We analyze mechanisms of player retention and commitment in massively multiplayer online games. Our ground assumptions on player retention are based on a marketing model of customer retention and commitment. To measure the influence of gameplay, in-game sociality, and real-life status on player commitment, we use the following metrics: weekly play time, stop rate and number of years respondents have been playing the game. The cross-cultural sample is composed of 2865 World of Warcraft players from North-America, Europe, Taiwan, and Hong-Kong who completed an online questionnaire. We differentiate players in terms of demographic categories including age, region, gender and marital status.

World of Warcraft (WoW) is a massively multiplayer online game (MMO) supporting complex social interactions among over 12 million players. While the "lone gamer" stereotype still persists, there is little data on gaming with other players with whom one shares a "real life" (RL) social relationship. Our work departs from previous studies in focusing on the hybrid of online and offline sociality, rather than only one or the other. We provide perhaps the first systematic quantitative characterization of MMO play with RL friends, family and other social connections. A large online survey collected data from 2865 WoW players from the US, Europe, Hong Kong and Taiwan. The findings overwhelmingly support the view that playing WoW may often serve to enhance, not diminish, RL social interactions. In addition, we present benchmark results on demographics and WoW play practices in world regions previously not studied. The consistency of the patterns of findings across East/West and gender groupings suggests fascinating issues for further research.

This paper presents findings from a qualitative study of people's everyday interactions with energy-consuming products and systems in the home. Initial results from a large online survey are also considered. This research focuses not only on "conservation behavior" but importantly investigates interactions with technology that may be characterized as "normal consumption" or "over-consumption." A novel vocabulary for analyzing and designing energy-conserving interactions is proposed based on our findings, including: cutting, trimming, switching, upgrading, and shifting. Using the proposed vocabulary, and informed by theoretical developments from various literatures, this paper demonstrates ways in which everyday interactions with technology in the home are performed without conscious consideration of energy consumption but rather are unconscious, habitual, and irrational. Implications for the design of energy-conserving interactions with technology and broader challenges for HCI research are proposed.

In prior work we reported on the design of a social annotation system, SparTag.us, for use in sensemaking activities such as work-group reading and report writing. Previous studies of note-taking systems have demonstrated behavioral differences in social annotation practices, but are not clear in the actual performance gains provided by social features. This paper presents a laboratory study aimed at evaluating the learning effect of social features in SparTag.us. We found significant learning gains, and consider implications for design and for understanding the underlying mechanisms in play when people use social annotation systems.

This paper presents a context-aware mobile recommender system, codenamed Magitti. Magitti is unique in that it infers user activity from context and patterns of user behavior and, without its user having to issue a query, automatically generates recommendations for content matching. Extensive field studies of leisure time practices in an urban setting (Tokyo) motivated the idea, shaped the details of its design and provided data describing typical behavior patterns. The paper describes the fieldwork, user interface, system components and functionality, and an evaluation of the Magitti prototype.

Facial affect (or emotion) recognition is a central issue for many VMC and naturalistic computing applications. Most computational models assume "categorical perception" of facial affect, in which a benign illusion promotes robust recognition of emotional expressions even under severe degradation conditions, including temporal compression. However, this applied interest in human facial affect perception is coming at a time when the evidence for categorical perception is being challenged in the basic research literature, largely on methodological grounds. The research presented here systematically addresses the classic evidence for categorical perception of facial affect, using high-quality digital imaging and display technologies and improved research methods. In doing so, it illustrates a fruitful convergence of basic and applied research. The evidence does NOT support categorical perception of facial affect, which in turn underlines the importance of preserving high-fidelity motion information in portraying emotion. This research provides new human behavioral data on facial affect perception, and underscores the importance of careful consideration of facial affect compression methods.

Blogging is a Web-based form of communication that is rapidly becoming mainstream. In this paper, we report the results of an ethnographic study of blogging, focusing on blogs written by individuals or small groups, with limited audiences. We discuss motivations for blogging, the quality of social interactivity that characterized the blogs we studied, and relationships to the blogger's audience. We consider the way bloggers related to the known audience of their personal social networks as well as the wider blogosphere of unknown readers. We then make design recommendations for blogging software based on these findings.

Current perceptions of Instant Messaging (IM) use are based primarily on self-report studies. We logged thousands of (mostly) workplace IM conversations and evaluated their conversational characteristics and functions. Contrary to prior research, we found that the primary use of workplace IM was for complex work discussions. Only 28% of conversations were simple, single-purpose interactions and only 31% were about scheduling or coordination. Moreover, people rarely switched from IM to another medium when the conversation got complex. We found evidence of two distinct styles of use. Heavy IM users and frequent IM partners mainly used it to work together: to discuss a broad range of topics via many fast-paced interactions per day, each with many short turns and much threading and multitasking. Light users and infrequent pairs mainly used IM to coordinate: for scheduling, via fewer conversations per day that were shorter, slower-paced with less threading and multitasking.

Facial expression of emotion (or “facial affect”) is rapidly becoming an area of intense interest in the computer science and interaction design communities. Ironically, this interest comes at a time when the classic findings on perception of human facial affect are being challenged in the psychological research literature, largely on methodological grounds. This paper presents two studies on perception of facial affect. Experiment 1 provides new data on the recognition of human facial expressions, using experimental methods and analyses designed to systematically address the criticisms and help resolve this controversy. Experiment 2 is a user study on affect in a prototype robot face; the results are compared to the human data of Experiment 1. Together they provide a demonstration of how basic and more applied research can mutually contribute to this rapidly developing field.

This paper presents major findings Corn a large research project designed to carefully characterize what “life in LambdaMOO” (a classic social MUD) is lie for many of its members. A “convergent methodologies” approach embracing qualitative and quantitative, subjective and objective procedures was used. A rich, extensive database was produced, Corn which robust patterns could emerge, be considered in context and assessed with some confidence. Results are discussed in terms of four broad categories of interest: 1) users and use, 2) identity 3) sociality and 4) spatiality. These data should help inform the discourse on, and design of, online communities in the future.

Rapid growth in 3-D rendering technologies has deluged us with glitzy graphical representations.In what contexts do people find 3-D graphs of 2-D data both attractive and useful?We examine students' preferences for graphical display formats under several use scenarios.Line graphs were preferred more for conveying trends than details, and more for promoting memorability than for immediate use; bar graphs showed the opposite pattern.3-D graphs were preferred more for depicting details than trends, more for memorability than immediate use, and more for showing others than oneself.The reverse held for 2-D graphs.