Although, today, website design still contains many variable design elements which strongly influence its design outcome, like browser usage, platforms, user preferences, window size, connection speed, computer speed, colour support, software support, and font support, the original design idea still plays an important role. Emotion is difficult to measure or evaluate. Designers need to understand its importance and how to measure emotion efficiently in order to undertake the subsequent design stage. Positive emotions are as important as negative ones-positive emotions are critical to learning, curiosity, and creative thought, and today research is turning toward this dimension (Norman, 2004b: 19). To understand users' negative emotions can supply a better solution for design problems. Both users' likes and dislikes are important when exploring the role of emotional design. The fieldwork consisted of two pilot tests (the initial pilot test-I. P. T. and the second pilot test-S. P. T. ), a website impression test (W. I. T. ), and an improved website impression test (I. W. I. T. ). The research methods involved Think-Aloud usability testing, Emotional Probes testing (EPs testing), and questionnaires. In addition, the evaluation method used a coding system and statistics. Triangulation was used in making consistent the process methods and evaluation methods. The research outcomes include a fashion website design reference model, an insurance website design reference model, and the website impression test system. Through conducting the fieldwork, the importance of emotional design can be identified in the website design field. The whole research process and research outcomes supply one solution for researchers and designers to predict users' emotions in design outcomes.

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In social networks, analysing the explicit interactions among users can help in inferring hierarchical relationships and roles that may be implicit. In this thesis, we focus on two objectives: detecting hierarchical relationships between users and inferring the hierarchical roles of users interacting via the same online communication medium. In both cases, we show that considering the temporal dimension of interaction substantially improves the detection of relationships and roles. The first focus of this thesis is on the problem of inferring implicit relationships from interactions between users. Based on promising results obtained by standard link-analysis methods such as PageRank and Rooted-PageRank (RPR), we introduce three novel time-based approaches, \Time-F" based on a defined time function, Filter and Refine (FiRe) which is a hybrid approach based on RPR and Time-F, and Time-sensitive Rooted-PageRank (T-RPR) which applies RPR in a way that takes into account the time-dimension of interactions in the process of detecting hierarchical ties. We experiment on two datasets, the Enron email dataset to infer managersubordinate relationships from email exchanges, and a scientific publication coauthorship dataset to detect PhD advisor-advisee relationships from paper co-authorships. Our experiments demonstrate that time-based methods perform better in terms of recall. In particular T-RPR turns out to be superior over most recent competitor methods as well as all other approaches we propose. The second focus of this thesis is examining the online communication behaviour of users working on the same activity in order to identify the different hierarchical roles played by the users. We propose two approaches. In the first approach, supervised learning is used to train different classification algorithms. In the second approach, we address the problem as a sequence classification problem. A novel sequence classification framework is defined that generates time-dependent features based on frequent patterns at multiple levels of time granularity. Our framework is a exible technique for sequence classification to be applied in different domains. We experiment on an educational dataset collected from an asynchronous communication tool used by students to accomplish an underlying group project. Our experimental findings show that the first supervised approach achieves the best mapping of students to their roles when the individual attributes of the students, information about the reply relationships among them as well as quantitative time-based features are considered. Similarly, our multi-granularity pattern-based framework shows competitive performance in detecting the students' roles. Both approaches are significantly better than the baselines considered.

Context: Locating resources on the Web has become increasingly difficult for users and poses a number of issues. The sheer size of the Web means that despite what appears to be an increase in the amount of quality material available, the effort involved in locating that material is also increasing; in effect, the higher quality material is being diluted by the lesser quality. One such group affected by this problem is post-graduate students. Having only a finite amount of time to devote to research, this reduces their overall quality study time. Aim: This research investigates how post-graduate students use the Web as a learning resource and identifies a number of areas of concern with its use. It considers the potential for improvement in this matter by using a number of concepts such as: collaboration; peer reviewing and document classification and comparison techniques. This research also investigates whether by combining several of the identified technologies and concepts, student research on the Web can be improved. Method: Using some of the identified concepts as components, this research proposes a model to address the highlighted areas of concern. The proposed model, named the Durham Browsing Assistant (DurBA) is defined, and a number of key concepts which show potential within it are uncovered. One of the key concepts is chosen, that of document comparison. Given a source document, can a computer system reliably identify other documents which most closely match it from other on the Web? A software tool was created which allowed the testing of document comparison techniques, this was called the Durham Textual Comparison system (DurTeC) and it had two key concepts. The first was that it would allow various algorithms to be applied to the comparison process. The second concept was that it could simulate collaboration by allowing data to be altered, added and removed as if by multiple users. A set of experiments were created to test these algorithms and identify those which gave the best results. Results: The results from the experiments identified a number of the most promising relationships between comparison and collaboration processes. It also highlighted those which had a negative effect on the process, and those which produced variable results. Amongst the results, it was found that: 1. By providing DurTeC with additional source documents to the original, as if through a recommendation process, it was able to increase its accuracy substantially. 2. By allowing DurTeC to use synonym lists to expand its vocabulary, in many cases, it was found to have reduced its accuracy. 3. By restricting those words which DurTeC considered in its comparison process, based upon their value in the source document, accuracy could be increased. This could be considered as a form of collaborative keyword selection. Conclusion: This research shows that improvements can be made in the accuracy of identifying similar resources by using a combination of comparison and collaboration processes. The proposed model, DurBA would be an ideal host for such a system.

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Can a game help you write a meaningful story with others? Academic discussion of collaborative story-writing games usually contains reference to Surrealist game Exquisite Corpse, known to many as Consequences. In it, a game rule prohibits players, writing in turn, from reading most of the story written before their contribution. This rule promotes a fragmented form of narrative which, although often inventive and entertaining, does not often fulfil the normal requirements of a story. Is it possible to design a writing game with different rules that instead promote the production of a cohesive and meaningful story? In order to explore the possibilities of game-based story writing, the researcher developed two web-based games that formed the online platform Storyjacker (www.storyjacker.net). These were produced via an iterative design methodology which involved cyclical phases of software development and user testing. Design was also informed by a multi-disciplinary literature review and analysis of four other online writing platforms. Following the design phase, a selection of the stories that had been produced during Storyjacker testing were then rated and commented on by an expert reading panel, made up of creative writing academics and literary industry professionals. The panel’s ratings and comments informed a final analysis of the Storyjacker games as methods for creating meaningful stories. The research found that bespoke creative writing games do produce relatively meaningful stories. Plotlines in emerging stories motivate and entertain players through a joint sense of purpose. Writing games are also effective as a collaborative framework because they allow participants to work creatively together without feeling vulnerable in front of other players. However, the research finds that there are limits to the meaningfulness of stories written through games. By aligning gameplay with linear plot development, a feature of both Storyjacker games, there is no opportunity or motivation for players to go back and redraft stories. This, ultimately, has the most negative effect on story meaningfulness as this is the normal way that writers make sense of their stories. Entertaining game features, such as turn-based writing challenges, can also negatively impact story quality by distracting the writer from the overall storytelling task. Complicating the debate on meaningfulness, the thesis also finds that texts written by games typically contain two discernable narratives: the story narrative and a description of the event of playing the game. This both enriches the text and makes it more difficult readers to decode as a meaningful story. Further practice-led research is needed to explore ways in which story games could incorporate a drafting process. This could significantly improve the meaningfulness of stories produced in this way. In the broader context of design, successful features in the Storyjacker games should be trialled in other digital interfaces to see if they help users perform other creative or subjective tasks. Finally, more research should be conducted on the effects of these collaborative games in broader educational, creative and organisational contexts.

Compared to information systems that work the same for all users and contexts, systems that utilise contextual information have greater potential to help a user identify relevant information more quickly and more accurately. Contextual information comes in a variety of flavours, often derived from records of past interactions between a user and the information system. It can be individual- or group-based. The motivation for our work is as follows. First, instead of looking at Web searching or browsing, which has been studied extensively, we focus our attention on Web sites. Such collections can be notoriously difficult to search or explore. If we could learn from past user interactions what information needs can be satisfied by which -documents, we would be in a position to help a new user to get to the required information much more rapidly. Hence, we harness the search behaviour of cohorts of users instead of individual users, turning it automatically into a profile which can then be used to assist other users of the same cohort. Finally, we are interested in exploring how such a profile is best utilised for profile-based summarisation of the collection at hand in a navigation scenario in which such summaries can be displayed as hover text as a user moves the mouse over a link. The process of acquiring the profile is not a research interest here; we simply adopt a biologically inspired method that resembles the idea of ant colony optimisation (AGO). This has been shown to work well in a variety of application areas. The model can be built in a continuous learning cycle that exploits search patterns as recorded in typical query log files. The main focus of this thesis will be on using the model in profile-based summarisation to generate summaries of documents for navigation support. Our research explores different single-document and multi- document summarisation techniques, some of which use the profile and some of which do not. We perform task-based evaluations of these different techniques - and hence of the impact of the profile and profile-based summarisation - in the context of Web site navigation. The experimental results demonstrate that profile-based summarisation to assist users in navigation tasks can significantly outperform generic summarisation as well as a standard Web site without such assistance.

The Web is being transformed into an open data commons, and is now the dominant point of access for information seeking scientists. In parallel the scientific community has been required to manage the challenges of "Big Data" - characterized by its large-scale, distributed, and diverse nature. The Web of Linked Data has emerged as a platform through which the sciences can meet this challenge, allowing them to publish and reuse data in a machine readable manner. The openness of the Web of Data is however a double-edged sword. On one hand it drives a rapid growth of adoption, but on the other a lack of governance and quality control has led to data of varied quality and trustworthiness. The challenge scientists face then is not that data on the Web is universally poor, but that the quality is unknown. Previous research has established the notion of Quality Knowledge, latent domain knowledge possessed by expert scientists to make quality based decisions. The main idea pursued in this thesis is that we can address Information Quality (IQ) issues in the Web of Data by repurposing these existing mechanisms scientists use to evaluate data. We argue that there are three distinct aspects of Quality Knowledge, objective, predictive, and subjective, defined by information required for their assessment, and present two studies focused on the modelling and exploitation of the objective and predictive aspects. We address the objective aspect by developing the Minimum Information Model as a repurposing of Minimum Information Checklists, an increasingly prevalent type of quality knowledge employed in the Life Sciences. A more general approach to modelling the predictive aspect explores the use of Multi-Entity Bayesian Networks to tackle the characteristic uncertainty in predictive quality knowledge, and the inconsistent availability of metadata in the Web of Data. We show that by following our classification we can develop techniques and infrastructure to successfully evaluate IQ that are tailored to the challenges of the Web of Data, and informed by the needs of the scientific community.

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Augmented Reality systems, which overlay virtual information over the real world, can benefit greatly from the techniques established by the Open Hypermedia research field. Storing information and links separately from a document can be advantageous for augmented reality applications and can enable the adaption of content to suit users’ preferences. This thesis explores how Open Hypermedia systems might be used as the information systems behind AR environments. This provides benefits to augmented reality developers, not only because of the existing Open Hypermedia methods but also because of the applicability of Open Hypermedia interaction techniques to the augmented reality domain. Tangible augmented reality techniques, in which graphics are overlaid on physical objects that can be manipulated as input devices, can be used to interact with the resulting information spaces by exposing the adaptation processes in the Open Hypermedia systems. This thesis describes the development of various physical interaction metaphors that allow users to physically manipulate the underlying hypermedia structures to their liking, resulting in a natural and intuitive way to navigate complex information spaces.