructure, sustained subject involvement mechanisms, adaptable playing strategies, and a strategic discourse evolution. Its openness helps youth generate a sense of place to express their subjectivities in response to social pressures and paternalistic rhetoric in an alternative manner. This study provides a new perspective on the Chinese youth culture and online public sphere research.

How does OTT social viewing relieve pandemic-related depressive symptoms? Investigating the moderated mediation model of social connectedness and network types

ABSTRACT After the outbreak of COVID-19, people have lacked offline social opportunities and had to focus their energy on online social activities. While some researchers have proposed that both anxiety and depression have increased significantly during the COVID-19 pandemic, previous studies have provided evidence that people have mitigated negative emotions during the health crisis by using online services. In this manner, the pandemic-induced increase in online activity has significantly boosted global demand for online video services (Over-the-Top, OTT). OTT social viewing refers to the act of interacting with other users while simultaneously watching content through the social viewing service provided by OTT service providers. Drawing on the social compensation hypothesis and social capital theory, we surveyed people who experienced COVID-19-related depression and used Watch party, a key OTT social viewing service in Korea. The study reveals that while social media alone did not directly alleviate COVID-19-related depression, emotional stability was regained through building social connectedness via online activities. Furthermore, the study highlights that in OTT social viewing, the quality of interactions, rather than the quantity, was more crucial for forming social connectedness.

Future-proofing entertainment: Navigating market changes in television and internet video services through predictive modeling

This research investigates the further prospects of TV and internet video services in the dynamic Yemen market by analyzing the factors that influence their use and engagement. This research expands its framework by including the combined concept of absorption and employ of technologies, and the idea of technology disruptions and systems improvement adding an entertaining bend to the analysis. Its purpose is to investigate the connection between the intention to use and the behaviour of interacting with the material. The research subjects were answered by a group of 400 academic graduates. In contrast to previous studies, this study discovered that only the Perceived Ease of Use (PES) is effectively connected with the desire to use online video services. However, it also revealed a significant optimistic connection between customer quality Online Flow Experience (OFE), Perceived Behavioral Control (PBO), and Instrumental Orientation (IR), the purpose to employ internet video services. Findings indicate a decline in TV viewership, while the limited amount of available money may pose a significant obstacle to the expansion of video platforms. This study provides vital insights into the evolving consumer behavior inside Yeman's media network at a period of minimal investigation.

IMPLEMENTATION OF CUSTOMER RELATIONSHIP MANAGEMENT BASED OF ARTIFICIAL INTELLIGENCE IN THE DHARMA BOOST MARKETING PROGRAM

Dharma Mitra Abadi is a leader in the DIY and Central Java regions which uses the best branded tools, continues to maintain and develop the quality of its services. Committed with PT. Abbott with the best brand diagnostic tools, until appointed as the sole agent. PT. Dharma Mitra Abadi is a medical device company that utilizes direct marketing to promote its products. The company has implemented the Dharma Boost program, which utilizes digital media and e-commerce tools such as online electronic applications, websites, mobile applications, social media, animation, video, data visualization, and location-based services. This research aims to evaluate and improve the effectiveness of these existing programs within the company. The research method used is qualitative, including direct observation, in-depth interviews, collection of documentation, and analysis of company secondary data. The research is being conducted within the marketing division of the company. The goal is to help the company innovate and address any marketing challenges. By incorporating Artificial Intelligence into its Customer Relationship Management, PT. Dharma Mitra Abadi hopes to optimize its use of digital marketing.

Robust Anomaly Clue Localization of Multi-Dimensional Derived Measure for Online Video Services

Anomaly clue localization of multi-dimensional derived measure is vitally important for the reliability of online video services. In this paper, we propose RobustSpot, an end-to-end framework for localizing the clues to anomalous multi-dimensional derived measures. RobustSpot integrates two novel indicators, i.e., “Anomaly Degree” and “Contribution Ability”, with a simple yet effective method, weighted association rule mining (WARM), to automatically mine the hidden relationships across data dimensions for localizing the most likely clues to the root cause. Using 135 real-world cases collected from a top-tier global online video service provider <inline-formula><tex-math notation="LaTeX">$H$</tex-math></inline-formula> with 170+ million monthly active users, we demonstrate that RobustSpot achieves high accuracy (Top-5 accuracy of 98%), significantly outperforming state-of-the-art methods. The average localization time of RobustSpot is 1.83s, which is satisfying in our scenario. We have open-sourced the implementation of RobustSpot as well as the data used in the evaluation experiments.

Research on the flow experience and social influences of users of short online videos. A case study of DouYin

Recently, short online videos have been highly recognized by video market users and have developed rapidly. This study aims to explore why users enjoy watching and sharing short online videos by applying the theory of flow experience. Previous research has extensively examined traditional video arts such as TV and movies and text or image based, while research on short online videos has increased only in recent years. To improve the precision and comprehensiveness of the research, social influence is also used as a variable. This study takes the short video representative platform DouYin as a case study and the Chinese user market as the background. Through questionnaires, 406 users' data about short online video experiences were collected. After statistical analysis, the study finds that flow experience has a significant impact on participative behaviour and sharing behaviour for short online videos. According to further analyses, the flow experience, social norms, perceived critical mass and participative and sharing behaviour constitute three groups of mediating relationships. Finally, the discussion of the research results provides help to broaden the academic scope of the flow experience and video art, improve the short online video platform environment, and upgrade short online video services.

Sweet Streams Are Made of This: The System Engineer’s View on Energy Efficiency in Video Communications [Feature

In recent years, the global use of online video services has increased rapidly. Today, a manifold of applications, such as video streaming, video conferencing, live broadcasting, and social networks, make use of this technology. A recent study found that the development and the success of these services had as a consequence that, nowadays, more than 1% of the global greenhouse-gas emissions are related to online video, with growth rates close to 10% per year. This article reviews the latest findings concerning energy consumption of online video from the system engineer’s perspective, where the system engineer is the designer and operator of a typical online video service. We discuss all relevant energy sinks, highlight dependencies with quality-of-service variables as well as video properties, review energy consumption models for different devices from the literature, and aggregate these existing models into a global model for the overall energy consumption of a generic online video service. Analyzing this model and its implications, we find that end-user devices and video encoding have the largest potential for energy savings. Finally, we provide an overview of recent advances in energy efficiency improvement for video streaming and propose future research directions for energy-efficient video streaming services.

Semantic Relevance Learning for Video-Query Based Video Moment Retrieval

The task of video-query based video moment retrieval (VQ-VMR) aims to localize the segment in the reference video, which matches semantically with a short query video. This is a challenging task due to the rapid expansion and massive growth of online video services. With accurate retrieval of the target moment, we propose a new metric to effectively assess the semantic relevance between the query video and segments in the reference video. We also develop a new VQ-VMR framework to discover the intrinsic semantic relevance between a pair of input videos. It comprises two key components: a Fine-grained Feature Interaction (FFI) module and a Semantic Relevance Measurement (SRM) module. Together they can effectively deal with both the spatial and temporal dimensions of videos. First, the FFI module computes the semantic similarity between videos at a local frame level, mainly considering the spatial information in the videos. Subsequently, the SRM module learns the similarity between videos from a global perspective, taking into account the temporal information. We have conducted extensive experiments on two key datasets which demonstrate noticeable improvements of the proposed approach over the state-of-the-art methods.

Bandwidth Allocation to Traffic and QoE Evaluation for Video Streaming Services

Video streaming is one of the most popular and highest bandwidth-consuming media on the internet. However, network bandwidth is a limited and costly resource. Therefore, usage should be managed well in order to optimize the management of available bandwidth resources. In this work, it is proposed to evaluate the traffic of online streaming applications in a bandwidth-constrained environment by testing the performance of Disney+, Netflix, and YouTube websites. The experiment has been done with both unlimited and limited bandwidth. The experiment has displayed protocol types, and data size, has measured QoS including throughput, delay, packet loss, and jitter of online video services, and it has compared the aforementioned elements with TIPHON standard specification. As a result, when the bandwidth has been limited, it has been found out that throughput has been in a bad range. This study recommends a bandwidth limitation of 2 Mbps for the greatest results for effective bandwidth usage. The importance of evaluating user satisfaction with service providers has been considered by measuring QoE levels using an individual rating or MOS for assessing the quality of video streams. This research has provided a guideline for managing the available bandwidth resources for the optimized benefit of all ISPs and users. This is a cost-effective and efficient use of bandwidth resources.

The shift in media consumption in Russia: overview of trends 2016-2021

The Internet has become omnipresent in Russia due to the mass accessibility of smartphones. Paired with the fact that the representatives of the digital generation are reaching adulthood, the significant changes in media consumption have occurred over the past five years. It can be stated that progressive quantitative transformations have turned into a qualitative digital shift. The use of digital media is growing: the use of messengers in almost all age groups, social networks, search engines, online video services surpasses traditional media. In 2021, digital platforms took the top eight places in the ranking of media platforms by audience in Russia. At the same time, there is a decrease in TV viewing, the fragmentation of the audience is growing, and the YouTube has become the most popular video service in the country. Interest in reading newspapers, magazines, listening to radio is falling. In terms of the importance of news sources and trust in them, the Internet surpasses TV in all audiences. The study provides statistics that have not been published before. A comprehensive analysis of the identified trends in the development of digital media allowed to draw a conceptual conclusion about the qualitative shift in media consumption in Russia between 2016 and 2021: this timeframe is marked for the first time.

Development and analysis of models for service migration to the MEC server based on hysteresis approach

Online video services are among the most popular ways of content consumption. Video hosting servers have a very high load every day, which we propose to reduce by migrating the application with the video content in demand to the local Multi-access Edge Computing (MEC) server of the target. This makes it possible to improve the quality of services (QoS) provided to users by reducing the transmission delay. Therefore, an architecture has been proposed that allows, at times of increased demand for the same video content, to migrate the video service application to the edge servers of the network operator. To evaluate the performance of this approach, a mathematical model was developed in the form of a queuing system. The results of the numerical experiment make it possible to optimize the time of using local MEC servers to provide video content.

Efficient incentive mechanism for video distribution on the home Internet of Things devices

Providing users with nearby video distribution services based on Edge Computing (EC) reduces backbone traffic and improves users' viewing experience. However, the behavior of edge networks is difficult to manage and cannot guarantee the rationality of video resource distribution, which has become a significant challenge for online video services. This paper takes the idle resources from home Internet of Things (IoT) devices for video distribution service as the research point. It proposes an incentive mechanism based on behavior management and balance of resources (BMBR). By paying attention to the rationality of resource distribution and establishing reasonable reward and punishment measures for edge devices, the incentive mechanism makes the initiative of edge devices and the relationship between resource supply and demand reach a stable equilibrium. Simulation results and analysis show that the incentive mechanism can effectively improve the enthusiasm for resource sharing in the edge network, ensure the rationality of resource distribution to reduce the resource price fluctuations, and maintain the balance of resource supply and demand.

What Likeability Attributes Attract People to Watch Online Video Advertisements?

As online video viewing increases, so does the size of the online video advertising market. However, it is challenging to create an advertising creative suitable for online video services. Advertising likeability helps to provide the strategies necessary for producing video advertisements that can facilitate consumer responsiveness and generate persuasive effects. Therefore, this study aimed to identify the likeability attributes of online video advertising content that increase online video advertisement views and to validate them with actual user data. To achieve this objective, this study applied a mixed-methods approach using two studies. The first study was an exploratory study in which users’ reviews on recently popular online video advertisements were analyzed through text mining, after which we identified key likeability attributes. We then conducted a focus group discussion method to measure the degree of video ads in each attribute. The second study was a confirmatory study, in which the key likeability attributes identified in the first study were verified empirically through an econometric model. As a result, we derived six likeability attributes of online video advertisements. The findings also highlight the effects of music, storytelling, influential people, and novel ideas on the number of views. Altogether, our study offers practical insights into which factors and identified likeability attributes enable effective online video advertisements.

Beyond Global Youth Culture: A Cross-National Comparison of YouTube Usage across the United States, Saudi Arabia, and Taiwan

ABSTRACT This paper examines the differences and similarities among three major YouTube markets (U.S.A., Saudi Arabia, and Taiwan) that are culturally very different to test the media globalization and global youth culture thesis and how national cultural values affect YouTube use. Hofstede’s cultural dimension framework was employed to explain the cultural differences in affecting the use of video genres and activities on YouTube. We found more differences than similarities among the U.S., Saudi Arabia, and Taiwan in program genre viewership and activities on YouTubes. Gender difference in program genre viewership was largest in Saudi Arabia with highest power distance and second highest in masculinity. Saudi Arabia also scored highest in engagement activities on YouTube. The results of this study enable media managers and global marketers to develop strategies to provide online video services and utilize YouTube for promotion and underscore the importance of developing recommendation algorithms and other popularity indexes such as the trending page.

More collaboration, less seriousness: Investigating new strategies for promoting youth engagement in government-generated videos during the COVID-19 pandemic in China

Effectively engaging citizens during crises is critical for governments to disseminate timely information and help the public to adjust to the constantly changing conditions. In particular, promoting youth engagement not only enhances crisis awareness and resilience among the young generation, but also has a positive impact on youths' social participation and responsibility. With the increasing popularity of online video services, leveraging online videos to disseminate authoritative information has become a method widely adopted by government. To enhance youth awareness and engagement, two new video-based crisis communication strategies have been utilized on a popular youth-targeted video platform Bilibili in China: creating recreational videos such as animation and music videos, and collaborating with individual video-uploaders in video making. However, their impacts and results are largely unknown, which motivates our study. Guided by Entertainment Education (EE) and Collaborative Governance (CG), we report, to our best knowledge, the first systematic study on how recreational video category and government-citizen collaboration would influence youth engagement focusing on 3347 COVID-19-related government-generated videos on Bilibili. This study reveals that recreational videos successfully promote youth engagement including interaction, feedback and sharing. Collaboration with individual uploaders in video making also has a substantially positive impact on youth engagement. Through an in-depth qualitative content analysis of user-generated commentaries, we further unpacked the unique values (e.g., trust work for youth participation) as well as latent limitations (e.g., imbalanced topic distribution) of the two new strategies. We discuss how the findings enrich EE and CG theoretically, and provide practical implications to effective and engaging communication strategies during crises.

Attitudes of Young Consumers in Chiang Mai, Thailand toward YouTube Online Video and Audio Advertising

Abstract With the increased use of the Internet, online audio and video are becoming more and more popular. The operating income of those websites providing online audio and video services is mainly from advertising. Therefore, not only advertisers need to care about the importance of the user' attitude toward advertising, but also the providers of online audio-visual service websites should understand it. This study focused on the attitude toward advertising of young consumers in Chiang Mai, Thailand, when they watch online audio-visual videos on YouTube, and explored their buying behaviors. The study found that entertainment, informativeness and credibility had a strong positive correlation with the attitude toward YouTube advertising, while irritability had a negative correlation. Based on the results of the analysis, this study provided future research directions for the academic community and the industry, as well as references for formulating business strategies and future development. JEL classification numbers: M31, M37. Keywords: Online audio-visual services, Attitude toward advertising, Buying behavior.

온라인 동영상 서비스의 혐오표현 콘텐츠 이용 경험과 규제 인식이 이용과 지속 이용 의도에 미치는 영향

The purpose of this study is to analyze the perception of major online video service users of hate speech concepts, hate speech content usage experiences, and regulations. It conducted an online survey of 520 users of YouTube, Instagram and TikTok. As a result of the analysis, the level of awareness of self-regulation was high for hate expression regulations. This could be used as a basis for understanding hate speech from the perspective of using online video services and for planning regulatory policies at the service provider and government level. This study is an exploratory study of the relationship between hate speech and service use of online video services. Unlike previous studies focused on legal discussions and fact-finding surveys on hate speech, we analyzed hate speech concepts, regulatory directions from the perspective of users. It is expected to refer to policies and regulations to minimize hate speech on online video service.

A New Parameterized Model for Determining Quality of Online Video Service Using Modern H.265/HEVC and VP9 Codecs

This paper describes a new measurement method (VS model) for determining the quality of online video services relying on modern H.265/HEVC and VP9 codecs. The said method has been developed on the basis of VQuad-HD curves (according to ITU-T J.341). This model does not refer to signal analysis, but protocol analysis instead. The parameters used are: type of video codec, encoding rate, transport technique, packet loss and burst size. The method may be implemented quickly and easily, which is one of the great advantages when using this method to measure QoS.

온라인동영상서비스(OTT)의 동영상 특성, 콘텐츠 특성 및 혁신확산 특성이 시청자의 시청태도에 미치는 영향 분석

온라인동영상서비스(OTT)의 동영상 특성, 콘텐츠 특성 및 혁신확산 특성이 시청자의 시청태도에 미치는 영향 분석

DQAMLearn: Device and QoE-Aware Adaptive Multimedia Mobile Learning Framework

With the proliferation of mobile devices and online video services, mobile learning has grown both in popularity and complexity. New challenges include the multitude of mobile devices with different characteristics and limitations, as well as the exponential growth in educational multimedia content. Streaming multimedia content to mobile devices is a resource intensive task that requires significant resources such as network bandwidth, with demand expected to increase beyond future networks capacity as users adopt new technologies such as UHD, AR, VR, 3D and 360-degree video. While a number of adaptive m-learning systems have been previously proposed, none of these have thoroughly addressed the adaptation of educational multimedia content. This article proposes the novel DQAMLearn framework that aims to support mobile learner’s seamless access to educational multimedia content from a variety of mobile devices with different characteristics. Moreover, as mobile users are increasingly becoming quality-aware, the framework integrates novel mechanisms for decreasing the video quality in a controlled way, with the aim to support a good learner quality of experience (QoE) even in resource constrained situations. A comprehensive subjective study was conducted to evaluate the proposed framework. The results showed that the framework enables both high learning achievement from educational multimedia clips, with 12% and 83% correct response rates for pre and post-test questionnaires, respectively, and high learner QoE with a mean video quality rating of 79.19 on a 0–100 acceptability scale.