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"Dyadic data analysis (Social sciences)"
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Twitter : a digital socioscope
How can Twitter data be used to study individual-level human behavior and social interaction on a global scale? This book introduces readers to the methods, opportunities, and challenges of using Twitter data to analyze phenomena ranging from the number of people infected by the flu, to national elections, to tomorrow's stock prices. Each chapter, written by leading domain experts in clear and accessible language, takes the reader to the forefront of the newly emerging field of computational social science.
Book
Dyadic-probabilistic methods in bilinear analysis
We demonstrate and develop dyadic–probabilistic methods in connection with non-homogeneous bilinear operators, namely singular
integrals and square functions. We develop the full non-homogeneous theory of bilinear singular integrals using a modern point of view.
The main result is a new global
While proving our bilinear results we also advance and
refine the linear theory of Calderón–Zygmund operators by improving techniques and results. For example, we simplify and make more
efficient some non-homogeneous summing arguments appearing in
eBook
Where Do Creative Interactions Come From? The Role of Tie Content and Social Networks
Understanding the determinants of creativity at the individual and organizational level has been the focus of a long history of research in various disciplines from the social sciences, but little attention has been devoted to studying creativity at the dyadic level.
Why are some dyadic interactions more likely than others to trigger the generation of novel and useful ideas in organizations?
As dyads conduit both knowledge and social forces, they offer an ideal setting to disentangle the effects of knowledge diversity, tie strength, and network structure on the generation of creative thoughts. This paper not only challenges the current belief that sporadic and distant dyadic relationships (weak ties) foster individual creativity but also argues that diverse and strong ties facilitate the generation of creative ideas. From a knowledge viewpoint, our results suggest that ties that transmit a wide (rather than narrow) set of knowledge domains (within the same tie) favor creative idea generation if exchanges occur with sufficient frequency. From a social perspective, we find that strong ties serve as effective catalysts for the generation of creative ideas when they link actors who are intrinsically motivated to work closely together. Finally, this paper also shows that dyadic network cohesion (i.e., the connections from the focal dyad to common contacts) does not always hinder the generation of creative ideas. Our empirical evidence suggests that when cohesion exceeds its average levels, it becomes detrimental to creative idea generation. Hypotheses are tested in a sociometric study conducted within the development department of a software firm.
Journal Article
Sensitivity of MRQAP Tests to Collinearity and Autocorrelation Conditions
Multiple regression quadratic assignment procedures (MRQAP) tests are permutation tests for multiple linear regression model coefficients for data organized in square matrices of relatedness among n objects. Such a data structure is typical in social network studies, where variables indicate some type of relation between a given set of actors. We present a new permutation method (called “double semi-partialing”, or DSP) that complements the family of extant approaches to MRQAP tests. We assess the statistical bias (type I error rate) and statistical power of the set of five methods, including DSP, across a variety of conditions of network autocorrelation, of spuriousness (size of confounder effect), and of skewness in the data. These conditions are explored across three assumed data distributions: normal, gamma, and negative binomial. We find that the Freedman–Lane method and the DSP method are the most robust against a wide array of these conditions. We also find that all five methods perform better if the test statistic is pivotal. Finally, we find limitations of usefulness for MRQAP tests: All tests degrade under simultaneous conditions of extreme skewness and high spuriousness for gamma and negative binomial distributions.
Journal Article
Using MEDYAD Macro to Test the Mediation Effect in Dyadic Data
Many variables studied in social and behavioral science researches inherently involve at least two individuals and the concept of dyad is used for these pairs with a certain relationship and connection between them and the concept of dyadic data is used for the data collected from these pairs. Analyzing the data obtained from these individuals (dyadic data) thinking that they are independent of each other may present misleading findings. In addition, complex models need to be established and tested to reveal how the pairs affect each other. Although programs such as LISREL, AMOS, MPLUS, R can be used to test various models established with dyadic data, many of these programs are paid or require researchers to know coding. The purpose of this article is to introduce the MEDYAD macro, which allows testing the mediation model (APIMeM) in distinguishable dyadic data without the need for coding. Within the scope of this study, the mediation model in dyadic data is first briefly explained, then the installation of the macro, preparation of the data file, and data analysis steps are given. Finally, how to interpret the analysis outputs is briefly explained.
Journal Article
Inferring friendship network structure by using mobile phone data
Data collected from mobile phones have the potential to provide insight into the relational dynamics of individuals. This paper compares observational data from mobile phones with standard self-report survey data. We find that the information from these two data sources is overlapping but distinct. For example, self-reports of physical proximity deviate from mobile phone records depending on the recency and salience of the interactions. We also demonstrate that it is possible to accurately infer 95% of friendships based on the observational data alone, where friend dyads demonstrate distinctive temporal and spatial patterns in their physical proximity and calling patterns. These behavioral patterns, in turn, allow the prediction of individual-level outcomes such as job satisfaction.
Journal Article
Individual and Partner Correlates of Sexual Satisfaction and Relationship Happiness in Midlife Couples: Dyadic Analysis of the International Survey of Relationships
The current research reports a dyadic analysis of sexual satisfaction, relationship happiness, and correlates of these couple outcomes in a large multinational dataset consisting of 1,009 midlife heterosexual couples (2,018 individuals) recruited in Japan, Brazil, Germany, Spain, and the United States (Heiman et al.,
2011
). Actor-Partner Interdependence Models (Kenny, Kashy, & Cook,
2006
) identified correlates of sexual satisfaction that included individuals’ reports of good health; frequent kissing, cuddling, and caressing; frequent recent sexual activity; attaching importance to one’s own and one’s partner’s orgasm; better sexual functioning; and greater relationship happiness. Even after controlling for individual-level effects,
partners
’ reports of good health; frequent kissing, cuddling, and caressing; frequent recent sexual activity; attaching importance to one’s own and one’s partner’s orgasm; better sexual functioning; and greater relationship happiness contributed significantly to predicting and understanding individuals’ sexual satisfaction. Correlates of relationship happiness included individuals’ reports of good health; frequent kissing, cuddling, and caressing; frequent recent sexual activity; attaching importance to one’s own and one’s partner’s orgasm; better sexual functioning; and greater sexual satisfaction, and once again, even after controlling for individual-level effects, partners’ reports of each of these correlates contributed significantly to predicting and understanding individuals’ relationship happiness. Interactions of individual and partner effects with participant gender are also reported. Current results demonstrate empirically that the partner “matters” to an individual’s sexual satisfaction and relationship happiness and indicate that a comprehensive understanding of factors contributing to these couple outcomes requires a couple-level research strategy. Partner effects, even when controlling for individual effects, were consistently observed, and explanation of sexual satisfaction and relationship happiness always depended on identifying and understanding mutual and concurrent individual and partner influences.
Journal Article
From unimodal to multimodal dynamics of verbal and nonverbal cues during unstructured conversation
Conversations encompass continuous exchanges of verbal and nonverbal information. Previous research has demonstrated that gestures dynamically entrain each other and that speakers tend to align their vocal properties. While gesture and speech are known to synchronize at the intrapersonal level, few studies have investigated the multimodal dynamics of gesture/speech between individuals. The present study aims to extend our comprehension of unimodal dynamics of speech and gesture to multimodal speech/gesture dynamics. We used an online dataset of 14 dyads engaged in unstructured conversation. Speech and gesture synchronization was measured with cross-wavelets at different timescales. Results supported previous research on intrapersonal speech/gesture coordination, finding synchronization at all timescales of the conversation. Extending the literature, we also found interpersonal synchronization between speech and gesture. Given that the unimodal and multimodal synchronization occurred at similar timescales, we suggest that synchronization likely depends on the vocal channel, particularly on the turn-taking dynamics of the conversation.
Journal Article
Inference in Linear Dyadic Data Models with Network Spillovers
When using dyadic data (i.e., data indexed by pairs of units), researchers typically assume a linear model, estimate it using Ordinary Least Squares, and conduct inference using “dyadic-robust” variance estimators. The latter assumes that dyads are uncorrelated if they do not share a common unit (e.g., if the same individual is not present in both pairs of data). We show that this assumption does not hold in many empirical applications because indirect links may exist due to network connections, generating correlated outcomes. Hence, “dyadic-robust” estimators can be biased in such situations. We develop a consistent variance estimator for such contexts by leveraging results in network statistics. Our estimator has good finite-sample properties in simulations, while allowing for decay in spillover effects. We illustrate our message with an application to politicians’ voting behavior when they are seating neighbors in the European Parliament.
Journal Article
Conducting dyadic, relational research about endometriosis: A reflexive account of methods, ethics and data analysis
Despite a growing literature on the value of relational data in studies of social phenomena, individuals still commonly constitute the basic unit of analysis in qualitative research. Methodological aspects of interviewing couples, particularly interviewing partners separately, and of conducting dyadic analysis have received scant attention. This article describes the experience of conducting separate interviews with both partners in 22 heterosexual couples (n = 44) in a study of the impact of the gynaecological condition endometriosis. In order to advance current methodological thinking regarding interviewing couples, we describe the dyadic, relational approach employed in designing the study and our specific method of dyadic analysis. We argue that utilising separate interviews with dyadic analysis rather than conducting joint interviews, while not without its ethical, practical and analytical challenges, offers considerable methodological benefits. Such an approach allows a unique relational insight into the impact of chronic illness on couples and how they navigate chronic illness by illuminating both shared and individual interpretations, experiences, understandings and meanings.
Journal Article