Kerk F. Kee

The Organization and Management of Grid Infrastructures

Grid computing technology has become fundamental to e-Science. As the virtual organizations established by scientific communities progress from testing their applications to more routine usage, maintaining reliable and adaptive grid infrastructures becomes increasingly important.

The Dialectical Tensions in the Funding Infrastructure of Cyberinfrastructure

This article focuses on funding for cyberinfrastructure and how funding affects the cyberinfrastructure foundation laid, who completes the work, and what the outcomes of the funding are. By following qualitative procedures and thematic analysis, we identify five dialectical tensions across three difference levels of institutions, individuals, and ideologies in the funding infrastructure of cyberinfrastructure. Through an organizational communication lens, we define funding infrastructure as the communication arrangements of institutions, individuals, and ideologies that must be coordinated in order for cyberinfrastructure to be brought into existence. These communication arrangements include salient motivations of and financial compensations for individuals who engage in them. They also comprise explicit policies about funding, as well as implicit ideologies about science embedded in funding, as held by institutions involved in these communication arrangements.

Information diffusion, Facebook clusters, and the simplicial model of social aggregation: a computational simulation of simplicial diffusers for community health interventions

Abstract By integrating the simplicial model of social aggregation with existing research on opinion leadership and diffusion networks, this article introduces the constructs of simplicial diffusers (mathematically defined as nodes embedded in simplexes; a simplex is a socially bonded cluster) and simplicial diffusing sets (mathematically defined as minimal covers of a simplicial complex; a simplicial complex is a social aggregation in which socially bonded clusters are embedded) to propose a strategic approach for information diffusion of cancer screenings as a health intervention on Facebook for community cancer prevention and control. This approach is novel in its incorporation of interpersonally bonded clusters, culturally distinct subgroups, and different united social entities that coexist within a larger community into a computational simulation to select sets of simplicial diffusers with the highest degree of information diffusion for health intervention dissemination. The unique contributions of the article also include seven propositions and five algorithmic steps for computationally modeling the simplicial model with Facebook data.

Social Groups, Social Media, and Higher Dimensional Social Structures: A Simplicial Model of Social Aggregation for Computational Communication Research

By building on classical communication network literature, we present a computational approach to modeling tightly bound groups and social aggregations as higher dimensional social structures. Using the mathematical theory of simplicial complexes, these groups can be represented by geometric spatial elements (or simplexes) and a social aggregation a collection of simplexes (i.e., a simplicial complex). We discuss the uniting conditions that define a tightly bound group as a higher-dimensional group, which can be mathematically treated as nodes in a network of social aggregation. We utilize Facebook as a particularly relevant example to demonstrate innovative ways researchers can tap into digital data, in addition to traditional self-reported data, to advance communication research using the simplicial model, although the approach is applicable to many questions not involving communication technology.

Social media at work

Limited research has studied workplace satisfaction in a computer-mediated context, particularly with the use of social media. Based on an analysis of an online survey of working adults (N=512) in various companies and organizations in a metropolitan area in Southern California, we tested the relationships among time spent on Facebook interacting with co-workers, employment status, and job satisfaction. Results show that an employees satisfaction at work is positively associated with the amount of time they spend on Facebook interacting with co-workers. Contrary to our initial predictions, results to the second and third hypotheses revealed that part time employees reported having spent the highest amount of time on Facebook with their co-workers, and contract employees reported the highest degree of job satisfaction at work. Results have implications for Facebook as a strategic platform for promoting employee satisfaction at work, and Facebook a social network/ing platform for part time employees seeking further social integration and professional connection. Job satisfaction is positively associated with time on Facebook with co-workers.Part time employees report the highest amount of time on Facebook with co-workers.Contract employees reported the highest degree of job satisfaction at work.Facebook can be an organizational strategy to promote job satisfaction at work.This paper highlights a positive outcome of Facebook use among co-workers.

A regression-based study using jackknife replicates of HINTS III data: Predictors of the efficacy of health information seeking

Abstract The current study determines and assesses the effects of the statistically significant predictors of the efficacy of health information seeking through a regression-based analysis of the 2007 edition of the Health Information National Trends Survey (HINTS) data. The HINTS III data were collected through list-assisted random digit dialing and mail-in questionnaire with a natural corresponding unstratified and cluster sampling design with jackknife replicates and were analyzed using generalized linear models with jackknife parameter estimation based on the complete and 50 jackknife replicate datasets. The resampling-based analytic approaches, such as the jackknife and bootstrap, generally provide unbiased parameter estimates and are the preferred methods for complex survey data analyses. We implemented an exhaustive search through all potential predictors of the efficacy in health information seeking combined with model building based on forward selection and backward elimination of covariates to derive the best predictive model. This model-based and data-driven approach to detect and assess the relative effects of the significant predictors of the aforesaid outcome variable of interest is a greatly advantageous alternative to the common hypotheses-based analyses. Our results show that numeracy, education, patient health care satisfaction (with the health information given by their health provider), health information dissatisfaction, general health, and psychological distress are the optimal covariates significantly associated with the efficacy of health information seeking. Interestingly, many usually important background covariates such as race, income, gender, geographical location, and others were not significant predictors of the outcome variable of interest. The conclusions of our analysis reveal new insights into the complexity of the efficacy of health information seeking and will undoubtedly have important implications on the design and success of future health care messages and campaigns.

Running Out of Water! Developing a Message Typology and Evaluating Message Effects on Attitude Toward Water Conservation

ABSTRACT In three phases, this study identifies and evaluates the major messages being used in communication campaigns focused on the ongoing drought in California. A literature review in Phase 1 resulted in a typology of 12 message strategies. Following this typology, trained coders in Phase 2 evaluated water conservation messages (N = 100) to determine whether each message utilized one or multiple strategies. The results revealed various frequencies of strategy application; and a correlational analysis rendered a pattern of strategy use in combinations. Phase 3 focused on a controlled message experiment applying the three most relevant strategies: conservation tips, loss aversion, and evidence of drought. Analysing data sampled from California residents (N = 180), conservation messages, regardless of the strategy, led to attitude change in a negative direction. Additional analyses revealed interesting patterns of combinatorial strategy effects. The results call for a re-examination of message strategies as they may lead to several unfavourable outcomes.

Developing and validating the A-B-C framework of information diffusion on social media

This research addresses the problem of promoting information diffusion, the extent to which information spreads, on social media platforms. Utilizing the number of views, comments, and shares as indicators of diffusion, we developed and validated an original research framework based on the big data approach (using all the blog posts in a university in the year 2013; N = 4120). This A-B-C framework (1) analyzes the textual features of blog posts using linguistic inquiry and word count (Study 1), (2) applies the former results to build message concepts (Study 2), and (3) creates validated instructional material based on message concepts to promote message diffusion among blog readers (Study 3). This framework supports operational strategies for developing strategic and corporate communication material aimed at increasing diffusion.

Towards an integrated model of strategic environmental communication: advancing theories of reactance and planned behavior in a water conservation context

ABSTRACT This study demonstrates how communication research can be strategically applied to address environmental problems in modern societies. To accomplish this goal, this research advances an integrated communication model based on psychological reactance theory and the theory of planned behavior to explain negative attitude change that can occur when people are exposed to water conservation campaigns [Liang, Y. J., Henderson, L.K., & Kee, K. F. (2017). Running out of water! Developing a message typology and evaluating message effects on attitude toward water conservation. Environmental Communication. doi:10.1080/17524032.2017.1288648]. The data fit the hypothesized model, synthesizing message-, social-, and individual-based processes to predict their effects on behavioral intention towards water conservation. Interestingly, data show that (1) combinations of message strategies affect reactance differently, and (2) subjective norm and perceived behavioral control negatively correlated with threat to freedom. These results point to the practical implication that environmental communication to promote voluntary water conservation are effective when campaign messages are designed to reduce threat to freedom, induce social norms, and increase self-efficacy. We call the documented research process strategic environmental communication, which focuses on the joint application of evidence and theory towards addressing environmentally motivated problems.

The Ten Adoption Drivers of Open Source Software That Enables e-Research in Data Factories for Open Innovations

This chapter describes ten drivers of the adoption of open source software that enables e-research in data factories for open innovations. More specifically, the chapter discusses the emerging phenomena of big data and e-research, along with their various defining characteristics. Then the chapter makes a case for the importance of understanding the adoption of open source software for processing and harnessing big data. In other words, big data which remain in the raw form will continue to be big data with hidden insights uncovered without the adoption of appropriate software. Open source software applications, along with the larger concept of cyberinfrastructure, play a critical role in our ability to optimize the full potential of big data. The chapter also includes critical questions community stakeholders should keep in mind when promoting the diffusion and dissemination of good software applications that will support data factories for open innovations.