Insights from Analysis of Video Streaming Data to Improve Resource Management

Today a large portion of Internet traffic is video. Over The Top (OTT) service providers offer video streaming services by creating a large distributed cloud network on top of a physical infrastructure owned by multiple entities. Our study explores insights from video streaming activity by analyzing data collected from Korea's largest OTT service provider. Our analysis of nationwide data shows interesting characteristics of video streaming such as correlation between user profile information (e.g., age, sex) and viewing habits, viewing habits of users (when do the users watch? using which devices?), viewing patterns (early leaving viewer vs. steady viewer), etc. Video on Demand (VoD) streaming involves costly (and often limited) compute, storage, and network resources. Findings from our study will be beneficial for OTTs, Content Delivery Networks (CDNs), Internet Service Providers (ISPs), and Carrier Network Operators, to improve their resource allocation and management techniques.Comment: This is a preprint electronic version of the article accepted to IEEE CloudNet 201

Just browsing?:understanding user journeys in online TV

Understanding the dynamics of user interactions and the behaviour of users as they browse for content is vital for advancements in content discovery, service personalisation, and recommendation engines which ultimately improve quality of user experience. In this paper, we analyse how more than 1,100 users browse an online TV service over a period of six months. Through the use of model-based clustering, we identify distinctive groups of users with discernible browsing patterns that vary during the course of the day

Content Discovery in Online Services: A Case Study on a Video on Demand System

Video-on-demand services have gained popularity in recent years for the large catalogue of content they offer and the ability to watch them at any desired time. Having many options to choose from may be overwhelming for the users and affect negatively the overall experience. The use of recommender systems has been proven to help users discover relevant content faster. However, content discovery is affected not only by the number of choices, but also by the way the content is displayed to the user. Moreover, the development of recommender systems has been commonly focused on increasing their prediction accuracy, rather than the usefulness and user experience. This work takes on a user-centric approach to designing an efficient content discovery experience for its users. The main contribution of this research is a set of guidelines for designing the user interface and recommender system for the aforementioned purpose, formulated based on a user study and existing research. The guidelines were additionally translated into interface designs, which were then evaluated with users. The results showed that users were satisfied with the proposed design and the goal of providing a better content discovery experience was achieved. Moreover, the guidelines were found feasible by the company in which the research was conducted and thus have a high potential to work in a real product. With this research, I aim to highlight the importance of improving the content discovery process both from the perspective of the user interface and a recommender system, and encourage researchers to consider the user experience in those aspects

A Video Timeline with Bookmarks and Prefetch State for Faster Video Browsing

International audienceReducing seek latency by predicting what the users will access is important for user experience, particularly during video browsing, where users seek frequently to skim through a video. Much existing research strived to predict user access pattern more accurately to improve the prefetching hit rate. This paper proposed a different approach whereby the prefetch hit rate is improved by biasing the users to seek to prefetched content with higher probability, through changing the video player user interface. Through a user study, we demonstrated that our player interface can lead to up to 4$\times$ more seeks to bookmarked segments and reduce seek latency by 40\%, compared to a video player interface commonly used today. The user study also showed that the user experience and the understanding of the video content when browsing is not compromised by the changes in seek behavior.

Do All Roads Lead to Rome? Exploring the Relationship Between Social Referrals, Referral Propensity and Stickiness to Video-on-Demand Websites

Content website providers have two main goals: They seek to attract consumers and to keep them on their websites as long as possible. To reach potential consumers, they can utilize several online channels, such as paid search results or advertisements on social media, all of which usually require a substantial marketing budget. However, with rising user numbers of online communication tools, website providers increasingly integrate social sharing buttons on their websites to encourage existing consumers to facilitate referrals to their social networks. While little is known about this social form of guiding consumers to a content website, the study proposes that the way in which consumers reach a website is related to their stickiness to the website and their propensity to refer content to others. By using a unique clickstream data set of a video-on-demand website, the study compares consumers referred by their social network to those consumers arriving at the website via organic search or social media advertisements in terms of stickiness to the website (e.g., visit length, number of page views, video starts) and referral likelihood. The results show that consumers referred through social referrals spend more time on the website, view more pages, and start more videos than consumers who respond to social media advertisements, but less than those coming through organic search. Concerning referral propensity, the results indicate that consumers attracted to a website through social referrals are more likely to refer content to others than those who came through organic search or social media advertisements. The study offers direct insights to managers and recommends an increase in their efforts to promote social referrals on their websites

Giving and Following Recommendations on Video-on-Demand Services

This is an empirical paper about giving, receiving and following recommendations on Video-on-Demand (VoD) services, including results on gender-specific differences. Based upon a model for infor-mation behavior on VoD services, we applied an online survey and generated 1,258 valid question-naires from active VoD users. Participants receive recommendations from the systems once a week on average, but they follow them only occasionally. They give actively recommendations to other people sever-al times a month. Users do not receive recommenda-tions from other users as often as from the services (only several times a month); however, they follow those personal recommendations more often. The most important source for receiving personal rec-ommendations is face-to-face communication. Obvi-ously, VoD users follow personal recommendations from other people more than suggestions from algo-rithmically generated recommender systems. Besides, self-determined content selection following intrinsic motivation is important. The findings are of interest for research on digital and social media and for VoD services

Traffic analysis of Internet user behavior and content demand patterns

El estudio del trafico de internet es relevante para poder mejorar la calidad de servicio de los usuarios. Ser capaz de conocer cuales son los servicios más populares y las horas con más usuarios activos permite identificar la cantidad de tráfico producido y, por lo tanto, diseñar una red capaz de soportar la actividad esperada. La implementación de una red considerando este conocimiento puede reducir el tiempo de espera considerablemente, mejorando la experiencia de los usuarios en la web. Ya existen análisis del trafico de los usuarios y de sus patrones de demanda. Pero, los datos utilizados en estos estudios no han sido renovados, por lo tanto los resultados obtenidos pueden estar obsoletos y se han podido producir cambios importantes. En esta tesis, se estudia la cantidad de trafico entrante y saliente producido por diferentes aplicaciones y se ha hecho una evolución teniendo en cuenta datos presentes y pasados. Esto nos permitirá entender los cambios producidos desde 2007 hasta 2015 y observar las tendencias actuales. Además, se han analizado los patrones de demanda de usuarios del inicio de 2016 y se han comparado con resultados previos. La evolución del tráfico demuestra cambios en las preferencias de los usuarios, a pesar de que los patrones de demanda siguen siendo los mismos que en años anteriores. Los resultados obtenidos en esta tesis confirman las predicciones sobre un aumento del tráfico de 'Streaming Media'; se ha comprobado que el tráfico de 'Streaming Media' es el tráfico total dominante, con Netflix como el mayor contribuidor.L'estudi del trànsit d'Internet és rellevant per a poder millor la qualitat de servei dels usuaris. Ser capaç de conèixer quins són els serveis més popular i les hores amb més usuaris actius permet identificar la quantitat de trànsit produït i, per tant, dissenyar una xarxa capaç de soportar la activitat esperada. L'implementació d'una xarxa considerant aquest coneixement pot reduir el temps d'espera considerablement, millorant l'experiència dels usuaris a la web. Ja existeixen anàlisis del transit dels usuaris i els seus patrons de demanda. Però, les dades utilitzades en aquests estudis no han sigut renovades, per tant els resultats obtinguts poden estar obsolets i s'han produït canvis importants. En aquesta tesis, s'estudia la quantitat de transit entrant i sortint produit per diferents aplicacions i s'ha fet una evolució, tenint en compte dades presents i passades. Això ens permetrà entendre els canvis produïts des de 2007 fins 2015 i observar les tendències actuals. A més, s'han analitzat els patrons de demanda de usuaris de principis de 2016 i s'han comparat amb resultats previs. L'evolució del trànsit mostra canvis en las preferències dels usuaris, en canvi els patrons de demanda continuen sent els mateixos que en anys posteriors. Els resultats obtinguts en aquesta tesis confirmen les prediccions sobre un augment del trànsit de 'Streaming Media'; s'ha comprovat que el trànsit de 'Streaming Media' es el trànsit total dominant, amb Netflix com el major contribuïdor.The study of Internet traffic is relevant in order to improve the quality of service of users. Being able to know which are the most popular services and the hours with most active users can let us identify the amount of inbound and outbound traffic produced, and hence design a network able to support the activity expected. The implementation of a network considering that knowledge can reduce the waiting time of users considerably, improving the users’ experience in the web. Analysis of users’ traffic and user demand patterns already exist. However, the data used in these studies is not renewed, thus the results found can be obsolete and considerable changes would have happened. In this bachelor’s thesis, it is studied the amount of inbound and outbound traffic produced considering different applications and the evolution when regarding previous and actual data has been taken into account. This would let us understand the changes produced from 2007 to 2015 and observe the tendencies nowadays. In addition, it has been analyzed the user demand patterns in the beginning of 2016 and it has been contrasted with previous results. The evolution of traffic has shown changes in users’ preferences, although their demand patterns are still the same as previous years. The results found in this thesis confirmed the expectations about an increase of streaming media Internet traffic; it was proved that streaming media traffic is the dominant total traffic, with Netflix as the major contributor

Impact of information presentation modes on online shopping: An empirical evaluation of a broadband interactive shopping service

With the increasing cost-effectiveness of communication technologies, online shopping has emerged as one of the most important areas of electronic commerce. A major problem facing online shopping service providers is the heterogeneity of user profile. Unlike organizational systems that have a well-defined universe of users and system boundary, these shopping services are designed for public users with very different cognitive and demographic profiles. The major challenge lies in designing friendly and effective user interfaces for online shoppers. Previous studies on online shopping suggest that a good user interface with an appropriate mode of information presentation is the key to system acceptance. In this article, we report on an empirical study that looks at product information presentation modes in an actual broadband supermarket shopping environment. Four prototypes with different combinations of text and picture displays were developed and evaluated in an experimental setting. The findings suggest that there is a close relation between product familiarity and shopping effectiveness. When the system is used to purchase familiar product items, pictures are better than text in terms of both efficiency and effectiveness. However, when users are not familiar with the product items, the advantages of pictures over text diminish. Implications of the findings and future research areas are discussed.published_or_final_versio