• The Journal of Information Systems
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• v.32 no.4
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• pp.29-50
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• 2023

Purpose The impact of online reviews is widely acknowledged, with extensive research focused on text-based reviews. However, there's a lack of research regarding reviews in video format. To address this gap, this study aims to explore the connection between company-sponsored product review videos and the extent of directive speech within them. This article analyzed viewer sentiments expressed in video comments based on the level of directive speech used by the presenter. Design/methodology/approach This study involved analyzing speech acts in review videos based on sponsorship and examining consumer reactions through sentiment analysis of comments. We used Speech Act theory to perform the analysis. Findings YouTubers who receive company sponsorship for review videos tend to employ more directive speech. Furthermore, this increased use of directive speech is associated with a higher occurrence of negative consumer comments. This study's outcomes are valuable for the realm of user-generated content and natural language processing, offering practical insights for YouTube marketing strategies.

• Asia pacific journal of information systems
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• v.25 no.4
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• pp.763-783
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• 2015

Online customer reviews (i.e., electronic word-of-mouth) has gained considerable interest over the past years. However, a knowledge gap exists in explaining the mechanisms among the factors that determine the product sales in online retailing environment. To fill the gap, this study adopts a principal-agent perspective to investigate the effect of customer reviews and customer incentives on product sales in online retail stores. Two customer review factors (i.e., average review ratings and the number of reviews) and two customer incentive factors (i.e., price discounts and special shipping offers) are used to predict product sales in regression analysis. The sales ranking data collected from the video game titles at Amazon.com are used to analyze the direct effects of the four factors and the interaction effects between customer review and customer incentive factors to product sales. Result reveals that most relationships exist as hypothesized. The findings support both the direct and interaction effects of customer reviews and incentive factors on product sales. Based on the findings, discussions are provided with regard to the academic and practical contributions.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.140-146
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• 2023

A detailed survey, applications and challenges of video encoding-decoding systems is discussed in this paper. A novel architecture has also been set aside for future work in the same direction. The literature reviews span the years 1960 to the present, highlighting the benchmark methods proposed by notable academics in the field of video compression. The timeline used to illustrate the review is divided into three sections. Classical methods, conventional heuristic methods, and current deep learning algorithms are all used for video compression in these categories. The milestone contributions are discussed for each category. The methods are summarized in various tables, along with their benefits and drawbacks. The summary also includes some comments regarding specific approaches. Existing studies' shortcomings are thoroughly described, allowing potential researchers to plot a course for future research. Finally, a closing note is made, as well as future work in the same direction.

• Archives of design research
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• v.17 no.3
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• pp.373-382
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• 2004

Video protocol analysis is a popular and effective technique in many research disciplines including industrial design and HCI for understanding the interactions between people, and between people and machines. Analysing and transcribing video recordings is, however, notoriously time consuming, and a variety of single-user computer based tools have been developed to ease the task. This paper examines collaborative video analysis. The motivation for groupware tools for video analysis is described, and the desirable features of such tools are identified. The following section reviews related work on video analysis and on single-user video analysis tools. The review is used to derive a set of design goals for collaborative video analysis tools. We then detail prototype's user interface, its collaborative facilities, and its implementation. The preliminary evaluation is described prior the conclusions which identify directions for further work.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.375-388
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• 2021

This study aims to contribute to the understanding of consumer behavior during the COVID-19 by comparing blog reviews of an over-the-top (OTT) online video service from before and during the pandemic. We anticipate that the COVID-19 outbreak prompts the use of the OTT service as part of an emotion-focused coping strategy derived from the loss of personal control and the subsequent avoidance motivation. We also posit that a strong yearning for life before COVID-19 will increase interest in the content that fulfills a need for nostalgia. Our analysis of Netflix reviews provides empirical evidence of the effects of an emotion-focused coping strategy and nostalgia on OTT service usage. First, the titles of the reviews posted during COVID-19 indicate that consumers were less likely to mention OTT services other than Netflix, more interested in domestic content, and used OTT services as an avoidance-denial strategy. Second, the blog content demonstrates that while pre-COVID reviews tend to focus on the practical benefits of OTT services, those posted during the pandemic focus on mood, emotions, and dialogue. In addition, interest in comedy and romance genres increased during COVID-19. Third, we identified a greater preference for realistic or everyday content that depicted the pre-pandemic era. This is the first empirical study to investigate the effects of COVID-19 on video streaming usage in Korea. In addition, this research contributes to the field of marketing by expanding our understanding of online video service users during COVID-19 and identifies practical implications for OTT services in the midst of a pandemic.

• The Journal of the Korea Contents Association
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• v.16 no.5
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• pp.137-147
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• 2016

The Online video content service developed into one of the most popular network service of internet and mobile users. The number of online video content distributors are rapidly increasing in China. But, at present, Online video content distributors in china has the following problems: severe similar content, copyright infringement issue and profit model absence. The purpose of this study is to analyze the development of these distributors, especially YoukuTudou and iQiyiPPS. This study also reviews the stage of development and current situation of online video content market in china.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.2_2
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• pp.445-456
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• 2024

This study aims to suggest service improvement opportunities by analyzing user review data of the top three OTT service apps(Netflix, Coupang Play, and TVING) on Google Play Store. To achieve this objective, we proposed a framework for uncovering service opportunities through the analysis of negative user reviews from OTT service providers. The framework involves automating the labeling of identified topics and generating service improvement opportunities using topic modeling and prompt engineering, leveraging GPT-4, a generative AI model. Consequently, we pinpointed five dissatisfaction topics for Netflix and TVING, and nine for Coupang Play. Common issues include "video playback errors", "app installation and update errors", "subscription and payment" problems, and concerns regarding "content quality". The commonly identified service enhancement opportunities include "enhancing and diversifying content quality". "optimizing video quality and data usage", "ensuring compatibility with external devices", and "streamlining payment and cancellation processes". In contrast to prior research, this study introduces a novel research framework leveraging generative AI to label topics and propose improvement strategies based on the derived topics. This is noteworthy as it identifies actionable service opportunities aimed at enhancing service competitiveness and satisfaction, instead of merely outlining topics.

• Science of Emotion and Sensibility
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• v.18 no.3
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• pp.3-16
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• 2015

Will orange scent enhance video reality if it is presented with a video which vividly illustrates orange juice? Or, will romantic scent improve video reality if it is presented along with a date scene? Whereas the former is related to reality improvement when concrete objects or places are present in a video, the latter is related to a case when they are absent. This paper reviews previous research which tested diverse videos and scents in order to answer the above two different questions, and discusses implications, limitations, and future research directions. In particular, this paper focuses on measurement methods and results regarding acceptability of olfactory information, perception of scent similarity, olfactory vividness and video reality, matching between scent vs. color (or color temperature), and description of various scents using emotional adjectives. We expect this paper to help researchers or engineers who are interested in using scents for video reality.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.12
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• pp.1811-1818
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• 2013

As the broadband network are being deployed recently, the IPTV (Internet Protocol TV) has appeared and become a most representative service that incorporates audio, video, etc. In spite of the long-period efforts, however, no standardized method exists to measure and evaluate the quality of video that is experienced through TV in the customer's premises. Therefore, before developing a method to measure and evaluate the quality of experience (QoE) for video that is the ultimate goal, this paper reviews the outcomes from the past standardization activities and drive a few important implications that would be reflected to the method to measure and evaluate QoE for video.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.3
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• pp.172-179
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• 2015

Because of the development of computers and high-technology applications, all devices that we use have become more intelligent. In recent years, security and surveillance systems have become more complicated as well. Before new technologies included video surveillance systems, security cameras were used only for recording events as they occurred, and a human had to analyze the recorded data. Nowadays, computers are used for video analytics, and video surveillance systems have become more autonomous and automated. The types of security cameras have also changed, and the market offers different kinds of cameras with integrated software. Even though there is a variety of hardware, their capabilities leave a lot to be desired. Therefore, this drawback is trying to compensate by dint of computer program solutions. Image processing is a very important part of video surveillance and security systems. Capturing an image exactly as it appears in the real world is difficult if not impossible. There is always noise to deal with. This is caused by the graininess of the emulsion, low resolution of the camera sensors, motion blur caused by movements and drag, focus problems, depth-of-field issues, or the imperfect nature of the camera lens. This paper reviews image processing, pattern recognition, and image digitization techniques, which will be useful in security services, to analyze bio-images, for image restoration, and for object classification.