An integral representation for Besov and Lipschitz spaces

It is well known that functions in the analytic Besov space $B_1$ on the unit disk \D admits an integral representation f(z)=\ind\frac{z-w}{1-z\bar w}\,d\mu(w), where $\mu$ is a complex Borel measure with |\mu|(\D)<\infty. We generalize this result to all Besov spaces $B_p$ with $0<p\le1$ and all Lipschitz spaces $\Lambda_t$ with $t>1$. We also obtain a version for Bergman and Fock spaces

Exploring personality-targeted UI design in online social participation systems

We present a theoretical foundation and empirical findings demonstrating the effectiveness of personality-targeted design. Much like a medical treatment applied to a person based on his specific genetic profile, we argue that theory-driven, personality-targeted UI design can be more effective than design applied to the entire population. The empirical exploration focused on two settings, two populations and two personality traits: Study 1 shows that users' extroversion level moderates the relationship between the UI cue of audience size and users' contribution. Study 2 demonstrates that the effectiveness of social anchors in encouraging online contributions depends on users' level of emotional stability. Taken together, the findings demonstrate the potential and robustness of the interactionist approach to UI design. The findings contribute to the HCI community, and in particular to designers of social systems, by providing guidelines to targeted design that can increase online participation. Copyright © 2013 ACM

A Theory-Driven Design Framework for Social Recommender Systems

Social recommender systems utilize data regarding users’ social relationships in filtering relevant information to users. To date, results show that incorporating social relationship data – beyond consumption profile similarity – is beneficial only in a very limited set of cases. The main conjecture of this study is that the inconclusive results are, at least to some extent, due to an under-specification of the nature of the social relations. To date, there exist no clear guidelines for using behavioral theory to guide systems design. Our primary objective is to propose a methodology for theory-driven design. We enhance Walls et al.’s (1992) IS Design Theory by introducing the notion of “applied behavioral theory,” as a means of better linking theory and system design. Our second objective is to apply our theory-driven design methodology to social recommender systems, with the aim of improving prediction accuracy. A behavioral study found that some social relationships (e.g., competence, benevolence) are most likely to affect a recipient’s advice-taking decision. We designed, developed, and tested a recommender system based on these principles, and found that the same types of relationships yield the best recommendation accuracy. This striking correspondence highlights the importance of behavioral theory in guiding system design. We discuss implications for design science and for research on recommender systems

Personalityzation: UI Personalization, Theoretical Grounding in HCI and Design Research

Personalization is an effective means for accommodating differences between individuals. Therefore, the personalization of a system’s user interface (UI) features can enhance usability. To date, UI personalization approaches have been largely divorced from psychological theories of personality, and the user profiles constructed by extant personalization techniques do not map directly onto the fundamental personality traits examined in the psychology literature. In line with recent calls to ground the design of information systems in behavioral theory, we maintain that personalization that is informed by psychology literature is advantageous. More specifically, we advocate an approach termed “personalityzation”, where UI features are adapted to an explicit model of a user’s personality. We demonstrate the proposed personalityzation approach through a proof-of-concept in the context of social recommender systems. We identify two key contributions to information systems research. First, extending prior works on adaptive interfaces, we introduce a UI personalization framework that is grounded in psychology theory of personality. Second, we reflect on how our proposed personalityzation framework could inform the discourse in design research regarding the theoretical grounding of system’s design

Heuristic Principles and Differential Judgments in the Assessment of Information Quality

Information quality (IQ) is a multidimensional construct and includes dimensions such as accuracy, completeness, objectivity, and representation that are difficult to measure. Recently, research has shown that independent assessors who rated IQ yielded high inter-rater agreement for some information quality dimensions as opposed to others. In this paper, we explore the reasons that underlie the differences in the “measurability” of IQ. Employing Gigerenzer’s “building blocks” framework, we conjecture that the feasibility of using a set of heuristic principles consistently when assessing different dimensions of IQ is a key factor driving inter-rater agreement in IQ judgments. We report on two studies. In the first study, we qualitatively explored the manner in which participants applied the heuristic principles of search rules, stopping rules, and decision rules in assessing the IQ dimensions of accuracy, completeness, objectivity, and representation. In the second study, we investigated the extent to which participants could reach an agreement in rating the quality of Wikipedia articles along these dimensions. Our findings show an alignment between the consistent application of heuristic principles and inter-rater agreement levels found on particular dimensions of IQ judgments. Specifically, on the dimensions of completeness and representation, assessors applied the heuristic principles consistently and tended to agree in their ratings, whereas, on the dimensions of accuracy and objectivity, they not apply the heuristic principles in a uniform manner and inter-rater agreement was relatively low. We discuss our findings implications for research and practice

What\u27s in a Stream? Understanding Video Gamers\u27 Perceptions regarding Streaming and its Legitimacy

Video game streaming – live interactive broadcasts of gameplay on online platforms such as YouTube, has emerged as an important phenomenon in the world of video games, with leading streamers attracting the viewership of millions. The public’s perception of streaming, and its legitimacy, is still very much undecided. We seek to understand gamers’ and streamers’ normative perceptions of streaming. Employing an extreme case study methodology, we analyze the Reddit discussion threads and streamers’ video-blogs following the decision of a game producer, Altus, to restrict streaming of its Persona 5 game. We reveal ambiguities amongst community regarding the nature of streaming, with perceptions ranging between streaming as a broadcast of game, a creative performance, or a community activity. Further, we discover the factors that influence gamers’ perceptions regarding streaming legitimacy. We discuss implications for HCI and IS research and practice