Jim WestabyTopics of Interest:
Dynamic Network Theory
Our research has focused on how social networks influence goal pursuit, performance, and emotional contagion in social and organizational settings. Social networks permeate our lives, both in-person and online, such as through social networking and social media platforms (e.g., Facebook, Twitter, and LinkedIn). After years in development, our work has culminated in the development of dynamic network theory (DNT) to predict and understand the way social networks impact goal pursuits in various domains (Westaby, 2012). For example, individuals have used the theory to model the in-person networks involved in their pursuits to get jobs, start businesses, lose weight, run marathons, quit tobacco, and improve social and organizational systems, among many others. In contrast to the classic study of social network structure alone, DNT examines how a taxonomy of only 8 social network roles can explain the complex ways in which networks wield their influence on our goals, dreams, and aspirations. Dynamic network charting, another new contribution, is also used in the theory to model how these roles are involved in specific goal pursuit cases.
The 8 Social Network Roles
The first two roles in dynamic network theory (Westaby, 2012) represent the functional ways that entities in social networks are involved in our goal pursuits: goal strivers (G) and system supporters (S). Together, these roles show the network motivation underlying our pursuits. The third and fourth roles show network resistance working against our goals: goal preventers (P) and supportive resisters (V), which helps explain the genesis of many human conflicts. The fifth and sixth roles show how individuals in social networks demonstrate negativity toward our pursuits (i.e., system negators, N) or our negativity toward those resisting us (i.e., system reactors, R). These roles can illustrate prejudice and hostility linkages as well. The last two roles illustrate the peripheral behaviors in networks that can inadvertently influence our goal pursuits: interactants (I), who may be in the vicinity of our goal pursuits but not paying attention to them, and observers (O), who are watching or aware of our goal pursuits but are not helping, hurting, or closely interacting with us.
Dynamic Network Charts
The following presents a very simple example illustrating how some of the social network roles in the theory are modelled in dynamic network charts, which are different from traditional network diagrams, because they directly insert goals into the social network. This chart is examining who’s involved in Joan’s goal to get her project completed tonight:
Other Key Concepts
A number of other original concepts are introduced in the theory to explain important dynamics related to dynamic network systems, such as the “network rippling of emotions,” which explains how emotions become contagious in networks based on goal achievement or failure, and “dynamic network intelligence” (DNI), which explains how accurate individuals are in knowing other people’s roles in their goal pursuits. Also, the theory has many applications for the study of human conflict, given its ability to model conflict linkages in dynamic network systems. Westaby and Redding (2014) illustrated these applications and demonstrated the unique aspects of the theory in comparison to traditional network approaches to conflict. They also developed network conflict worksheets to show how individuals in a network can be categorized to understand their motivational roles on the different sides of a conflict, which may be easier to apply for practitioners. Our work is now generalizing this worksheet method to more general goal pursuits.
- Jim Westaby, Ph.D.
- Danielle Pfaff, Ph.D. Student
- Nick Redding, Ph.D. Student
- Examining the hidden psychological world underlying our observable behavior: A review of different theories and methods
- A review of the social media literature through dynamic network theory
- Examining the reliability and validity of dynamic network charts
- Comparing dynamic network charts to traditional social network diagrams
- Using dynamic network theory for social interaction analyses in dyads, groups, and social media
- Explaining complex organizational behavior through network dynamics
First, our past work has tested different aspects of dynamic network theory (Westaby, 2012) and presented this work at various social psychology and industrial-organizational psychology conferences. Second, our previous, more micro work has developed and tested behavioral reasoning theory (Westaby, 2005; Westaby, Probst, & Lee, 2010), which is geared toward predicting human behavior from individual perceptions alone, such as intentions, attitudes, subjective norms, perceived control, and reasons (for and against) a behavior. Ph.D. students have used concepts from the different theories in our lab for their dissertations, and other researchers have used the theoretical concepts to ground their empirical studies.
Westaby, J. D. (2012). Dynamic network theory: How social networks influence goal pursuit. Washington, DC: American Psychological Association.
Westaby, J.D., & Redding, N. (2014/in press). Social networks, social media, and conflict resolution. In P.T. Coleman, M. Deutsch, & E.C. Marcus (Eds.), The handbook of conflict resolution: Theory and practice (3rd ed.). San Francisco, CA: Jossey-Bass.
Westaby, J. D. (2012). Social networks, social support, and goal pursuit: Testing dynamic network theory. Paper presented at the Society for Personality and Social Psychology.
Westaby, J. D. (2005). Behavioral reasoning theory: Identifying new linkages underlying intentions and behavior. Organizational Behavior and Human Decision Processes, 98, 97-120.
Westaby, J. D., Probst, T. M., & Lee, B. C. (2010). Leadership decision-making: A behavioral reasoning theory analysis. Leadership Quarterly, 21, 481-495.
Westaby, J. D., Versenyi, A., & Hausmann, R. C. (2005). Intentions to work during terminal illness: An exploratory study of antecedent conditions. Journal of Applied Psychology, 90, 1027-1035.
Westaby, J. D., & Lowe, J. K. (2005). Risk taking orientation and injury among youth workers: Examining the social influence of supervisors, coworkers, and parents. Journal of Applied Psychology, 90, 1297-1305.