Co-viewing TV with Twitter: more interesting than the shows?

Social media services, and Twitter in particular, are changing the way in which many people consume traditional broadcast media. Real-time backchannel conversations are now common-place as audiences simultaneously watch TV whilst using Twitter to broadcast their own thoughts, sentiments, opinions and emotions related to what they are watching. This individual behavior, when aggregated, results in a new social experience comprising of mass, real-time, coconsumption of TV services that has, thus far, been neither recognized nor investigated by the HCI community nor the broadcast industry. This paper describes a work-in-progress which aims to understand user behaviour in this burgeoning area and provides some preliminary analysis of viewers’ Twitter activity surrounding the popular UK TV show, The X Factor

Evaluating Engagement in Digital Narratives from Facial Data

Engagement researchers indicate that the engagement level of people in a narrative has an influence on people's subsequent story-related attitudes and beliefs, which helps psychologists understand people's social behaviours and personal experience. With the arrival of multimedia, the digital narrative combines multimedia features (e.g. varying images, music and voiceover) with traditional storytelling. Research on digital narratives has been widely used in helping students gain problem-solving and presentation skills as well as supporting child psychologists investigating children's social understanding such as family/peer relationships through completing their digital narratives. However, there is little study on the effect of multimedia features in digital narratives on the engagement level of people. This research focuses on measuring the levels of engagement of people in digital narratives and specifically on understanding the media effect of digital narratives on people's engagement levels. Measurement tools are developed and validated through analyses of facial data from different age groups (children and young adults) in watching stories with different media features of digital narratives. Data sources used in this research include a questionnaire with Smileyometer scale and the observation of each participant's facial behaviours

Learning Intelligent Dialogs for Bounding Box Annotation

We introduce Intelligent Annotation Dialogs for bounding box annotation. We train an agent to automatically choose a sequence of actions for a human annotator to produce a bounding box in a minimal amount of time. Specifically, we consider two actions: box verification, where the annotator verifies a box generated by an object detector, and manual box drawing. We explore two kinds of agents, one based on predicting the probability that a box will be positively verified, and the other based on reinforcement learning. We demonstrate that (1) our agents are able to learn efficient annotation strategies in several scenarios, automatically adapting to the image difficulty, the desired quality of the boxes, and the detector strength; (2) in all scenarios the resulting annotation dialogs speed up annotation compared to manual box drawing alone and box verification alone, while also outperforming any fixed combination of verification and drawing in most scenarios; (3) in a realistic scenario where the detector is iteratively re-trained, our agents evolve a series of strategies that reflect the shifting trade-off between verification and drawing as the detector grows stronger.Comment: This paper appeared at CVPR 201

Narrative Generation in Entertainment: Using Artificial Intelligence Planning

From the field of artificial intelligence (AI) there is a growing stream of technology capable of being embedded in software that will reshape the way we interact with our environment in our everyday lives. This ‘AI software’ is often used to tackle more mundane tasks that are otherwise dangerous or meticulous for a human to accomplish. One particular area, explored in this paper, is for AI software to assist in supporting the enjoyable aspects of the lives of humans. Entertainment is one of these aspects, and often includes storytelling in some form no matter what the type of media, including television, films, video games, etc. This paper aims to explore the ability of AI software to automate the story-creation and story-telling process. This is part of the field of Automatic Narrative Generator (ANG), which aims to produce intuitive interfaces to support people (without any previous programming experience) to use tools to generate stories, based on their ideas of the kind of characters, intentions, events and spaces they want to be in the story. The paper includes details of such AI software created by the author that can be downloaded and used by the reader for this purpose. Applications of this kind of technology include the automatic generation of story lines for ‘soap operas’

Towards a Video Consumer Leaning Spectrum: A Medium-Centric Approach

Purpose: As TV and digital video converge, there is a need to compare advertising effectiveness, advertising receptivity, and video consumption drivers in this new context. Considering the emerging viewing practices and underlying theories, this study examines the feasibility of the traditional notion of differentiating between lean-back (LB) and lean-forward (LF) media, and proposes a revised approach of addressing video consumption processes and associated advertising effectiveness implications. Methodology: An extensive, systematic literature review examines a total of 715 sources regarding current lean-back/lean-forward media research and alternative approaches as by (1) basic terminologies, (2) limitations of lean-back/lean-forward situations, (3) advertising effectiveness implications, (4) video-specific approaches. Findings/Contribution: Key differences between lean-back and lean-forward video consumption are presented. A conceptual integration of video ad receptivity/effectiveness drivers is proposed to guide future media and marketing research and practice. Video consumption today is no longer lean-back or lean-forward, but a “leaning spectrum” with two dimensions: leaning direction and leaning degree. Designing video content today requires focusing on consumption drivers and platform synergies for owning the “leaning spectrum”

Understanding user experience of mobile video: Framework, measurement, and optimization

Since users have become the focus of product/service design in last decade, the term User eXperience (UX) has been frequently used in the field of Human-Computer-Interaction (HCI). Research on UX facilitates a better understanding of the various aspects of the user’s interaction with the product or service. Mobile video, as a new and promising service and research field, has attracted great attention. Due to the significance of UX in the success of mobile video (Jordan, 2002), many researchers have centered on this area, examining users’ expectations, motivations, requirements, and usage context. As a result, many influencing factors have been explored (Buchinger, Kriglstein, Brandt & Hlavacs, 2011; Buchinger, Kriglstein & Hlavacs, 2009). However, a general framework for specific mobile video service is lacking for structuring such a great number of factors. To measure user experience of multimedia services such as mobile video, quality of experience (QoE) has recently become a prominent concept. In contrast to the traditionally used concept quality of service (QoS), QoE not only involves objectively measuring the delivered service but also takes into account user’s needs and desires when using the service, emphasizing the user’s overall acceptability on the service. Many QoE metrics are able to estimate the user perceived quality or acceptability of mobile video, but may be not enough accurate for the overall UX prediction due to the complexity of UX. Only a few frameworks of QoE have addressed more aspects of UX for mobile multimedia applications but need be transformed into practical measures. The challenge of optimizing UX remains adaptations to the resource constrains (e.g., network conditions, mobile device capabilities, and heterogeneous usage contexts) as well as meeting complicated user requirements (e.g., usage purposes and personal preferences). In this chapter, we investigate the existing important UX frameworks, compare their similarities and discuss some important features that fit in the mobile video service. Based on the previous research, we propose a simple UX framework for mobile video application by mapping a variety of influencing factors of UX upon a typical mobile video delivery system. Each component and its factors are explored with comprehensive literature reviews. The proposed framework may benefit in user-centred design of mobile video through taking a complete consideration of UX influences and in improvement of mobile videoservice quality by adjusting the values of certain factors to produce a positive user experience. It may also facilitate relative research in the way of locating important issues to study, clarifying research scopes, and setting up proper study procedures. We then review a great deal of research on UX measurement, including QoE metrics and QoE frameworks of mobile multimedia. Finally, we discuss how to achieve an optimal quality of user experience by focusing on the issues of various aspects of UX of mobile video. In the conclusion, we suggest some open issues for future study

Enhancing fan experience during live sports broadcasts through second screen applications

When sports fans attend live sports events, they usually engage in social experiences with friends, family members and other fans at the venue sharing the same affiliation. However, fans watching the same event through a live television broadcast end up not feeling so emotionally connected with the athletes and other fans as they would if they were watching it live, together with thousands of other fans. With this in mind, we seek to create mobile applications that deliver engaging social experiences involving remote fans watching live broadcasted sports events. Taking into account the growing use of mobile devices when watching TV broadcasts, these mobile applications explore the second screen concept, which allows users to interact with content that complements the TV broadcast. Within this context, we present a set of second screen application prototypes developed to test our concepts, the corresponding user studies and results, as well as suggestions on how to apply the prototypes’ concepts not only in different sports, but also during TV shows and electronic sports. Finally, we also present the challenges we faced and the guidelines we followed during the development and evaluation phases, which may give a considerable contribution to the development of future second screen applications for live broadcasted events

Evaluation of Future Mobile Services Based on the Technology Acceptance Model

Mobile telecommunication operators are under great pressure to launch new profitable data services. However, most of the mobile data services have fallen short of the expectation and have failed on the market. One important reason for the failure of mobile data services is the difficulty to assess user needs and requirements in advance. This paper suggests to use the Technology Acceptance Model (TAM) to approximate the user acceptance of non-existing mobile services. The TAM model is applied to assess the potential future acceptance of five mobile broadcasting service scenario. The results show that TAM is a helpful model to evaluate the user acceptance of future services. However, the more innovative the new service is, the less accurate is the model. The results show furthermore that the most influential aspect on the future intention to use is the perceived value of the future prod

Online users' behaviours and behavioural intentions with reference to live streaming : a thesis presented in partial fulfilment of the requirements for the degree of Doctor of Philosophy at Massey University, Albany, New Zealand. EMBARGOED until 26 March 2023.

Embargoed until 26 March 2023Live streaming, as a new medium, allows users to participate in real-time interaction. It has attracted a large number of online users, and become a new social commerce venue and lucrative business, especially in China where the live streaming industry is growing explosively and is the largest in the world. This thesis aims to comprehensively investigate users’ behaviours and behavioural intentions in live streaming through both qualitative and quantitative approaches using the Chinese live streaming as an example. This thesis contains four studies to investigate from both streamers’ and viewers’ aspects. Firstly, we conducted two qualitative studies to investigate users’ online behaviours in the social commerce practice in live streaming by exploring how streamers attract viewers (Chapter 2) and encourage gifting (Chapter 3). Novel multiple triangulation was used, including data source triangulation and methodological triangulation. Through multiple triangulation, three behaviours for viewer attraction and four behaviours for gifting encouragement were identified. These two chapters help to comprehensively understand streamers’ online behaviours in this new form of social commerce. Next, we conducted two quantitative studies to explore why viewers continue to watch streams (Chapters 4 and 5). Based on expectation-confirmation theory (ECT), in Chapter 4, we modified the post-acceptance model of information system continuance and re-defined the constructs in a structural equation model of predictors of continuance intention of watching live streams. Chapter 4 successfully connects intention and continuance intention of watching, and integrates disparate understandings of viewers’ watching behaviours. To solve the deficiencies identified in current ECT-based models and further increase the explanation of variance in continuance intention of watching, in Chapter 5, we proposed a value-based continuance intention model (V-ECM), which theoretically extends ECT-based studies by including a process of overall practical assessment between users’ perceived benefits and perceived sacrifices. V-ECM appears to be a better model for explaining users’ continuance intention in the stream-watching context. Also, V-ECM could be used broadly in online and/or technology-related fields. Overall, this thesis comprehensively investigates both streamers’ and viewers’ behaviours and behavioural intentions in live streaming. Insights from this thesis can improve the design, functions and marketing within live streaming platforms. Also, this thesis provides strong foundations for further online behaviour studies, for example, stream-watching addiction