An efficient counting method for the colored triad census

The triad census is an important approach to understand local structure in network science, providing comprehensive assessments of the observed relational configurations between triples of actors in a network. However, researchers are often interested in combinations of relational and categorical nodal attributes. In this case, it is desirable to account for the label, or color, of the nodes in the triad census. In this paper, we describe an efficient algorithm for constructing the colored triad census, based, in part, on existing methods for the classic triad census. We evaluate the performance of the algorithm using empirical and simulated data for both undirected and directed graphs. The results of the simulation demonstrate that the proposed algorithm reduces computational time many-fold over the naive approach. We also apply the colored triad census to the Zachary karate club network dataset. We simultaneously show the efficiency of the algorithm, and a way to conduct a statistical test on the census by forming a null distribution from 1,000 realizations of a mixing-matrix conditioned graph and comparing the observed colored triad counts to the expected. From this, we demonstrate the method's utility in our discussion of results about homophily, heterophily, and bridging, simultaneously gained via the colored triad census. In sum, the proposed algorithm for the colored triad census brings novel utility to social network analysis in an efficient package

Constructing and Modifying Sequence Statistics for relevent Using informR in R

The informR package greatly simplifies the analysis of complex event histories in R by providing user friendly tools to build sufficient statistics for the relevent package. Historically, building sufficient statistics to model event sequences (of the form a / b) using the egocentric generalization of Butts’ (2008) relational event framework for modeling social action has been cumbersome. The informR package simplifies the construction of the complex list of arrays needed by the rem() model fitting for a variety of cases involving egocentric event data, multiple event types, and/or support constraints. This paper introduces these tools using examples from real data extracted from the American Time Use Survey

Recommendations for accelerating open preprint peer review to improve the culture of science

Peer review is an important part of the scientific process, but traditional peer review at journals is coming under increased scrutiny for its inefficiency and lack of transparency. As preprints become more widely used and accepted, they raise the possibility of rethinking the peer-review process. Preprints are enabling new forms of peer review that have the potential to be more thorough, inclusive, and collegial than traditional journal peer review, and to thus fundamentally shift the culture of peer review toward constructive collaboration. In this Consensus View, we make a call to action to stakeholders in the community to accelerate the growing momentum of preprint sharing and provide recommendations to empower researchers to provide open and constructive peer review for preprints

Recommendations for accelerating open preprint peer review to improve the culture of science

Peer review is an important part of the scientific process, but traditional peer review at journals is coming under increased scrutiny for its inefficiency and lack of transparency. As preprints become more widely used and accepted, they raise the possibility of rethinking the peer-review process. Preprints are enabling new forms of peer review that have the potential to be more thorough, inclusive, and collegial than traditional journal peer review, and to thus fundamentally shift the culture of peer review toward constructive collaboration. In this Consensus View, we make a call to action to stakeholders in the community to accelerate the growing momentum of preprint sharing and provide recommendations to empower researchers to provide open and constructive peer review for preprints

Yet Another Statistical Analysis of Bob Ross Paintings

In this paper, we analyze a sample of clippings from paintings by the late artist Bob Ross. Previous work focused on the qualitative themes of his paintings (Hickey, 2014); here, we expand on that line of research by considering the colorspace and luminosity values as our data. Our results demonstrate the subtle aesthetics of the average Ross painting, the common variation shared by his paintings, and the structure of the relationships between each painting in our sample. We reveal, for the first time, renderings of the average paintings and introduce “eigenross” components to identify and evaluate shared variance. Additionally, all data and code are embedded in this document to encourage future research, and, in the spirit of Bob Ross, to teach others how to do so

ConvertAllImages.sh

Small bourne shell script using imagemagick to convert image clippings

Social Time: Variations in Social Interaction Across the Life Course

Older and younger people have long been known to have very different social lives. Past research on support and close confidant networks has shown that old age is associated with less and more kin-focused social interaction. Yet, we know remarkably little about the ways in which older versus younger people access their personal networks during the comings-and-goings of daily living. Psychosocial theories, which emphasize preference and personality differences between the young and old, have richly informed explanations of why aging is associated with changes in various network characteristics. However, social structural theories, which emphasize how the availability of other people to interact with varies with the life course, has garnered much less attention as explanations of network differences between the young and old. This dissertation advances the state of knowledge on this topic by examining how people spend their time, who they spend their time with, and the extent to which age differences in time use are explained by life course and social structural factors. To address my research questions, I leverage interpersonal data on who is present during the performance of daily activities from a large sample of U.S. population using the American Time Use Survey. I find that life course and social structural variables account for a large part of the relationship between age and time spent with others. Depending on the relation, the social structure accounts for between 14% and 65% of the variance in social time. I find that elderly people tend to interact with others during leisure activities that are sui generis social while younger adults spend their leisure time with others on all types of leisure. Furthermore, poor health tends to suppress the effects of age on time spent doing certain activities (like social leisure) and tends to augment the effects of age on other activities (like traveling alone). These results strongly suggest that the social structure plays an important role in shaping social interaction across the life course