基于聚类的网络直播群体行为建模分析

近年来,随着互联网技术的不断发展,以及手机、平板电脑等移动终端的普及,网络直播逐渐兴起并壮大.国内众多直播平台基本都有送礼机制,允许观众购买平台提供的虚拟礼物来打赏主播.观众的打赏对于主播和平台来说都是主要的收入来源之一,所以理解观众的行为以挖掘观众的用户价值,提升用户的变现能力就显得尤为重要.本文以斗鱼直播平台为例,聚焦于直播平台上的高消费群体,通过构建观众特征,采用聚类方法分析高消费群体的行为.实验结果表明,高消费观众可被分为特征有明显差异的三类群体.对这三类观众的特征,本文进一步进行详细分析,为直播平台面向用户的差异化产品服务提供依据.     

On improving the engagement between viewers and TV commercials through gamification

Multimedia Systems - TV advertisements are less and less watched as most viewers turn their attention to the smartphone during commercial breaks. Therefore, broadcasters are facing a novel...     

PULSE: An Adaptive, Incentive-Based, Unstructured P2P Live Streaming System

Large-scale live media streaming is a challenge for traditional server-based approaches. To appropriately support big audiences, broadcasters must be able to allocate huge bandwidth and computational resources. The costs involved with such an infrastructure exclude all but the established content producers from exploiting the Internet as a distribution medium. Publishers of not-yet-popular content, unless they manage to properly predict their maximum audience size, will likely fail to dimension correctly their broadcast infrastructure. Peer-to-peer systems for live streaming allow the users to support content distribution by contributing their unused resources: this increases the scalability of the content distribution while reducing at the same time the economical burden on the streaming provider. This paper presents and evaluates PULSE, an unstructured mesh-based peer-to-peer system designed to support live streaming to large audiences under the arbitrary resource availability as is typically the case for the Internet. PULSE is a highly dynamic system: it constantly optimizes its mesh of data connections using a feedback-driven peer selection strategy that is based on pairwise incentives. We evaluate the behavior of PULSE under realistic scenarios via simulation and emulation, and present the advantages of our approach, namely a best-effort response to system-wide resource scarcity, high resilience to node churn, and good hop-count properties of the average data distribution paths.     

Hierarchically Clustered P2P Video Streaming: Design,implementation, and evaluation

P2P based live streaming has been gaining popularity. The new generation P2P live streaming systems not only attract a large number of viewers, but also support better video quality by streaming the content at higher bit-rate. In this paper, we propose a novel P2P streaming framework, called Hierarchically Clustered P2P Video Streaming, or HCPS, that can support the streaming rate approaching the optimal upper bound while accommodating large viewer population. The scalability comes with the hierarchical overlay architecture by grouping peers into clusters and forming a hierarchy among them. Peers are assigned to appropriate cluster so as to balance the bandwidth resources across clusters and maximize the supportable streaming rate. Furthermore, individual peers perform distributed queue-based scheduling algorithms to determine how to retrieve data chunks from source and neighboring peers, and how to utilize its uplink bandwidth to serve data chunks to other peers. We show that queue-based scheduling algorithms allow to fully utilize peers’ uplink bandwidths, and HCPS supports the streaming rate close to the optimum in practical network environment. The prototype of HCPS is implemented and various design issues/tradeoffs are investigated. Experiments over the PlanetLab further demonstrate the effectiveness of HCPS design.     

On helping broadcasters to promote TV-shows through hashtags

Television is no longer the king of the living room: 86% of people watch TV with a second screen in the nearby and more than 30% of the attention time is given to the second device to perform social activities. Therefore, the television industry is facing a new challenge: find a way to re-catch viewers’ attention. A recent and popular approach considers the use of official hashtags to implement a cross-media strategy that will connect different contents across multiple media. Since the simple proposition of official hashtags is not sufficient to guarantee the success of a cross media strategy, in this paper, we analyze how official hashtags are used and we propose a model to write tweets effectively. The model is based on the analysis of more than 250,000 tweets that talk about TV-shows. In particular, (i) we analyze the availability and visibility of official hashtags, (ii) we study the tweets characteristics written by the most retweeted authors, and (iii) we build a network of hashtags in order to understand how users use official hashtags. The obtained results allowed us to define guidelines to help broadcasters in the promotion of TV-shows and in the engagement of viewers.

     

Personalized live streaming channel recommendation based on most similar neighbors

Multimedia Tools and Applications - With the rapid development of mobile network technology, an increasing number of viewers are watching channels through live streaming platforms, and thousands...     

What makes a video go viral? An analysis of emotional contagion and Internet memes

What qualities lead some Internet videos to reach millions of viewers while others languish in obscurity? This question has been largely unexamined empirically. We addressed this issue by examining the role of emotional response and video source on the likelihood of spreading an Internet video by validating the emotional response to an Internet video and investigating the underlying mechanisms. Results indicated that individuals reporting strong affective responses to a video reported greater intent to spread the video. In terms of the role of the source, anger-producing videos were more likely to be forwarded but only when the source of the video was an out-group member. These results have implications for emotional contagion, social influence, and online behavior.     

A holistic approach for personalization,relevance feedback & recommendation in enriched multimedia content

As the prerequisites of production houses, broadcasters, advertising agencies and online publishing companies for enriched multimedia content increase rapidly, the need of innovative methods for the effective creation of enriched multimedia content is undeniable. Stemming from this need, in this paper we focus on the design, development and evaluation of a framework consisting of personalization, relevance feedback and recommendation mechanisms, as a principal method for the creation of enriched multimedia content targeted to each user’s needs, preferences and interests. As the multimedia content proliferates along with its consumption by the users, more effective ways of presenting it to the viewers are demanded in order to facilitate them with the multimedia content search and selection and improve their Quality of Experience (QoE). The main contribution of the paper is the introduction of a holistic framework that offers personalized enriched multimedia content, by extending the recommendation process to the set of enrichments that accompany the video except from the video itself and by collecting explicit and implicit relevance feedback from the interactions of the user with both the video and its enrichments. We evaluate the proposed framework following a two-step approach. Firstly, we perform extended experiments by applying reasonably simulated user interactions, in order to calibrate its parameters that refer to multiple aspects of the enriched multimedia content, aiming at high performance in terms of QoE. Here, most importantly, we have shown that appropriately designing the enrichments and considering users’ interactions with them allows for achieving a better quality in inferring users’ profiles in many realistic cases. Secondly, we integrated our proposed recommender framework within the MECANEX streaming platform in order to perform user studies about its usability within a realistic environment of use.     

A hybrid approach for personalized service staff recommendation

In this study, we established a novel set of service procedures that epitomize the human-centered spirit of service. By using self-organizing maps and collaborative filtering recommendation, we developed a mechanism that links the two service procedures of selecting service staff members and how customers decide tip amounts based on perceived value. Through the proposed mechanism, the recommender system could effectively predict customer preferences regarding service staff members and assign suitable members for delivering services. In addition, this study integrated the service experiences of previous customers with local tipping cultures for calculating recommended tip amounts for the reference of customers. Under this mechanism, the customer-centered spirit can be completely integrated into service procedures for effectively enhancing customer satisfaction, increasing the job satisfaction of employees, and producing a virtuous cycle of service quality improvement.     

Immersive interactive reality: Internet-based on-demand VR for cultural presentation

This paper presents an Internet-based virtual reality technology, called panoramic broadcasting (PanoCAST) where multiple viewers share an experience yet each having full control of what they see independent from other viewers. Our solution was developed for telepresence-based cultural presentation and entertainment services. The core architecture involves a compact spherical vision system that compresses and transmits data from multiple digital video sources to a central host computer, which in turn distributes the recorded information among multiple render- and streaming servers for personalized viewing over the Internet or mobile devices. In addition, using advanced computer vision, tracking and animation features, the PanoCAST architecture introduces the notion of Clickable Content Management (CCM), where each visual element in the image becomes a source for providing further information, educational content and cultural detail. Key contributions of our application to advance the state-of-the-art include bringing streaming panoramic video onto mobile platforms, an advanced tracking interface to turn visual elements into sources of interaction, physical simulation to combine the benefits of panoramic video with that of 3D models and animated, photo-realistic faces to help users express their emotions in shared online virtual cultural experiences as well as a feedback mechanism in such environments. Therefore, we argue that the PanoCAST system offers a low-cost and economical solution for personalized content distribution and as such it can serve as a unified basis for novel applications many of which are demonstrated in this paper.     

On the way to understanding binge watching behavior: the over-estimated role of involvement

Watching television shows using online television streaming services, such as Netflix, Hulu, and Youku, has mushroomed in the recent years. Along with these services, binge watching, defined as an act of consuming more than one episode of a television show in quick succession, has become a widespread behavior. Yet, it has received very little attention from academics. This study conceptualizes binge watching and examines its effect on satisfaction. We present binge watching as a two-dimensional system usage concept, including behavioral and cognitive involvement components. Using these components, we then study their impact on user satisfaction. We test our explorative approach with a sample of 227 respondents using Partial Least Squares modeling. The results support heterogeneous view of online television streaming service use. That is, involvement with binge watching is over-estimated and does not define user satisfaction. Our study contributes to online consumer behavior research as well as the information systems literature by investigating binge watching as a distinct form of technology use.     

Interest-suppression-based NDN live video broadcasting over wireless LAN

Named data networking (NDN) is a new Internet architecture that replaces today’s focus on where – addresses and hosts with what – the content that users and applications care about. One of NDN’s prominent advantages is scalable and efficient content distribution due to its native support of caching and multicast in the network. However, at the last hop to wireless users, often the WiFi link, current NDN implementation still treats the communication as multiple unicast sessions, which will cause duplicate packets and waste of bandwidth when multiple users request for the same popular content. WiFi’s built-in broadcast mechanism can alleviate this problem, but it suffers from packet loss since there is no MAC-layer acknowledgement as in unicast. In this paper, we develop a new NDN-based cross-layer approach called NLB for efficient and scalable live video streaming over wireless LAN. The core ideas are: using WiFi’s broadcast channel to deliver content from the access point to the users, a leader-based mechanism to suppress duplicate requests from users, and receiver-driven rate control and loss recovery. The design is implemented and evaluated in a physical testbed comprised of one software AP and 20 Raspberry Pi-based WiFi clients. While NDN with multiple unicast sessions or plain broadcast can support no more than ten concurrent viewers of a 1Mbps streaming video, NDN plus NLB supports all 20 viewers, and Received December 29, 2015; accepted April 28, 2016 E-mail: zhxp@tsinghua.edu.cn can likely support much more when present.     

A target advertisement system based on TV viewer’s profile reasoning

The traditional broadcasting services such as terrestrial, satellite and cable broadcasting have been unidirectional mass media regardless of TV viewer’s preferences. Recently rich media streaming has become possible via the broadband networks. Furthermore, since bidirectional communication is possible, personalcasting such as personalized streaming service has been emerging by taking into account the user’s preference on content genres, viewing times and actors/actresses etc. Accordingly personal media becomes an important means for content provision service in addition to the traditional broadcasting service as mass media. In this paper, we introduce a user profile reasoning method for TV viewers. The user profile reasoning is made in terms of genre preference and TV viewing times for TV viewer’s groups in different genders and ages. For user profiling reasoning, the TV viewing history data is used to train the proposed user profiling reasoning algorithm which allows for target advertisement for different age/gender groups. To show the effectiveness of our proposed user profile reasoning method, we present plenty of the experimental results by using real TV usage history.     

Streaming video transforms the media industry

After years of promises, streaming media has finally arrived. Skeptics argued for years that IP-based videa was an overhyped technology that only succeeded in frustrating users by its high failure rate. But proponents maintained that streaming was first and foremost about access, and that full-screen, DVD-quality video was a matter of time. Developments have proved them right. Streaming media is causing a sea change in education, business, and mass media. Millions of people watch live newscasts, sports, and concerts on their PCs. Universities deploy streaming technology to enhance their distance learning programs, and corporations use it to improve knowledge-sharing and cross-company cooperation. Media companies and broadcasters are opening their archives, giving consumers access to thousands of popular and long-forgotten movies, documentaries, and 50 years of television programming. Web casters are proliferating, targeting audiences ranging from homemakers to business professionals, and advertisers insert interactive audiovisual ads in Web pages. Streaming is not limited to PCs. Wireless carriers target mobile phones with made-for-mobile content, and several carriers are preparing to launch live TV services for mobile phones. Streaming combines the immediacy of with the interactivity of the internet and is revolutionizing the media landscape. Its provides access-on-demand rich media anywhere on any device. Based on Internet protocols, sttreaming technology enables small companies and individuals to become Web casters with a global audience.     

More than watching: An empirical and experimental examination on the impacts of live streaming user-generated video consumption

Live streaming user-generated video (UGV), a nascent format of crowdsourced content, has grown massive popularity among social media users and is believed to have substantial potential business influences. However, industry practitioners express concerns regarding this new form on social media platforms and the influences of live streaming UGV consumption lack research. Motivated such, through a uniquely merged dataset from the video game industry, we conduct a series of panel time-series empirical analyses to investigate the business value of live streaming UGV consumption. Further, we propose a conceptual framework based on the sense of community literature to understand the consequences of live streaming UGV consumption and verify it through several online experiments. This research contributes to the IS literature by shedding light on the influences of emergent crowdsourced content, providing a conceptual framework to existing literature, and offering rich managerial implications and guidelines to managers regarding utilizing live streaming UGVs.     

Packet loss in peer-to-peer video streaming over the Internet

Peer-to-peer streaming has recently gained attention as an effective solution to support large scale media streaming applications over the Internet. One of the main challenges of peer-to-peer video streaming is the cumulative impact of the Internet packet loss due to the decoding dependency of the compressed video frames. In this paper we study the impact of the Internet packet loss on the performance of peer-to-peer video streaming systems, and analyze the efficiency of various packet loss recovery policies in such systems. Our analytical and simulation results show how the Internet packet loss can affect the performance of peer- to-peer video streaming systems and how different packet loss recovery policies can be effective for such systems. Our analysis results give us some insights that can be used in designing efficient peer-to-peer video streaming systems.     

浅谈LoadRunner在网络流媒体中的应用

随着互联网的迅猛发展和普及为网络流媒体业务发展提供了强大市场动力,网络流媒体技术也得到了广泛的应用,用户对流媒体业务的质量需求也日益高涨。本文首先简单介绍什么是LoadRunner和它的工作原理以及什么是网络流媒体和网络流媒体的工作原理,然后介绍如何运用LoadRunner对网络流媒体的播放操作进行压力测试,研究分析测试结果,提出相应的解决方案。     

Emotional responses to watching and touching 3d emotional face in a virtual environment

Virtual Reality - Facial expressions play a crucial role in modulating the emotional responses in the viewers. Touch is an important factor in shaping human emotions and social communication. The...     

57 channels and nothing on

Public Service broadcasters face stiff competition as a result of an increase in the number of broadcasters in the digital era. Further falls in their advertising revenue are the likely result. This will make it harder for them to finance their Public Service obligations.

The EC concerned at the impact of US imports has promulgated the Television Without Frontiers Directive. This requires member states to impose cultural diversity obligations on broadcasters with their jurisdiction. The legality of these measures has been questioned by the US. Their effectiveness is thrown into doubt by the convergence phenomenon.

The article examines these challenges. It also looks at the programming requirements imposed on public service broadcasters by the Communications Act 2003. |em|At a broadcaster level, the authors argue, the Directive provides a further illustration of the difficulty of achieving a workable balance between free trade and other social policy goals (such as cultural diversity).     

Publicly Private and Privately Public: Social Networking on YouTube

YouTube is a public video-sharing website where people can experience varying degrees of engagement with videos, ranging from casual viewing to sharing videos in order to maintain social relationships. Based on a one-year ethnographic project, this article analyzes how YouTube participants developed and maintained social networks by manipulating physical and interpretive access to their videos. The analysis reveals how circulating and sharing videos reflects different social relationships among youth. It also identifies varying degrees of "publicness" in video sharing. Some participants exhibited "publicly private" behavior, in which video makers' identities were revealed, but content was relatively private because it was not widely accessed. In contrast, "privately public" behavior involved sharing widely accessible content with many viewers, while limiting access to detailed information about video producers' identities.