For some computational problems, allowing the algorithm to flip coins (i.e., use a random number generator) makes for a simpler, faster, easier-to-analyze algorithm. The following are the three main reasons.

Hiding the Worst Cases from the Adversary: The running time of a randomized algorithms is analyzed in a different way than that of a deterministic algorithm. At times, this way is fairer and more in line with how the algorithm actually performs in practice. Suppose, for example, that a deterministic algorithm quickly gives the correct answer on most input instances, yet is very slow or gives the wrong answer on a few instances. Its running time and its correctness are generally measured to be those on these worst case instances. A randomized algorithm might also sometimes be very slow or give the wrong answer. (See the discussion of quick sort, Section 9.1). However, we accept this, as long as on every input instance, the probability of doing so (over the choice of random coins) is small.

Probabilistic Tools: The field of probabilistic analysis offers many useful techniques and lemmas that can make the analysis of the algorithm simple and elegant.

Solution Has a Random Structure: When the solution that we are attempting to construct has a random structure, a good way to construct it is to simply flip coins to decide how to build each part. Sometimes we are then able to prove that with high probability the solution obtained this way has better properties than any solution we know how to construct deterministically.

Iterative Algorithms: Measures of Progress and Loop Invariants

Selection Sort: If the input for selection sort is presented as an array of values, then sorting can happen in place. The first k entries of the array store the sorted sublist, while the remaining entries store the set of values that are on the side. Finding the smallest value from A[k + 1] … A[n] simply involves scanning the list for it. Once it is found, moving it to the end of the sorted list involves only swapping it with the value at A[k + 1]. The fact that the value A[k + 1] is moved to an arbitrary place in the right-hand side of the array is not a problem, because these values are considered to be an unsorted set anyway. The running time is computed as follows. We must select n times. Selecting from a sublist of size i takes Θ(i) time. Hence, the total time isΘ(n + (n–1) + … + 2 + 1) = Θ(n2) (see Chapter 26).

Cyberspace constitutes a specific environment; the investigations in this field are based either on the original cyberspace-dependent methods and theories, or on universal theories and methods worked out in diverse areas of knowledge, not necessarily closely connected with cyberspace. A psychological theoretical construct (with vast practical perspectives) introduced by Csikszentmihalyi, (2000/1975) known as optimal, or flow experience, alongside the methods of its measurement, basically refer to the universal, that is, nonspecific theoretical and methodological background. This traditional methodology was adapted and accepted within cyberspace; it represents a growing area of the investigators' activity in the field.

Like many other investigations of human behavior in cyberspace, flow-related studies are of both practical and theoretical significance. The practical significance is associated with the challenges deriving from business: a large body of research is stimulated by business expectations of acquiring advantages in the quality of offers to be suggested to customers. The theoretical significance stems from a supposition that optimal experience is an important construct mediating human activity in cyberspace, and thus represents a special level of psychological mediation of mental processes. The mechanisms of multiple mediation and remediation of a previously mediated experience are known to affect human psychic development (Cole, 1996; Vygotsky, 1962).

In this chapter, major research directions are presented and discussed, referring to the optimal, or flow, experience studies conducted within cyberspace environments.

The psychology of cyberspace, or cyberpsychology, is a new field of study. Fewer than a handful of universities around the world offer a course in this emerging area, despite the unequivocal fact that many activities today take place online. In this novel social environment, new psychological circumstances project onto new rules governing human experiences, including physiological responses, behaviors, cognitive processes, and emotions. It seems, however, that psychology gradually is acknowledging and accepting this new field of study, as more behavioral scholars have begun to research the field, growing numbers of articles in the area appear in psychology journals, and an increasing number of books related to this domain are being published. This change reflects not only the growing number of professionals who find interest in researching the new field but also the growing number of people – students and laypeople alike – who search for credible and professional answers in this relatively unknown and uninvestigated area of human psychology.

I discovered this exciting direction in psychology mainly because of personal necessity. I was living in London, Ontario, Canada – affiliated with The University of Western Ontario and collaborating with my long-time friend and colleague William (Bill) Fisher, with whom I have thoroughly studied issues of sexuality on the Internet – when the revolutionary computer network, called the Internet, emerged (quite innovative in comparison to the relatively primitive Bitnet we used before).

Intergroup conflict is sadly part of our existence. Such conflicts exist around the globe originating through differences, for example, in beliefs, religion, race, and culture. The degree of conflict between rival groups varies from mild hostility to all-out war, leading to the loss of thousands of lives every year. The field of intergroup conflict has attracted the attention of many social psychologists who have attempted to understand the phenomenon and to provide solutions to end it.

These scholars concentrated their research on the structure of such conflicts that they perceived as comprising three major aspects: cognitive, affective, and behavioral. The cognitive aspect is demonstrated by the stereotype held by one group toward the other; the affective aspect by the prejudice held regarding the other group, and the behavioral aspect by discrimination against this group.

The fundamental component found in intergroup conflict is the stereotype – the negative perception of the other group. Stereotypes may include negative perceptions of a variety of characteristics such as traits, physical characteristics, and expected behaviors. People generally believe that their group (the ingroup) is a heterogeneous group, whereas members of the other group (the outgroup) are all similar to one another. This perception, known as the homogeneity effect, is one of the bases for our tendency to stereotype the members of the outgroup and claim that they are all, for example, hostile, liars, and lazy (Linville, Fischer, & Salovey, 1989; Linville & Jones, 1980).

Introduction

Science and the Internet: Its most appealing, usable, and integrating component, the World Wide Web, came from its laboratories. Fifteen years after the invention of the web, it has become such an integral part of the infrastructure of modern societies that young people cannot imagine a world without it. It has become even easier to imagine a world without roads and cars than a world without the World Wide Web.

Time to ask in what ways the Internet had and is having an impact on science. How is what once came from the laboratory influencing that laboratory's structure and the researchers working in it? In particular, how is it influencing the way research is conducted? Tim Berners-Lee, who invented the World Wide Web at CERN in Geneva, wrote in 1998:

Groups within the electronic realm share many characteristics in common with groups that meet and function in shared physical spaces. Groups in both domains can be quite diverse in terms of the composition and personality characteristics of members, the purpose and goals of the group, and the contextual setting in which the group functions. A variety of factors likely affect and influence the structure and functioning of any given group. Many, if not most, of these factors can potentially influence the group, regardless of the domain (electronic or face-to-face) and produce similar outcomes. There are qualities of electronic communication settings and qualities of physical settings that can uniquely influence the dynamics of a group in those respective settings (see McKenna & Green, 2002; McKenna & Seidman, 2005 for reviews).

This chapter delves into the workings of online groups and examines potentially influential factors for group functioning. The chapter is divided into three sections, which examine (1) the role of the motivations and personality characteristics of individual members within the group, (2) the way in which different categories or kinds of online groups distinctly function (including support groups), and (3) aspects of the internal dynamics of online groups, such as cohesiveness, status and stereotypes, and performance.

Individuals and Groups

Individual motivations of members

Classical motivation theory indicates that all behavior is motivated in some way and that an individual will engage in particular behaviors to further a desired end (e.g., Atkinson & Birch, 1970; Lewin, 1951).

Personal computers and computer networks began to take over offices and increasingly the public in the 1980s, but the extensive adoption of the Internet did not come about until the introduction of the first browsers and the overwhelming acceptance of Microsoft Windows and Apple systems – equipped with advanced graphics – both in the mid-1990s. The world changed in many ways for numerous people from that point, as both social institutions and individuals have witnessed and participated in another social revolution: the availability and accessibility of information of all kinds and the dramatic innovation in interpersonal communication. With the assistance and encouragement of governments and many organizations (acting out of a variety of reasons), computers, linked to ever-growing networks, penetrated the general public rather quickly and relatively easily. It did not take long before numerous technological firms around the world, acknowledging significant improvements in a broad array of personal, work-related, social, business-related, and government-related activities, joined a competitive race for this line of business, marked by its creativity and high potential. Accordingly, they advanced and reinforced more intensive use of computers and numerous computer-related activities. This race, in turn, brought about fantastic technological developments that have changed people's world order and lives in many ways, from seeking and using information on any topic to shopping and trading, from communication with acquaintances and with strangers to virtual dating and a love life, from learning and teaching to doing research, from helping others and being helped to improved use of medicine and other facets of health care, from entertainment and leisure to self-expression.

Introduction

For those who regularly surf through cyberspace and experience it as a parallel and not unusual social environment – whether this takes the form of online forums, chat rooms, or personal communication through instant messaging (IM) – it is customary to encounter various types and exhibitions of human behavior. Many Internet surfers, in the beginning, are convinced that most other surfers impersonate, lie, cheat, or at the very least attempt to pull your leg; later, however, it occurs to them that this basic premise is generally wrong. After spending much time in virtual communities, publicly and privately interacting with numerous anonymous individuals, many people start to realize that their behavior in cyberspace reflects their actual personalities or mood states. To their astonishment, as they observe over time other people's gestures, behavioral patterns, writing styles, frequency and intensity of involvement in group situations, personal associations, vocabulary, choice of verbal expressions, netiquette, and other features of their online behavior – all based on textual communication – laypeople realize that they can learn a great amount about themselves and about others. Moreover, it occurs to them that under these circumstances, they could learn even more about many people's personality dispositions, attitudes, moral values, sensitivities, habits, needs, and preferences than in an offline, face-to-face (F2F) environment. This intuitive recognition by many Internet users is consistent with what behavioral theorists and researchers of cyberspace have argued in regard to the emergence of self in cyberspace.

There has been much alarm about Internet abuse in the past decade. Claims of Internet-related crimes such as homicides, suicides, and child neglect have received widespread media attention across the globe (“Chinese Gamer Sentenced to Life,” 2005; Spain & Vega, 2005). Many claim that they are or know someone who is addicted to the Internet. Fifteen percent of university students in the United States and Europe and 26 percent of Australian students claim they know someone is addicted to the Internet (Anderson, 1999; Wang, 2001). Almost 10 percent of adult Internet users in a large online study self-identified as Internet addicts (Cooper, Morahan-Martin, Mathy, & Maheu, 2002), while 31 percent of MySpace users (Vanden Boogart, 2006) and 42 percent of online gamers (Yee, 2002) say they are addicted to those Internet applications. In Germany, a camp was established to help children who were addicted to the Internet (Moore, 2003). It is tempting to dismiss these claims as media hype, but clinicians also have reported Internet-related problems and have set up clinics specifically to treat these problems in many countries. In recent years, governments in Asia have established clinics and intervened to reduce Internet use. The first Chinese clinic for Internet addiction in Beijing has expanded from 40 to 300 inpatient beds, and new clinics are being established in other Chinese cities (Griffiths, 2005; Lin-Liu, 2006).

A new and rather surprising door in the history of the mental health field has opened. Professionals have begun to explore methods for using online environments to help people. How do these methods compare to in-person interventions? Although face-to-face approaches may be advantageous in many cases, there are some advantages to computer-mediated and online interventions. One obvious and frequently cited benefit that applies to all forms of online work is the opportunity to reach people who are unable to visit the professional for geographical, physical, or lifestyle reasons. Computer-mediated work also may be an important initial step in the establishment of what could become an ongoing, in-person treatment. Other advantages, as I'll discuss later, are specific to particular types of online interventions.

In writing this chapter, I decided not to organize it around the concept of psychotherapy. After all, what do we mean by that term? If we assembled a group of psychotherapists to discuss this question, we would be lucky if they came to any agreement other than a very general definition about psychotherapy as a service in which a professional helps a person with a problem. That controversy exists even before we toss cyberspace into the debate. Whether we call it psychotherapy or not, there have been many approaches over the past 100 years for applying psychological principles to the delivery of mental health services. Now cyberspace offers even more possibilities – many never dreamed of in the past.

Introduction

The use of new technology, and particularly the Internet, increasingly requires people to disclose personal information online for various reasons. In computer-mediated communication (CMC), disclosure may serve to reduce uncertainty in an interaction (Tidwell & Walther, 2002) or to establish legitimacy when joining an online group (Galegher, Sproull, & Kiesler, 1998). Disclosure is often a prerequisite to access services (for instance, with the ubiquitous registration form), to make online purchases (Metzger, 2006) or is requested for those same services to be personalized. The increasingly social nature of much web-based software (e.g., social network sites) also places a privacy cost on users due to a heightened requirement for disclosure of personal information as part of the functionality of the system (see BBC News). In addition to this increased need for disclosure, the development of ambient and ubiquitous technologies has raised the possibility that devices will communicate, or even broadcast, personal information without recourse to the user. Moreover, the ability to store information easily and cross-reference databases raises the possibility of unwitting disclosure through information accrual. Perhaps not surprisingly, this has raised a number of privacy concerns, among consumers and privacy advocates (e.g., Jupiter Research, 2002; U.K. Information Commissioner, 2006).

We start this chapter by introducing the existing research literature surrounding privacy and trust online. We then go on to consider how privacy and trust interact in determining online behavior.