Dynamic Network Lab

Mission

To use social network, motivation, and decision science to improve individual, social, and organizational systems.

Networks, Motivation, and Decision-Making

The lab combines social network analysis, motivation, and decision-making approaches to more fully explain how social networks wield their power on important targets: goals, important decisions, specific behaviors, performance, climates, and system well-being. Largely grounded in dynamic network theory (DNT), network goal analysis (NGA) aims to portray these system dynamics at individual, group, organizational, or international levels, including those with conflict. NGA can also be used with other theoretical approaches, not just DNT, whenever social networks and goals (or target behaviors) are the focus. In contrast, we also use behavioral reasoning theory (BRT) to examine how people's reasoning and counter-argument processes within the network help trigger motivated goal striving and behavior at the individual levels. Utilizing both DNT and BRT together is presumed to provide a richer, yet highly operational understanding of system behavior with direct implications for strategic change to improve system functioning.

How are networks connected to motivation and decision-making?

Our approach inserts goal nodes into social networks to provide new insights about system functioning (Westaby and colleagues). Goals nodes are inherently motivational and can represent many important things, such as goals, missions, objectives, important decisions, intentions, wishes, needs, dreams, or target behaviors. Thus, inserting goal nodes into network structures has the capacity to help explain system functioning across diverse human experiences.

Single Goal Node Example

Two entities are independently goal striving on their own (G) to accomplish the goal (produced from our Lab's R programming).

Online Example

Six enties indepedently responding to a question posted online (i.e., question goal node [circled]; Kumu program used to upload our Lab's DNT-based code).

Full System Example

The full multipedent social network independently and dependently involved in the goal (Westaby & Parr, 2020; produced from our Lab's R programming):

KEY for network goal analysis

KEY pdf

Online Egocentric Example

The ciricled entity's goal striving (G) and system supporting (S) toward its question goal node responses shown, some of which is shared with others (Kumu program used to upload our Lab's DNT-based code).

Full Online Analysis

(Kumu program used to upload our Lab's DNT-based code); G = indepedent blue responding directly to question goal node; S = depedent system support responses.

Comparison to Traditional Social Network

Comparing Approaches

Network goal analyis (NGA) examines how social networks pivot around important goals with theoretically determined motivational linkages. In contrast, traditional social network analysis (SNA) focuses on social structural linkages without explict links to goal nodes. However, the approaches are complementary, depending on the scientific or practice question.

Click to compare

Break it down and build it back up

The Lab's surveys, computer visualizations, and reports allow each sub-network to be examined separately to better understand complex systems. It breaks down the complexity into meaningful chunks to maximize meaning and understanding. We also combine the concepts to provide overall system-level summaries of the networks, such as their positive focus ratio and network affirmation ratio. Out decision tools also provide feedback as to how people may be leaning in their decisions, based upon specific reasoning, counter-arguments, confidence, and information search.

View more data visualization.

Collaborating on New Research

Researchers engaged in rigorous projects examining important target goals, decisions, behaviors, or general life or work networks can contact us to inquire about using our decision-making calculators and/or network goal surveys and computer visualizations.

Recent Activities

Fall, 2020, Columbia University, New York, NY

Dynamic Network Lab Special Sessions – Ph.D. Students, Invited Professors and Network and Behavioral Scientists
Social Networks and Performance Lecture Modules

Summer, 2020, Academcy of Management

Prof. Westaby - Presentation of at the Academy of Management Conference entitled: Modeling Massive Social Network Problem Solving via Network Goal Analysis vs Social Network Analysis. Eccho Yu is a collaborator on this project.

Spring, 2020

Prof. Westaby (Lab Director) - Chair - Accepted session at the Society for Industrial and Organizational Psychology (SIOP) conference on “New advances in social network science and practice in organizations”. Panel members were to include leading experts on social networks in organizations: Prof. Prasad Balkundi, Prof. Noshir Contractor, Prof. Travis Grosser, Prof. David Krackhardt, and Prof. James Westaby.

Prof. Westaby (Lab Director) and Adam Parr (DNL Associate) - Presentation at the Society for Industrial and Organizational Psychology (SIOP) conference: “Social networks and team goals: New insights through network goal analysis”.