TL;DR: This paper presents mathematical representation of social networks in the social and behavioral sciences through the lens of Dyadic and Triadic Interaction Models, which describes the relationships between actor and group measures and the structure of networks.
Abstract: Part I. Introduction: Networks, Relations, and Structure: 1. Relations and networks in the social and behavioral sciences 2. Social network data: collection and application Part II. Mathematical Representations of Social Networks: 3. Notation 4. Graphs and matrixes Part III. Structural and Locational Properties: 5. Centrality, prestige, and related actor and group measures 6. Structural balance, clusterability, and transitivity 7. Cohesive subgroups 8. Affiliations, co-memberships, and overlapping subgroups Part IV. Roles and Positions: 9. Structural equivalence 10. Blockmodels 11. Relational algebras 12. Network positions and roles Part V. Dyadic and Triadic Methods: 13. Dyads 14. Triads Part VI. Statistical Dyadic Interaction Models: 15. Statistical analysis of single relational networks 16. Stochastic blockmodels and goodness-of-fit indices Part VII. Epilogue: 17. Future directions.
TL;DR: A new corpus named the “interactive emotional dyadic motion capture database” (IEMOCAP), collected by the Speech Analysis and Interpretation Laboratory at the University of Southern California (USC), which provides detailed information about their facial expressions and hand movements during scripted and spontaneous spoken communication scenarios.
Abstract: Since emotions are expressed through a combination of verbal and non-verbal channels, a joint analysis of speech and gestures is required to understand expressive human communication. To facilitate such investigations, this paper describes a new corpus named the “interactive emotional dyadic motion capture database” (IEMOCAP), collected by the Speech Analysis and Interpretation Laboratory (SAIL) at the University of Southern California (USC). This database was recorded from ten actors in dyadic sessions with markers on the face, head, and hands, which provide detailed information about their facial expressions and hand movements during scripted and spontaneous spoken communication scenarios. The actors performed selected emotional scripts and also improvised hypothetical scenarios designed to elicit specific types of emotions (happiness, anger, sadness, frustration and neutral state). The corpus contains approximately 12 h of data. The detailed motion capture information, the interactive setting to elicit authentic emotions, and the size of the database make this corpus a valuable addition to the existing databases in the community for the study and modeling of multimodal and expressive human communication.
TL;DR: In this article, the dyadic interaction between a service provider and a customer is an important determinant of the customer's global satisfaction with the service, based on role theory, and it is shown that dyadic interactions between service providers and customers are important determinants of customer satisfaction.
Abstract: This article proposes that the dyadic interaction between a service provider and a customer is an important determinant of the customer's global satisfaction with the service. Based on role theory,...
TL;DR: Individuals who scored high on the Relational-Interdependent Self-Construal (RISC) Scale characterized their important relationships as closer and more committed than did individuals who scored low on this measure and were more likely to take into account the needs and wishes of others when making decisions.
Abstract: Three studies describe the development and validation of a measure of the relational-interdependent self-construal, which is defined as the tendency to think of oneself in terms of relationships with close others. Study 1 reports the development, psychometric properties, and tests of validity of this new measure. Individuals who scored high on the Relational-Interdependent Self-Construal (RISC) Scale characterized their important relationships as closer and more committed than did individuals who scored low on this measure (Study 1) and were more likely to take into account the needs and wishes of others when making decisions (Study 2). In Study 3, using a dyadic interaction paradigm with previously unacquainted participants, the partners of persons who scored high on the RISC scale viewed them as open and responsive to their needs and concerns; these perceptions were related to positive evaluations of the relationship.
TL;DR: This article investigated the nature of dyadic interaction in an adult ESL classroom and found that certain dyadic interactions are more conducive than others to language learning, which is explained by reference to Vygotsky's theory of cognitive development.
Abstract: This study investigated the nature of dyadic interaction in an adult ESL classroom. The study was longitudinal, classroom based, and examined the nature of interaction between 10 pairs of adult ESL students over a range of language tasks and over time (a semester). Four distinct patterns of dyadic interaction were found. These patterns are distinguishable in terms of equality and mutuality (Damon & Phelps, 1989). More importantly, the findings suggest that certain patterns of dyadic interaction are more conducive than others to language learning. These findings are explained by reference to Vygotsky’s theory of cognitive development.