Psychological studies of relationships tend to focus on specific types of close personal relationships (romantic, parent-offspring, friendship) and examine characteristics of both the individuals and the dyad. This paper looks more broadly at the wider range of relationships that constitute an individual's personal social world. Recent work on the composition of personal social networks suggests that they consist of a series of layers that differ in the quality and quantity of relationships involved. Each layer increases relationship numbers by an approximate multiple of 3 (5-15-50-150) but decreasing levels of intimacy (strong, medium, and weak ties) and frequency of interaction. To account for these regularities, we draw on both social and evolutionary psychology to argue that relationships at different layers serve different functions and have different cost-benefit profiles. At each layer, the benefits are asymptotic but the costs of maintaining a relationship at that level (most obviously, the time that has to be invested in servicing it) are roughly linear with the number of relationships. The trade-off between costs and benefits at a given level, and across the different types of demands and resources typical of different levels, gives rise to a distribution of social effort that generates and maintains a hierarchy of layered sets of relationships within social networks. We suggest that, psychologically, these trade-offs are related to the level of trust in a relationship, and that this is itself a function of the time invested in the relationship.Social relationships are studied in numerous fields of basic and applied psychology. Within social psychology, relationships are a fundamental component in models of

A century of research on small groups has yielded bountiful findings about many specific features and processes in groups. Much of that work, in line with a positivist epistemology that emphasizes control and precision and favors the laboratory experiment over other data collection strategies, has also tended to treat groups as though they were simple, isolated, static entities. Recent research trends that treat groups as complex, adaptive, dynamic systems open up new approaches to studying groups. In line with those trends, a theory of groups as complex systems is offered and some methodological and conceptual issues raised by this theory are identified. A 3-pronged research strategy based on theory development, computational modeling, and empirical research that holds promise for illuminating the dynamic processes underlying the emergence of complexity and the ongoing balance of continuity and change in groups is proposed.

This article describes the network approach to small groups. First, the core constructs that compose social network research are explained. The primary theories that provide the intellectual underpinning of the network approach are described, including theories of self-interest, theories of social exchange or dependency, theories of mutual or collective interest, cognitive theories, and theories of homophily. Highlights of the empirical work examining the internal and external networks of small groups is summarized. Finally, the primary challenges researchers face when applying the network perspective to small groups, and the primary benefits that can accrue to researchers who adopt that perspective, are enumerated.

Group identification is defined as member identification with an interacting group and is distinguished conceptually from social identity, cohesion, and common fate. Group identification is proposed to have three sources: cognitive (social categorization), affective (interpersonal attraction), and behavioral (interdependence). Inconsistent use of the term and problematic measurement mar existing literature on group identity and group identification. A new group identification scale, composed of three subscales that match the tripartite model for the cognitive, affective, and behavioral sources, is presented and its psychometric properties described.