This thesis investigates how web agencys in Stockholm use, value and incoroprate the terms usability, user experience and interaction design in their work process. The purpose of this study is to investigate how creative professionals works with the notions of usability, user experience and interaction design with focus on the end user. Our definition of creative professionals is every employee at a web agency involved in the work process of developing digital artefacts in any capacity. We wanted to investigate how these notions are considered, consciously or unconsciously, during the workprocess. Semi-structured interviews were conducted at three different web agencys with eight different employees. The result of the study has shown that all web agencys have a constant focus on the end-user during the entire development of digital artefacts towards their customers.This focus is kept during the whole process, from the development of a concept based on knowledge on both the customer and the end-users, until the release of the end-product. The work and design methods differs between the different web agencys in which way they incorporate end-users in the process.

Like many other transportation agencies, the Ministry of Transportation Ontario (MTO) is also using the same work zone closure strategies and standards that it has used for decades. However, the lane closure strategies should incorporate the impacts of construction duration and inconvenience to the road users and find the balance where users face minimal inconvenience while contractors have the appropriate amount of time to finish the work and produce a high quality product. In-order to evaluate and assess the appropriate time for lane closures, it is important to estimate the capacity of the lanes. The capacity estimates can help in determining the optimized time for lane closures to minimize the user delays while providing sufficient time for contractors to achieve the desired productivity and quality of work. There are different models, computer Software and wide variety of studies to evaluate and estimate the Workzone Capacity and associated User Delay Costs at workzones. These costs are primarily affected by traffic flows, vehicle speeds, and work zone capacities. In-view of the above, this study is designed to estimate freeway capacity of construction workzones and discuss the associated user delay costs and economic issues. For this study, the capacity at the work zones was measured as the mean queue discharge flow rate during forced-flow conditions. Forced-flow conditions were defined as congested conditions during which a sustained queue formed. There are several studies and approaches for collecting traffic volume data for estimating workzone capacity. For this study, it was decided to utilize a manual counting method for volume data. This would help provide the visual confirmation of queuing and intensity of work activity at workzones. Six sites located in Southern Ontario, were selected for this study. The data from these sites is used to develop a mathematical model for estimating workzone capacity for Ontario.

User Authentication is the process of establishing confidence in the User identities presented to an information system. This thesis establishes a method of assigning a confidence level to the output of a user authentication process based on what attacks and threats it is vulnerable to. Additionally, this thesis describes the results of an analysis where the method was performed on several different authentication systems and the confidence level in the authentication process of these systems determined. Final conclusions found that most systems lack confidence in their ability to authenticate users as the systems were unable to operate in the face of compromised authenticating information. Final recommendations were to improve on this inadequacy, and thus improve the confidence in the output of the authentication process, through the verification of both static and dynamic attributes of authenticating information. A system that operates confidently in the face of compromised authenticating information that utilizes voice verification is described demonstrating the ability of an authentication system to have complete confidence in its ability to authenticate a user through submitted data.

Usable privacy and security has become a significant area of interest for many people in both industry and academia. A better understanding of the knowledge and motivation is an important factor in the design of privacy and security tools. However, users of these tools are a heterogeneous group, and many past studies of user characteristics in the security and privacy domain have looked only at a small subset of factors to define differences between groups of users. The goal of this research is to critically look at the difference between people, their opinions and habits when it comes to issues of privacy and security. To address this goal, 32 in-depth qualitative interviews were conducted and analyzed to look at the heterogenous nature of this community. The participant’s attitudes and actions around the dimensions of knowledge about tools and of motivation for self-protection were used to cluster participants. The traits of these participant clusters are used to create a set of privacy and security personas, or prototypical privacy and security tool users. These personas are a tool for incorporating a broader understanding of the diversity of users into the design of privacy and security tools.

This thesis investigates ways to reduce or eliminate the necessity of user input to learning-based personal email spam filters. Personal spam filters have been shown in previous studies to yield superior effectiveness, at the cost of requiring extensive user training which may be burdensome or impossible. This work describes new approaches to solve the problem of building a personal spam filter that requires minimal user feedback. An initial study investigates how well a personal filter can learn from different sources of data, as opposed to user’s messages. Our initial studies show that inter-user training yields substantially inferior results to intra-user training using the best known methods. Moreover, contrary to previous literature, it is found that transfer learning degrades the performance of spam filters when the source of training and test sets belong to two different users or different times. We also adapt and modify a graph-based semi-supervising learning algorithm to build a filter that can classify an entire inbox trained on twenty or fewer user judgments. Our experiments show that this approach compares well with previous techniques when trained on as few as two training examples. We also present the toolkit we developed to perform privacy-preserving user studies on spam filters. This toolkit allows researchers to evaluate any spam filter that conforms to a standard interface defined by TREC, on real users’ email boxes. Researchers have access only to the TREC-style result file, and not to any content of a user’s email stream. To eliminate the necessity of feedback from the user, we build a personal autonomous filter that learns exclusively on the result of a global spam filter. Our laboratory experiments show that learning filters with no user input can substantially improve the results of open-source and industry-leading commercial filters that employ no user-specific training. We use our toolkit to validate the performance of the autonomous filter in a user study.

Game reviews play an important role in both the culture and business of games the words of a reviewer can have an influential effect on the commercial success of a video game. While reviews are currently used by game developers to aid in important decisions such as project financing and employee bonuses, the effect of game reviews on players is not known. Additionally, the use of game reviews to improve evaluation techniques has received little attention. In this thesis we investigate the effect of game reviews on player experience and perceptions of quality. We show that negative reviews cause a significant effect on how players perceive their in-game experience, and that this effect is a post-play cognitive rationalization of the play experience with the previously-read review text. To address this effect we designed and deployed a new heuristic evaluation technique that specifically uses game reviews to create a fine-grained prioritized list of usability problems based on the frequency, impact, and persistence of each problem. By using our technique we are able to address the most common usability problems identified by game reviews, thus reducing the overall level of negativity found within the review text. Our approach helps to control and eliminate the snowballing effect that can be produced by players reading reviews and subsequently posting their own reviews, and thus improve the commercial success of a game.

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Smartphones have become essential to modern people. More and more consumers are using smartphones. However, according to many reports and investigation, they indicate that user satisfaction and brand loyalty will differ from various brands and represent significant differences. This research adopted Bhattacherjee¡¦s (2001) ECT-IS model as the basic research framework to examine relationships among expectation confirmation, user satisfaction, perceived usefulness and brand loyalty of the smartphones. The model was further extended by measuring perceived usefulness with functional, experiential, and symbolic brand benefits proposed by Park, Jaworski & MacInnis (1986) to investigate how they influenced user satisfaction and brand loyalty. The results include the following: 1. Expectation confirmation had a significant impact on user satisfaction and perceived usefulness. 2. User satisfaction had a positive effect on brand loyalty. 3. Different effects on user satisfaction and brand loyalty were found among three smartphone brands, Apple, Samsung, and hTC.

The past few years have seen the rapid rise of all things “social” on the web from the growth of online social networks like Facebook, to real-time communication services like Twitter, to user-contributed content sites like Flickr and YouTube, to content aggregators like Digg. Beyond these popular Web 2.0 successes, the emer- gence of Social Information Systems is promising to fundamentally transform what information we encounter and digest, how businesses market and engage with their customers, how universities educate and train a new generation of researchers, how the government investigates terror networks, and even how political regimes interact with their citizenry. Users have moved from being passive consumers of information (via querying or browsing) to becoming active participants in the creation of data and knowledge artifacts, actively sorting, ranking, and annotating other users and artifacts. This fundamental shift to social systems places new demands on providing de- pendable capabilities for knowing whom to trust and what information to trust, given the open and unregulated nature of these systems. The emergence of large-scale user participation in Social Information Systems suggests the need for the development of user-centric approaches to information quality. As a step in this direction this research proposes an interaction-based approach for modeling the notion of user im- portance. The interaction-based model is centered around the uniquely social aspects of these systems, by treating who communicates with whom (an interaction) as a core building block in evaluating user importance. We first study the interaction characteristics of Twitter, one of the most buzzworthy recent Social Web successes, examining the usage statistics, growth patterns, and user interaction behavior of over 2 million participants on Twitter. We believe this is the first large-scale study of dynamic interactions on a real-world Social Information System. Based on the anal- ysis of the interaction structure of Twitter, the second contribution of this thesis research is an exploration of approaches for measuring user importance. As part of this exploration, we study several different approaches that build on the inherent interaction-based framework of Social Information Systems. We explore this model through an experimental study over an interaction graph consisting of 800,000 nodes and about 1.9 million interaction edges. The user importance modeling approaches that we present can be applied to any Social Information System in which interactions between users can be monitored.

Users are being embraced as partners in developing computer services in many current computer supported cooperative work systems. Many web-based applications, including collaborative authoring tools like wikis, place users into collaborations with unknown and distant partners. Individual participants in such environments need to identify and understand others' contributions for collaboration to succeed and be efficient. One approach to supporting such understanding is to record user activity for later access. Issues with this approach include difficulties in locating activity of interest in large tasks and the history is often recorded at a system-activity level instead of at a human-activity level. To address these issues, this dissertation introduces CoActIVE, an application-independent history mechanism that clusters records of user activity and extracts keywords in an attempt to provide a human-level representation of history. CoActIVE is integrated in three different software applications to show its applicability and validity. Multiple visualization techniques based on this processing are compared in their ability to improve users' location and comprehension of the activity of others. The results show that filmstrip visualization and visual summarization of user activity show significant improvement over traditional list view interfaces. CoActIVE generates an interpretation of large-scale interaction history and provides the interpretation thorough a variety of visualizations that allow users to navigate the evolution of collaborative work. It supports branching history, with the understanding that asynchronous authoring and design tasks often involve the parallel development of alternatives. Additionally, CoActIVE has the potential to be integrated into a variety of applications with little adjustment for compatibility. Especially, the comparison of visualizations for locating and comprehending the work of others is unique.