• ETRI Journal
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• v.36 no.5
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• pp.819-828
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• 2014

To solve the increasing popularity of video streaming services over the Internet, recent research activities have addressed the locality of content delivery from a network edge by introducing a storage module into a router. To employ in-network caching and persistent request routing, this paper introduces a hybrid content delivery network (CDN) system combining novel content routers in an underlay together with a traditional CDN server in an overlay. This system first selects the most suitable delivery scheme (that is, multicast or broadcast) for the content in question and then allocates an appropriate number of channels based on a consideration of the content's popularity. The proposed scheme aims to minimize traffic volume and achieve optimal delivery cost, since the most popular content is delivered through broadcast channels and the least popular through multicast channels. The performance of the adaptive scheme is clearly evaluated and compared against both the multicast and broadcast schemes in terms of the optimal in-network caching size and number of unicast channels in a content router to observe the significant impact of our proposed scheme.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.191-210
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• 2014

As mobile devices that can be connected to the Internet have spread and networking has become possible whenever/wherever, the Internet has become central in the dissemination and consumption of news. Accordingly, the ways news is gathered, disseminated, and consumed have changed greatly. In the traditional news media such as magazines and newspapers, expert editors determined what events were worthy of deploying their staffs or freelancers to cover and what stories from newswires or other sources would be printed. Furthermore, they determined how these stories would be displayed in their publications in terms of page placement, space allocation, type sizes, photographs, and other graphic elements. In turn, readers-news consumers-judged the importance of news not only by its subject and content, but also through subsidiary information such as its location and how it was displayed. Their judgments reflected their acceptance of an assumption that these expert editors had the knowledge and ability not only to serve as gatekeepers in determining what news was valuable and important but also how to rank its value and importance. As such, news assembled, dispensed, and consumed in this manner can be said to be expert-based recommended news. However, in the era of Internet news, the role of expert editors as gatekeepers has been greatly diminished. Many Internet news sites offer a huge volume of news on diverse topics from many media companies, thereby eliminating in many cases the gatekeeper role of expert editors. One result has been to turn news users from passive receptacles into activists who search for news that reflects their interests or tastes. To solve the problem of an overload of information and enhance the efficiency of news users' searches, Internet news sites have introduced numerous recommendation techniques. Recommendations based on popularity constitute one of the most frequently used of these techniques. This popularity-based approach shows a list of those news items that have been read and shared by many people, based on users' behavior such as clicks, evaluations, and sharing. "most-viewed list," "most-replied list," and "real-time issue" found on news sites belong to this system. Given that collective intelligence serves as the premise of these popularity-based recommendations, popularity-based news recommendations would be considered highly important because stories that have been read and shared by many people are presumably more likely to be better than those preferred by only a few people. However, these recommendations may reflect a popularity bias because stories judged likely to be more popular have been placed where they will be most noticeable. As a result, such stories are more likely to be continuously exposed and included in popularity-based recommended news lists. Popular news stories cannot be said to be necessarily those that are most important to readers. Given that many people use popularity-based recommended news and that the popularity-based recommendation approach greatly affects patterns of news use, a review of whether popularity-based news recommendations actually reflect important news can be said to be an indispensable procedure. Therefore, in this study, popularity-based news recommendations of an Internet news portal was compared with top placements of news in printed newspapers, and news users' judgments of which stories were personally and socially important were analyzed. The study was conducted in two stages. In the first stage, content analyses were used to compare the content of the popularity-based news recommendations of an Internet news site with those of the expert-based news recommendations of printed newspapers. Five days of news stories were collected. "most-viewed list" of the Naver portal site were used as the popularity-based recommendations; the expert-based recommendations were represented by the top pieces of news from five major daily newspapers-the Chosun Ilbo, the JoongAng Ilbo, the Dong-A Daily News, the Hankyoreh Shinmun, and the Kyunghyang Shinmun. In the second stage, along with the news stories collected in the first stage, some Internet news stories and some news stories from printed newspapers that the Internet and the newspapers did not have in common were randomly extracted and used in online questionnaire surveys that asked the importance of these selected news stories. According to our analysis, only 10.81% of the popularity-based news recommendations were similar in content with the expert-based news judgments. Therefore, the content of popularity-based news recommendations appears to be quite different from the content of expert-based recommendations. The differences in importance between these two groups of news stories were analyzed, and the results indicated that whereas the two groups did not differ significantly in their recommendations of stories of personal importance, the expert-based recommendations ranked higher in social importance. This study has importance for theory in its examination of popularity-based news recommendations from the two theoretical viewpoints of collective intelligence and popularity bias and by its use of both qualitative (content analysis) and quantitative methods (questionnaires). It also sheds light on the differences in the role of media channels that fulfill an agenda-setting function and Internet news sites that treat news from the viewpoint of markets.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1095-1102
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• 2023

Content Centric Network (CCN) is a network that emerged to improve the existing network structure and communicates based on content names instead of addresses. It utilises caches to distribute traffic and reduce response time by delivering content from intermediate nodes. In this paper, we propose a popularity-based caching policy to efficiently utilise the limited CS space in CCN environment. The performance of CCNs can vary significantly depending on which content is prioritised to be stored and released. To achieve the most efficient cache replacement, we propose a real-time content popularity-based efficient cache replacement policy that calculates and prioritises content popularity based on constructor popularity, constructor distance, and content hits, and demonstrate the effectiveness of the new policy through experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.1
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• pp.78-87
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• 2015

Content-Centric Networking(CCN) is a new networking paradigm to search for the routing information needed to find a data from the content name, unlike conventional IP networks. In CCN, the mobility management, one of the CCN challenges, is consists of consumer mobility and content provider mobility. Among both, in the case of the content provider mobility, it requires too much overhead and time to update routing information on the corresponding routers. In this paper, we propose Popularity-based Pushing CCN(PoPCoN) which considers the content popularity to support effective mobility of content provider in CCN. Our proposed algorithm shortens content download time for the consumer and reduces the network overhead during mobility as compared to the existing approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1498-1507
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• 2017

According to recent report, global mobile data traffic is expected to increase by 11 times from 2016 to 2020. Moreover, this growth is expected to be driven mainly by mobile video traffic which is expected to account for about 70% of the total mobile data traffic. To cope with enormous mobile traffic, we need to understand video traffic's characteristic. Recently, the repetitive requests of some popular content such as popular YouTube videos cause a enormous network traffic overheads. If we constitute a network with the nodes capable of content caching based on the content popularity, we can reduce the network overheads by using the cached content for every request. Through device-to-device, multicast, and helpers, the video throughput can improve about 1.5~2 times and prefix caching reduces the playback delay by about 0.2~0.5 times than the conventional method. In this paper, we introduce some recent work on content popularity-based caching techniques in wireless networks.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.49-55
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• 2023

In this study, models for predicting the popularity of mukbang content on YouTube were proposed, and factors influencing the popularity of mukbang content were identified through post-analysis. To accomplish this, information on 22,223 pieces of content was collected from top mukbang channels in terms of subscribers using APIs and Pretty Scale. Machine learning algorithms such as Random Forest, XGBoost, and LGBM were used to build models for predicting views and likes. The results of SHAP analysis showed that subscriber count had the most significant impact on view prediction models, while the attractiveness of a creator emerged as the most important variable in the likes prediction model. This confirmed that the precursor factors for content views and likes reactions differ. This study holds academic significance in analyzing a large amount of online content and conducting empirical analysis. It also has practical significance as it informs mukbang creators about viewer content consumption trends and provides guidance for producing high-quality, marketable content.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.11
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• pp.2151-2159
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• 2015

Unlike an existing IP routing methods, the Content Centric Network(CCN) is new networking paradigm to find the contents by content name. The CCN can effectively process the content requested repeatedly by the user because of the cache which can be storing a content. This paper proposes a popularity based cache replacement scheme. The proposed scheme improves the hit rate better than a existing scheme. Accordingly reducing the load of server and Round Trip Time(RTT).

• Asia pacific journal of information systems
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• v.33 no.2
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• pp.282-297
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• 2023

One of the emerging trends in the marketing field is digital video marketing. Online videos offer rich content typically containing more information than any other type of content (e.g., audible or textual content). Accordingly, previous researchers have examined factors influencing videos' popularity. However, few studies have examined what causes a video to remain popular. Some videos achieve continuous, ongoing popularity, while others fade out quickly. For practitioners, videos at the recommendation slots may serve as strong communication channels, as many potential consumers are exposed to such videos. So,this study will provide practitioners important advice regarding how to choose videos that will survive as long-lasting favorites, allowing them to advertise in a cost-effective manner. Using deep learning techniques, this study extracts text from videos and measured the videos' tones, including factual and emotional tones. Additionally, we measure the aesthetic score by analyzing the thumbnail images in the data. We then empirically show that the cognitive features of a video, such as the tone of a message and the aesthetic assessment of a thumbnail image, play an important role in determining videos' long-term popularity. We believe that this is the first study of its kind to examine new factors that aid in ensuring a video remains popular using both deep learning and econometric methodologies.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1113-1120
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• 2021

Content Central Network (CCN) appeared to improve network efficiency by transforming IP-based network into content name-based network structures. Each router performs caching mechanism to improve network efficiency in the CCN. And the cache replacement policy applied to the CCN router is an important factor that determines the overall performance of the CCN. Therefore various studies has been done relating to cache replacement policy of the CCN. In this paper, we proposed a cache replacement policy that improves the limitations of the LFU policy. The proposal algorithm applies real-time producer popularity-based variables. And through experiments, we proved that the proposed policy shows a better cache hit ratio than existing policies.

• International Journal of Knowledge Content Development & Technology
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• v.1 no.1
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• pp.25-37
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• 2011

This study analyzes circulation statistics of television tie-in picture books from the Wake County Public Library System in North Carolina to determine their popularity among patrons. Caldecott winning picture books were used as a point of comparison. This study also examined OPAC holdings from North Carolina public libraries to determine television tie-in picture book popularity among collection builders. The findings of the study show that television tie-in picture books are found to some degree in the vast majority of North Carolina public libraries, and are more popular than award winners in the Wake County system.