Mapping the Money in Public Media

Provides an overview of emerging "user-centric" business models for public media that utilize the interactivity of digital technologies as a way to integrate content, communication, commerce, and community through participatory media creation

Social Media and User-Centric Approach: A Comprehensive Exploration

The communication industry has skilled a significant model shift in recent times because of the ubiquitous impact of social media (Smith, 2021). In addition to reforming interpersonal communication, these platforms have emerged as vital channels for the dissemination of information and the development of societies (Jones et al., 2020). This chapter explores the transition towards a user-centric approach and the development of social media stages over time. This investigation is built upon the user-centric approach, which prioritises the customization of digital experiences according to individual preferences. It is crucial to grasp the multi-layered effects of social media on group domains, including information sharing, communication, and community development, by adopting a user-centric perspective on its dynamics (Brown & Johnson, 2019). This chapter examines the implications of adopting a user-centric design and implementation approach for social media platforms on user assignation, satisfaction, and well-being as a whole. It emphasises the implication of this approach

User-centric research in media accessibility

Research on translation can be approached from a myriad of perspectives, depending on where the emphasis is put: product, process, participants or context-oriented investigations are the four broad categories identified by Saldanha and O'Brien (2013). TransMedia Catalonia research group has a long history of media accessibility projects where "participants" are at the center of the research, following the "Nothing about us without us" principle in accessibility. When developing new tools, a user-centric iterative methodology is generally followed: user requirements are gathered and implemented, and the resulting product is tested in terms of usability. This is the case of the ImAc project. When developing new strategies for certain access services (such as audio description or audio subtitling), alternative solutions are tested with end users through different experimental designs. This is the case of the NEA and RAD projects. When proposing new innovative approaches to media accessibility, users are involved in discussion groups and interviews to assess the feasibility of these new approaches. This is the case of the EASIT project. The aim of this presentation is to discuss how user-centric methodologies have been implemented and can be implemented in media accessibility projects, highlighting the pros and cons of different methodological tools. At the end of my presentation, I will open the lens to discuss new participatory-approaches to research inspired by the TRACTION project. I will also stress the need to share research through networks such as ALMA or LEAD-ME and through platforms such as MA

Service oriented interactive media (SOIM) engines enabled by optimized resource sharing

In the same way as cloud computing, Software as a Service (SaaS) and Content Centric Networking (CCN) triggered a new class of software architectures fundamentally different from traditional desktop software, service oriented networking (SON) suggests a new class of media engine technologies, which we call Service Oriented Interactive Media (SOIM) engines. This includes a new approach for game engines and more generally interactive media engines for entertainment, training, educational and dashboard applications. Porting traditional game engines and interactive media engines to the cloud without fundamentally changing the architecture, as done frequently, can enable already various advantages of cloud computing for such kinds of applications, for example simple and transparent upgrading of content and unified user experience on all end-user devices. This paper discusses a new architecture for game engines and interactive media engines fundamentally designed for cloud and SON. Main advantages of SOIM engines are significantly higher resource efficiency, leading to a fraction of cloud hosting costs. SOIM engines achieve these benefits by multilayered data sharing, efficiently handling many input and output channels for video, audio, and 3D world synchronization, and smart user session and session slot management. Architecture and results of a prototype implementation of a SOIM engine are discussed

Modeling user perception of 3D video based on ambient illumination context for enhanced user centric media access and consumption

For enjoying 3D video to its full extent, it is imperative that access and consumption of it is user centric, which in turn ensures improved 3D video perception. Several important factors including video characteristics, users’ preferences, contexts prevailing in various usage environments, etc have influences on 3D video perception. Thus, to assist efficient provision of user centric media, user perception of 3D video should be modeled considering the factors affecting perception. Considering ambient illumination context to model 3D video perception is an interesting research topic, which has not been particularly investigated in literature. This context is taken into account while modeling video quality and depth perception of 3D video in this paper. For the video quality perception model: motion and structural feature characteristics of color texture sequences; and for the depth perception model: luminance contrast of color texture and depth intensity of depth map sequences of 3D video are used as primary content related factors in the paper. Results derived using the video quality and depth perception models demonstrate that these models can efficiently predict user perception of 3D video considering the ambient illumination context in user centric media access and consumption environments

Tracking the History and Evolution of Entities: Entity-centric Temporal Analysis of Large Social Media Archives

How did the popularity of the Greek Prime Minister evolve in 2015? How did the predominant sentiment about him vary during that period? Were there any controversial sub-periods? What other entities were related to him during these periods? To answer these questions, one needs to analyze archived documents and data about the query entities, such as old news articles or social media archives. In particular, user-generated content posted in social networks, like Twitter and Facebook, can be seen as a comprehensive documentation of our society, and thus meaningful analysis methods over such archived data are of immense value for sociologists, historians and other interested parties who want to study the history and evolution of entities and events. To this end, in this paper we propose an entity-centric approach to analyze social media archives and we define measures that allow studying how entities were reflected in social media in different time periods and under different aspects, like popularity, attitude, controversiality, and connectedness with other entities. A case study using a large Twitter archive of four years illustrates the insights that can be gained by such an entity-centric and multi-aspect analysis.Comment: This is a preprint of an article accepted for publication in the International Journal on Digital Libraries (2018

On extracting user-centric knowledge for personalised quality of service in 5G networks

©2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper aims to improve the user Quality of Service (QoS) in 5G networks by introducing a user-centric view that exploits the predictability of the user’s daily motifs. An agglomerative clustering is used to identify these motifs according to the cells in which the user is camping during the day. Then, a technique to extract the personalised QoS observed by the user is proposed. The methodology is illustrated with an example that makes use of real measurements obtained from a specific customer of a 3G/4G operator. The presented results illustrate that the proposed user-centric approach is able to identify situations with poor user perceived QoS which could not be identified by a classical network-centric approach.Peer ReviewedPostprint (author's final draft

Human-Centric Cyber Social Computing Model for Hot-Event Detection and Propagation

The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.Microblogging networks have gained popularity in recent years as a platform enabling expressions of human emotions, through which users can conveniently produce contents on public events, breaking news, and/or products. Subsequently, microblogging networks generate massive amounts of data that carry opinions and mass sentiment on various topics. Herein, microblogging is regarded as a useful platform for detecting and propagating new hot events. It is also a useful channel for identifying high-quality posts, popular topics, key interests, and high-influence users. The existence of noisy data in the traditional social media data streams enforces to focus on human-centric computing. This paper proposes a human-centric social computing (HCSC) model for hot-event detection and propagation in microblogging networks. In the proposed HCSC model, all posts and users are preprocessed through hypertext induced topic search (HITS) for determining high-quality subsets of the users, topics, and posts. Then, a latent Dirichlet allocation (LDA)-based multiprototype user topic detection method is used for identifying users with high influence in the network. Furthermore, an influence maximization is used for final determination of influential users based on the user subsets. Finally, the users mined by influence maximization process are generated as the influential user sets for specific topics. Experimental results prove the superiority of our HCSC model against similar models of hot-event detection and information propagation

Extending 3-DoF Metrics to Model User Behaviour Similarity in 6-DoF Immersive Applications

Immersive reality technologies, such as Virtual and Augmented Reality, have ushered a new era of user-centric systems, in which every aspect of the coding-delivery-rendering chain is tailored to the interaction of the users. Understanding the actual interactivity and behaviour of the users is still an open challenge and a key step to enabling such a user-centric system. Our main goal is to extend the applicability of existing behavioural methodologies for studying user navigation in the case of 6 Degree-of-Freedom (DoF). Specifically, we first compare the navigation in 6-DoF with its 3-DoF counterpart highlighting the main differences and novelties. Then, we define new metrics aimed at better modelling behavioural similarities between users in a 6-DoF system. We validate and test our solutions on real navigation paths of users interacting with dynamic volumetric media in 6-DoF Virtual Reality conditions. Our results show that metrics that consider both user position and viewing direction better perform in detecting user similarity while navigating in a 6-DoF system. Having easy-to-use but robust metrics that underpin multiple tools and answer the question "how do we detect if two users look at the same content?" open the gate to new solutions for a user-centric syste