Denna explorativa studie analyserar gemensamma och differentiella mönster för kommunikation och beteende hos användare i Hjälpforum. Målet med studien är att kartlägga aktiva användartyper med syfte att ge SVT kunskap om Hjälpforumets användare. Om forumadministratörer har mer kunskap om användarna i Hjälpforum kan de anpassa sin kommunikation utifrån användarnas individuella behov och öka deras förmåga att bidra med mer kvalitativ återkoppling. Detta kan i sin tur bidra till en positivare inställning och ökat förtroende hos användare i Hjälpforum. I denna studie kunde fem användartyper kartläggas i Hjälpforum med stöd av egen empiri och tidigare forskning. Nybörjare utgör främsta användartypen i Hjälpforum och SVT bör därför tillgodose deras behov för att eventuellt minska antalet nya användarinlägg. Dessutom kunde denna studie med hjälp av lämpliga databearbetningsverktyg kartlägga, en för tillfället, okänd användartyp i Hjälpforum utifrån ovanliga mönster i beteende och kommunikation vilket kan vara intressant för vidare analys. Studien presenterar förslag på hur resultatet kan användas för att skapa riktlinjer för framtida kommunikation och utveckling av Hjälpforum och SVT:s webbplats. / This exploratory study analyzes the common and differential patterns of communication and behavior of users in Help Forum. The goal of the study is to map the active user types with the aim of providing SVT knowledge of the Help Forum users. If the forum administrators have more knowledge of the users in the forum, they can adapt their communication based on the individual needs and enhance their ability to contribute more qualitative feedback. This may in turn contribute to a more positive attitude and greater confidence among users in Help Forum. In this study, five types of users could be identified in the Forum with the support of its own empirical data and previous research. Beginners are primary user type in the forum and SVT should cater to their needs in order to possibly reduce the number of new user posts. Furthermore, this study using appropriate data processing tool map, one for the moment, unknown user type in the forum by unusual patterns of behavior and communication which may be of interest for further analysis. The study presents suggestions on how the results can be used to create guidelines for future communication and development of Help Forum and SVT's website.

A challenge in Human-Robot Interaction is tailoring the social skills of robot companions to match those expected by individual humans during their rst encounter. Currently, large amounts of user data are needed to con gure robot companions with these skills. This creates the need of running long-term Human-Robot Interaction studies in domestic environments. A new approach using personas is explored to alleviate this arduous data collection task without compromising the level of interaction currently shown by robot companions. The personas technique was created by Alan Cooper in 1999 as a tool to de ne user archetypes of a system in order to reduce the involvement of real users during the development process of a target system. This technique has proven bene cial in Human-Computer Interaction for years. Therefore, similar bene ts could be expected when applying personas to Human-Robot Interaction. Our novel approach de nes personas as the key component of a computational behaviour model used to adapt robot companions to individual user's needs. This approach reduces the amount of user data that must be collected before a Human-Robot Interaction study, by associating new users to pre-de ned personas that adapt the robot behaviours through their integration with the computational behaviour model. At the same time that the current robot social interaction level expected by humans during the rst encounter is preserved. The University of Hertfordshire Robot House provided the naturalistic domestic environment for the investigation. After incorporating a new module, an Activity Recognition System, to increase the overall context-awareness of the system, a computational behaviour model will be de ned through an iterative research process. The initial de nition of the model was evolved after each experiment based on the iii ndings. Two successive studies investigated personas and determined the steps to follow for their integration into the targeted model. The nal model presented was de ned from users' preferences and needs when interacting with a robot companion during activities of daily living at home. The main challenge was identifying the variables that match users to personas in our model. This approach open a new discussion in the Human-Robot Interaction eld to de ne tools that help reduce the amount of user data requiring collection prior to the rst interaction with a robot companion in a domestic environment. We conclude that modelling people's preferences when interacting with robot companions is a challenging approach. Integrating the Human-Computer Interaction technique into a computational behaviour model for Human-Robot Interaction studies was more di cult than anticipated. This investigation shows the advantages and disadvantages of introducing this technique into Human-Robot Interaction, and explores the challenges in de ning a personas-based computational behaviour model. The continuous learning process experienced helps clarify the steps that other researchers in the eld should follow when investigating a similar approach. Some interesting outcomes and trends were also found among users' data, which encourage the belief that the personas technique can be further developed to tackle some of the current di culties highlighted in the Human-Robot Interaction literature.

This thesis describes research on methods for Ubiquitous/Pervasive Computing to better suit users in an Intelligent Environment. The approach is to create and equip a computing environment, such as our Active Office, with technologies that can identify user needs and meet these need in a timely, efficient and unobtrusive manner.¶ The critical issues in the Intelligent Environment are how to enable transparent, distributed computing to allow continued operation across changing circumstances and how to exploit the changing environment so that it is aware of the context of user location, the collection of nearby people and objects, accessible devices and changes to those objects over time.¶ Since the Intelligent Environment is an environment with rapid and rich computing processing, the distributed context processing architecture (DiCPA) was developed to manage and respond to rapidly changing aggregation of sensor data. This architecture is a scalable distributed context processing architecture that provides: 1. continued operation across changing circumstances for users, 2. the collection of nearby people and objects, 3. accessible devices and 4. the changes to those objects over time in the environment. The DiCPA approach focuses on how the Intelligent Environment provides context information for user location, user mobility and the user activity model. Users are assumed mobile within the Intelligent Environment and can rapidly change their access to relevant information and the availability of communications and computational resources.¶ Context-Aware Computing is a new approach in software engineering for Intelligent Environment. It is an approach in the design and construction of a context-aware application that exploits rapid changes in access to relevant information and the availability of communication and computing resources in the mobile computing environment. The goal of Context-Aware Computing is to make user interaction with the computer easier in the smart environment where technology is spread throughout (pervasive), computers are everywhere at the same time (ubiquitous) and technology is embedded (ambient) in the environment. Context-aware applications need not be difficult, tedious or require the acquisition of new skills on the part of the user. They should be safe, easy, simple to use and should enable new functionality without the need to learn new technology. They should provide relevant information and a simple way for a user to manage.¶ The Intelligent Environment requires a context-aware application to improve its efficiency and to increase productivity and enjoyment for the user. The context awareness mechanism has four fundamental cores i.e. identity (who), activity (what), location (where) and timestamp (when). Based on DiCPA architecture, the model of user location (where), user mobility (where), user activity (what) and Intelligent Environment response (what) were developed. Prototypes were also developed to proof the Context-Aware Computing concept in the Intelligent Environment.¶ An Intelligent Environment uses the multi-disciplinary area of Context-Aware Computing, which combines technology, computer systems, models and reasoning, social aspects, and user support. A “good quality” project for Context-Aware Computing requires core content and provides iterative evaluation processes, which has two types of iteration: design and product iteration of the evaluation. The aim of the development of an evaluation program in Context-Aware Computing is to determine what to test, how to test and the appropriate metrics to use. This work presents the metrics for a good quality project in the Context-Aware Computing area, which is followed by the evaluation of the prototypes of this work.

This diploma thesis aims to explore the increasing activity of internet users who intensively create, publish and spread their own content. The majority of this content is related to news and traditional forms of mass media organizations, which now must contend with the new means in which to disseminate information. The theoretical portion of this thesis describes the development of network media and strives for ground active user participation in media discourse and a historical context. Kinds of user-created contents will be introduced, defining their characteristics and analyzes these users who are called "prosumers" or "produsers" in the Web 2.0 era. Attention is also focused on user-generated content accessed by news websites and citizen journalism. The second part analyzes how the foremost world news media use and benefit from user-generated content. Examined media are iReport CNN, uReport Fox News and Have Your Say BBC. The text also analyzes the Czech news media, especially ČT24 news channel and main Czech news websites. The thesis closes with a comparison between Czech and world media and offers analysis of different media organizations approaches to user-generated content. Both parts of the thesis focus on web and television news service.

Η έλλειψη της δραστηριότητας του χρήστη σχετικά με τα αποτελέσματα της αναζήτησης μέχρι πρόσφατα θεωρείτο ως ένδειξη της δυσαρέσκειας του από την απόδοση ανάκτησης, και συχνά τέτοια αδράνεια χαρακτήριζε την αναζήτηση ως αποτυχημένη (negative search abandonment). Ωστόσο, πρόσφατες μελέτες δείχνουν ότι ορισμένες αναζητήσεις μπορούν να ικανοποιηθούν από το περιεχόμενο των αποτελεσμάτων που παρουσιάζονται στον χρήστη, χωρίς να χρειάζεται να κάνει κλικ σε κάποιο από τα ανακτημένα αποτελέσματα (positive search abandonment), και έτσι τονίζεται η ανάγκη να γίνουν διακρίσεις μεταξύ των επιτυχημένων και αποτυχημένων αναζητήσεων που δεν ακολουθούνται από κλικς. Με αυτή την εργασία προτείνουμε τον σχεδιασμό και την υλοποίηση μιας μεθοδολογίας αξιολόγησης της ικανοποίησης του χρήστη από τα αποτελέσματα αναζητήσεων που δεν ακολουθούνται από επισκέψεις στο περιεχόμενο των δεδομένων ανάκτησης. Για την επίτευξη του στόχου αυτού διενεργήσαμε μελέτη χρηστών που διερευνά τις προθέσεις των χρηστών πίσω από ερωτήματα που δεν ακολουθούνται από επίσκεψη σε κάποιο από τα αποτελέσματα που επέστρεψε η αναζήτηση και εξετάζει τις εργασίες αναζήτησης που μπορούν να ολοκληρωθούν με επιτυχία βασισμένες εξ ολοκλήρου στις πληροφορίες που παρέχονται στη σελίδα με τα αποτελέσματα. Επιπρόσθετα, μελετήθηκαν και υλοποιήθηκαν εργαλεία, QWC Browser, για την καταγραφή της δραστηριότητας του χρήστη με συστήματα ανάκτησης πληροφορίας από τον Παγκόσμιο Ιστό. Στηριζόμενοι στην ευρέως αποδεχόμενη ιδέα της χρήσης της δραστηριότητας του χρήστη ως δείκτη υπονοούμενης αξιολόγησης συσχέτισης (implicit relevance judgments), εξετάσαμε την ύπαρξη σχέση μεταξύ των ρητών δηλώσεων (explicit judgments) ικανοποίησης του χρήστη και μετρικών αξιολόγησης της υπονοούμενης ανατροφοδότησης (implicit measures) του χρήστη. Τέλος, χρησιμοποιήσαμε τεχνικές μοντελοποίησης για την ανάπτυξη μοντέλων πρόβλεψης για την σύλληψη της ικανοποίησης του χρήστη από τις αναζητήσεις που δεν ακολουθούνται από κλικς. / The lack of user activity on search results was until recently perceived as a sign of user dissatisfaction from retrieval performance, often, referring to such inactivity as a failed search (negative search abandonment). However, recent studies suggest that some search tasks can be achieved in the contents of the results displayed without the need to click through them (positive search abandonment); thus they emphasize the need to discriminate between successful and failed searches without follow-up clicks. In this paper we propose to design and implement a methodology for assessing user satisfaction from the results of searches that are not followed by visits to the content of the retrieved results. To achieve this goal we conducted a user study in order to identify the search intentions of queries without follow-up clicks to any of the results returned by the search and identify the search tasks that can be accomplished successfully based entirely on information provided on the results page. Additionally, we developed an instrumented browser, QWC Browser, to collect a variety of measures of user activity after the query submittion. Moreover, we examined whether there is an association between explicit judgments of user satisfaction and implicit measures of user interest in order to understand what implicit measures were most strongly associated with user satisfaction. Finally, we used Bayesian modeling techniques to develop predictive models, to capture user satisfaction from searches that are not followed by clicks to the retrieved results.

For the past decade, there has been many innovations made to the mobile phone and new features such as payments have been added to the mobile phone’s capabilities. East Africa is the region with the fastest uptake and highest adoption rates of mobile money in the world. Despite the success, the amount of active users of mobile money is still low in comparison to the number of registered users. The purpose of this master thesis is to analyze what mobile money providers should consider when trying to drive activity from the already registered user base. The main theoretical concept that was used is resource-based view and the analytical framework is an importance-effort matrix. The empirical study consisted of in-depth interviews with key experts and stakeholders from the mobile money industry. Most of the interviews were face-to-face interviews during a research trip to Kenya, Uganda and Tanzania. The findings were then reviewed during the Mobile Money Africa 2014 conference in South Africa. This thesis has identified a number of reasons for low user activity of the registered user base together with strategies that has the potential to tackle them. In order to drive activity, it is important for the service provider to understand and consider what that is desired and required to possess in terms of tangible, intangible and human resources to be able to successfully implement and run the identified strategies. The study concludes that tangible resources (physical and financial resources) are of great important for enabling success of most of the identified strategies whereas intangible (intellectual property, reputation and culture) and human (skills and knowledge, communication and interaction, and motivation) resources have great variance of importance. / Under det senaste decenniet har det skett många innovationer till mobiltelefonen och nya funktioner som mobilbetalningar har lagts till. Östafrika är den region med den snabbast växande adoptionen och högsta utnyttjandegraden av mobilbetalningar i världen. Trots regionens framgångar är det dock fortfarande få aktiva användare av mobilbetalningar i förhållande till antalet registrerade användare. Syftet med detta examensarbete är att analysera vad mobilbetalningsleverantörer bör tänka på när man försöker driva aktivitet från den registrerade användarbas. Det teoretiska ramverket har byggts huvudsakligen på resource-based view och den analytiska modell som används är en viktighet-instats-matris. Den empiriska studien bestod av ingående intervjuer med nyckelpersoner och intressenter från mobilbetalningsindustrin. Majoriteten av intervjuerna utfördes på plats med intervjuobjekten under en forskningsresa till Kenya, Uganda och Tanzania. Resultaten utvärderades därefter under Mobile Money Africa 2014 konferensen i Sydafrika. Denna studie har identifierat ett antal anledningar som orsakar låg användaraktivitet av den registrerade användarbasen och strategier som har möjlighet att angripa dessa anledningar. För att driva aktivitet, är det viktigt att mobilbetalningsleverantörerna förstår vad för materiella, immateriella och mänskliga resurser som är önskvärda samt krävs för att framgångsrikt kunna genomföra och driva de identifierade strategierna. I studien dras slutsatsen att materiella resurser (fysiska och finansiella resurser) är av stor betydelse för att möjliggöra framgång av de flesta identifierade strategier medan viktigheten för immateriella (immaterialrätt, rykte och kultur) och mänskliga (kompetens och kunskap, kommunikation och interaktion, och motivation) resurser varierar.

Cette thèse souhaite fournir des outils pour qu’un utilisateur puisse contribuer activement à la sécurité de son usage d’un système informatique. Les activités de sensibilités différentes d’un utilisateur nécessitent tout d’abord d’être cloisonnées dans des domaines dédiés, par un contrôle d’accès s’ajustant aux besoins de l’utilisateur. Afin de conserver ce cloisonnement, celui-ci doit être en mesure d’identifier de manière fiable les domaines avec lesquels il interagit, à partir de l’interface de sa machine. Dans une première partie, nous proposons un nouveau mécanisme de cloisonnement qui peut s’adapter de manière transparente aux changements d’activité de l’utilisateur, sans altérer le fonctionnement des contrôles d’accès existants, ni dégrader la sécurité du système. Nous en décrivons une première implémentation, nommée StemJail, basée sur les espaces de noms de Linux. Nous améliorons ce cloisonnement en proposant un nouveau module de sécurité Linux, baptisé Landlock, utilisable sans nécessiter de privilèges. Dans un second temps, nous identifions et modélisons les propriétés de sécurité d’une interface homme-machine (IHM) nécessaires à la compréhension fiable et sûre du système par l’utilisateur. En particulier, il s’agit d’établir un lien entre les entités avec lesquelles l’utilisateur pense communiquer, et celles avec lesquelles il communique vraiment. Cette modélisation permet d’évaluer l’impact de la compromission de certains composants d’IHM et d’aider à l’évaluation d’une architecture donnée. / This thesis aims to provide end users with tools enhancing the security of the system they use. First, user activities of different sensitivities require to be confined in dedicated domains by an access control fitting the user’s needs. Next, in order to maintain this confinement, users must be able to reliably identify the domains they interact with, from their machine’s interface. In the first part, we present a new confinement mechanism that seamlessly adapts to user activity changes, without altering the behavior of existing access controls nor degrading the security of the system. We also describe a first implementation named StemJail, based on Linux namespaces. We improve this confinement tool by creating a new Linux security module named Landlock which can be used without requiring privileges. In a second step, we identify and model the security properties a human-computer interface (HCI) requires for the reliable and secure understanding of the system by the user. Precisely, the goal is to establish a link between the entities with which the users think they communicate, and those with which they actually communicate. This model enables to evaluate the impact of HCI components jeopardization and helps assessing a given architecture.

This paper aims to investigate whether or not it is possible to identify users who are about change provider of service with machine learning. It is believed that the Consumer Decision Journey is a better model than traditional funnel models when it comes to depicting the processes which consumers go through, leading up to a purchase. Analytical and operational Customer Relationship Management are presented as possible fields where such implementations can be useful. Based on previous studies, Random Forest and XGBoost were chosen as algorithms to be further evaluated because of its general high performance. The final results were produced by an iterative process which began with data processing followed by feature selection, training of model and testing the model. Literature review and unstructured and semi-structured interviews with the employer Growth Hackers Sthlm were also used as methods in a complementary fashion, with the purpose of gaining a wider perspective of the state-of-the-art of ML-implementations. The final results showed that Random Forest could identify the sought-after users (positive) while XGBoost was inferior to Random Forest in terms of distinguishing between positive and negative classes. An implementation of such model could support and benefit an organization’s customer acquisition operations. However, organizational prerequisites regarding the data infrastructure and the level of AI and machine learning integration in the organization’s culture are the most important ones and need to be considered before such implementations. / I det här arbetet undersöks huruvida det är möjligt att identifiera ett beteende bland användare som innebär att användaren snart ska byta tillhandahållare av tjänst med hjälp av maskininlärning. Målet är att kunna bidra till ett maskininlärningsverktyg i kundförvärvningssyfte, såsom analytical och operational Customer Relationship Management. Det sökta beteendet i rapporten utgår från modellen ”the Consumer Decision Journey”. I modellen beskrivs fyra faser där fas två innebär att konsumenten aktivt söker samt är mer mottaglig för information kring köpet. Genom tidigare studier och handledning av uppdragsgivare valdes algoritmerna RandomForest och XGBoost som huvudsakliga algoritmer som skulle testas. Resultaten producerades genom en iterativ process. Det första steget var att städa data. Därefter valdes parametrar och viktades. Sedan testades algoritmerna mot testdata och utvärderades. Detta gjordes i loopar tills förbättringar endast var marginella. De slutliga resultaten visade att framförallt Random Forest kunde identifiera ett beteende som innebär att en användare är i fas 2, medan XGBoost presterade sämre när det kom till att urskilja bland positiva och negativa användare. Dock fångade XGBoost fler positiva användare än vad Random Forest gjorde. I syfte att undersöka de organisatoriska förutsättningarna för att implementera maskininlärning och AI gjordes litteraturstudier och uppdragsgivaren intervjuades kontinuerligt. De viktigaste förutsättningarna fastställdes till två kategorier, datainfrastruktur och hur väl AI och maskininlärning är integrerat i organisationens kultur.

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