PROFILING - CONCEPTS AND APPLICATIONS

Profiling is an approach to put a label or a set of labels on a subject, considering the characteristics of this subject. The New Oxford American Dictionary defines profiling as: “recording and analysis of a person’s psychological and behavioral characteristics, so as to assess or predict his/her capabilities in a certain sphere or to assist in identifying a particular subgroup of people”. This research extends this definition towards things demonstrating that many methods used for profiling of people may be applied for a different type of subjects, namely things. The goal of this research concerns proposing methods for discovery of profiles of users and things with application of Data Science methods. The profiles are utilized in vertical and 2 horizontal scenarios and concern such domains as smart grid and telecommunication (vertical scenarios), and support provided both for the needs of authorization and personalization (horizontal usage).:The thesis consists of eight chapters including an introduction and a summary. First chapter describes motivation for work that was carried out for the last 8 years together with discussion on its importance both for research and business practice. The motivation for this work is much broader and emerges also from business importance of profiling and personalization. The introduction summarizes major research directions, provides research questions, goals and supplementary objectives addressed in the thesis. Research methodology is also described, showing impact of methodological aspects on the work undertaken. Chapter 2 provides introduction to the notion of profiling. The definition of profiling is introduced. Here, also a relation of a user profile to an identity is discussed. The papers included in this chapter show not only how broadly a profile may be understood, but also how a profile may be constructed considering different data sources. Profiling methods are introduced in Chapter 3. This chapter refers to the notion of a profile developed using the BFI-44 personality test and outcomes of a survey related to color preferences of people with a specific personality. Moreover, insights into profiling of relations between people are provided, with a focus on quality of a relation emerging from contacts between two entities. Chapters from 4 to 7 present different scenarios that benefit from application of profiling methods. Chapter 4 starts with introducing the notion of a public utility company that in the thesis is discussed using examples from smart grid and telecommunication. Then, in chapter 4 follows a description of research results regarding profiling for the smart grid, focusing on a profile of a prosumer and forecasting demand and production of the electric energy in the smart grid what can be influenced e.g. by weather or profiles of appliances. Chapter 5 presents application of profiling techniques in the field of telecommunication. Besides presenting profiling methods based on telecommunication data, in particular on Call Detail Records, also scenarios and issues related to privacy and trust are addressed. Chapter 6 and Chapter 7 target at horizontal applications of profiling that may be of benefit for multiple domains. Chapter 6 concerns profiling for authentication using un-typical data sources such as Call Detail Records or data from a mobile phone describing the user behavior. Besides proposing methods, also limitations are discussed. In addition, as a side research effect a methodology for evaluation of authentication methods is proposed. Chapter 7 concerns personalization and consists of two diverse parts. Firstly, behavioral profiles to change interface and behavior of the system are proposed and applied. The performance of solutions personalizing content either locally or on the server is studied. Then, profiles of customers of shopping centers are created based on paths identified using Call Detail Records. The analysis demonstrates that the data that is collected for one purpose, may significantly influence other business scenarios. Chapter 8 summarizes the research results achieved by the author of this document. It presents contribution over state of the art as well as some insights into the future work planned

Exploring the diversity in the impact of colors of rating scales on user's rating behavior

User-generated ratings have become an integral part of data-driven systems, yet they are known to be susceptible to rating bias that can distort the true ratings of users and can subsequently contaminate the effectiveness of the system. Earlier studies have discovered that different characteristics of a rating scale such as granularity, color, neutral point, etc. play a significant role in instigating bias in users' rating behavior. Amongst all, the research works done so far to explore the impact of colors used in rating scales have uncovered significant contradictory patterns of bias in user ratings. This research argues that because of their individuality, users' responses to the influence exerted by the color of the scale are diverse. Personality and culture are known as two consistent representatives of a person's individuality. Yet no attempt has been made to explore the diversity in individuals' responses to the influence of color of rating scales from the perspective of their personality and culture. In addition to it, while investigating the impact of color, the existing research works employed rating scales varying in multiple characteristics other than colors and consequently failed to capture the sole impact of color on users' rating behavior. This research addresses the problem by providing new empirical information about the impact of color-coded rating scales on users' rating behavior. A within-subject study was conducted to collect participants' responses on a demographic and a personality assessment questionnaire and their ratings on different products. The result shows that, extroverts tend to provide biased ratings in star-based scales with contrasting color combinations. On the other hand, collectivists exhibit a tendency to provide biased ratings under the influence of star-based and emoji-based scales with contrasting color combinations. The analysis also revealed some significant directions on how extroverts and collectivists adjust their ratings due to bias. Precisely, taking a personality and culture based approach can help to gain a thorough understanding of the impact of color-coded rating scales on users' rating behavior

Computational personality recognition in social media

A variety of approaches have been recently proposed to automatically infer users' personality from their user generated content in social media. Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data. In this paper, we perform a comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube. We answer three questions: (1) Should personality prediction be treated as a multi-label prediction task (i.e., all personality traits of a given user are predicted at once), or should each trait be identified separately? (2) Which predictive features work well across different on-line environments? (3) What is the decay in accuracy when porting models trained in one social media environment to another

Exploring human factors issues & possible countermeasures in password authentication

PhD ThesisThis thesis is concerned with usable security. It describes a series of experiments to understand users’ behaviour in the domain of password authentication. The thesis is comprised of two parts. Part 1 reports on experiments into how different persuasion strategies can be used to increase the strength of users’ password. Existing research indicates that the lack of persuasive elements in password guidelines may lead to a lack of motivation to produce strong passwords. Thus, an experimental study involving seventy-five participants was conducted to evaluate the effectiveness of a range of persuasion strategies on password strength. In addition this experiment explores how personality variables affect the susceptibility of users to persuasion. The results showed that passwords created by users who received password guidelines that include a persuasion strategy produce stronger passwords than a control group. In terms of the personality variables, the result shows that there are certain personality types that tend to produce slightly better passwords than others; but it is difficult to draw a firm conclusion about how personality affects susceptibility to persuasion. The second part of this thesis presents an innovative alternative to text-based passwords, namely, graphical password schemes. Graphical passwords take advantage of the superior ability of humans to remember graphics and pictures over text and numbers. Research shows that graphical password schemes are a promising alternative, but that they are susceptible to shoulder surfing attacks, resulting in scepticism about adoption. Thus in part 2 of the thesis, three innovative shoulder surfing defence techniques are proposed and implemented in a small-scale prototype with a specific focus given to one type of graphical password; The Draw-A-Secret (DAS) scheme. The results of two separate experimental studies involving sixty-five and thirty participants respectively to evaluate the proposed defence techniques from the perspectives of security and usability are presented. The results show that the technique which, on theoretical grounds, was expected to be quite effective, provides little protection. A second technique which did provide the best overall shoulder surfing defence; created usability problems. But a third technique provided a reasonable shoulder surfing defence and good usability simultaneously; a good balance which the other two techniques did not achieve. The proposed defence techniques and experimental results are directly relevant to other graphical password schemes of the same category with slight modification to suit the requirements of the scheme intended. In summary, the thesis contributes to the discussion of some key usability problems which exist around password authentication domains. All the proposed countermeasures are evaluated through a series of experimental studies which present several intriguing discussions and promising findings

Interaction-driven User Interface Personalisation for Mobile News Systems

User interfaces of mobile apps offer personalised experience primarily through manual customisation rather than spontaneous adaptation. This thesis investigates methods for adaptive user interfaces in the context of future mobile news apps that are expected to systematically monitor users' news access patterns and adapt their interface and interaction in response. Although mobile news services are now able to recommend news that a user would be likely to read, there has not been equivalent progress in personalising the way that news content is accessed and read. This thesis addresses key issues for the development of adaptive user interfaces in the mobile environment and contributes to the existing literature of adaptive user interfaces, user modelling, and personalisation in the domain of news in four ways. First, using survey methods it explores differences in how people consume and read news content on mobile news apps and it defines a News Reader Typology that characterises the individual news consumer. Second, it develops a method for monitoring news reading patterns through a deployed news app, namely Habito News, and it proposes a framework for modelling users by analysing those patterns; machine learning algorithms are exploited selectively in the analysis. Third, it explores the design space of personalised user interfaces and interactions that would be tailored to the needs and preferences of individual news readers. Finally, it demonstrates the effectiveness of automatic adaptation through Habito News, the prototype mobile news app that was developed, which systematically monitors users' news reading interaction behaviour and automatically adjusts its interface in response to their news reading characteristics. The results indicate the feasibility of user interface personalisation and help shape the future of automatically changing user interfaces by systematic monitoring, profiling and adapting the interface and interaction

The Role of Self-congruity in Consumer Preferences: Perspectives from Transaction Records

Personalised marketing is more persuasive than traditional techniques aimed at the masses, however marketers do not always have access to consumers’ private attributes in order to apply these insights. The effect of personalisation is based on an established theory in consumer psychology – self-congruity theory – which posits that individuals prefer products, brands and advertisements that embody characteristics that match with their self-concepts. Self-congruence not only enhances marketing effectiveness, it can also be used to improve consumer well-being. While it has been established that consumers who spend in a way that is more congruent with their personality are happier, clarifications around the types of individuals who are more or less likely to engage in self-congruent spending, as well as the moderating effects on the benefit in happiness from such consumption could inform policy for improving happiness at a collective level. This thesis contributes to a growing body of research which attempts to understand how consumption patterns are related to consumers’ characteristics, its applications in advertising, as well as consumer well-being. By using a dataset containing more than 1 million transactions recorded over a period of 12-months, the thesis demonstrates the value of the digital footprint in the form of bank transactions for enriching our understanding of key questions in consumer research, underpinned by the theory of self-congruity. This thesis combines methods from computational social science with personality psychology to test research questions on consumer preferences. Two components of the thesis focused on the predictive utility of transaction records in inferring consumer attributes with which to personalise advertising, as well as the use of transaction records in examining self-congruence in overall consumption patterns and its relationship with happiness. Through five empirical studies, this work suggests that consumer attributes such as age and financial distress can be reliably inferred from consumption patterns reflected in transaction records (Chapter 3 and 5). The inferred age can be used to personalise advertisements in order to increase their appeal (Chapter 4). Using an objective measure of self-congruence in overall consumption pattern computed from transaction records and panel ratings, the thesis shows that individuals differ in their tendency to spend in a way that is congruent with their personality based on their levels of materialism and financial distress (Chapter 6). As the most important predictor of self-congruent spending, financial distress moderates the relationship between self-congruent spending and happiness (Chapter 7). These findings contribute insights into how consumption patterns are related to consumer attributes and usefulness for personalisation in marketing, as well as policy recommendations for improving well-being by targeting consumption patterns in financially distressed individuals. In addition, this thesis also showcases the value of machine learning and large-scale behavioural field data in the study of consumer psychology. Privacy and ethical concerns surrounding automated profiling and microtargeting are also cautioned

Improving the aesthetic and other experiential design aspects of bicycle paths in Western Australia

Governments around Australia are in the process of promoting cycling as both a sustainable form of transport that can be a viable alternative to the motor vehicle, particularly for shorter trips, and as a healthy recreational pursuit that can play an important role in addressing the growing problem of obesity and illnesses associated with a sedentary lifestyle in the community. As part of this initiative, the development of effective and efficient infrastructure for bicycles is seen as a vital step for achieving higher participation rates. A major component of the nation’s bicycle infrastructure is the growing networks of paved paths and natural surface trails located in both urban and regional areas. A well-designed path or trail must meet agreed standards related to safety and function and, in order to achieve maximum usage, it must also create a desirable riding experience. While requirements for safety and function are well understood by path and trail planners, little empirical information has been produced to enable these planning professionals to understand the elements that impact upon an individual’s riding experience and to then incorporate them into the design process. Accordingly, the overall aim of this research was to investigate how the aesthetic, cultural and other experiential design aspects of bicycle paths and trails can enhance the perceived riding experience. A secondary objective of the project involved a determination of the procedural factors guiding the local path and trail design protocols and process. A third objective was to gain an insight into the most effective method of communicating the benefits of these riding environments to important target groups. Following the establishment of a theoretical framework incorporating the psychophysical nature of cycling, the effect of landscape and current design practices, the research progressed through several stages beginning with an autoethnography examining the researcher’s extensive experience in the promotion of cycling in Western Australia, augmented by in-depth discussions with leading key informants. This was followed by a mix of quantitative and qualitative methodology to gauge perception of various elements of in-situ and photo-surrogate path-riding environments among the general population in Perth, Western Australia. The findings indicate that there are specific experiential design aspects related to the riding environment, surrounding landscape or associated features that can directly influence a person’s decision to use a particular path, trail or route. The research also identified preferred communication strategies and found deficiencies in the current design process that if addressed, could lead to the development of better received and patronised riding environments. It is intended that the outcome of this research will be to provide a design framework to guide path and trail planners in the development of facilities that enhance the overall riding experience. A number of agencies responsible for developing bicycle infrastructure, or design standards, have indicated a desire to access parts of this research project for use in the decision-making process, thus achieving a better balance between safety, functional and experiential aspects

Studying user behaviour through human-smartphone interactions and experience sampling method data

Nowadays, smartphones are considered ubiquitous with a large share of the global population carrying their phones everywhere and spending significant portions of their day interacting with the device. Due to the high habitual and repetitive usage and the diversity of the activities carried out through the handset, smartphones appear to be a convenient inspective tool to capture and understand human behaviour. In this thesis, we are interested in evaluating an individual’s disposition based on their smartphone usage behaviour. We achieve this through the deployment of the bespoke smartphone app Tymer within a cohort of 64 participants. Following ESM methodology principles, the app was designed to collect various metrics including self-reported mood and unobtrusively recorded low-level UI interaction event data for a period of 8 weeks. In contrast to commonly used alternatives such as inferring the time users spent on their phone or using self-report measures, our novel approach of quantifying smartphone usage based on the number of interaction events provides a more detailed and clearer signal. Using this method, we assess various hypotheses relating to smartphone usage and uncover associations with Smartphone Addiction. Particular significant findings in this domain further motivate the subsequent investigation of the Snapchat app. We also find evidence for the usefulness of smartphone usage behaviours in the prediction of mood states. Our results support the idea that smartphone-human interactions are a valuable proxy for the quantification of smartphone usage behaviours, and that the smartphone is a suitable tool to infer an individual’s disposition, such as their proneness to Smartphone Addiction and their mood