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Strategic tradeoffs in competitor dynamics on adaptive networks
Laurent Hébert-Dufresne1,2, Antoine Allard3, Pierre-André Noël4
1Santa Fe Institute, Santa Fe, NM, 87501, USA.
Scientific Reports
|August 10, 2017
Summary
Social competition strategies, like those in political campaigns, create adaptive networks. Tradeoffs between aggressiveness and defensiveness lead to paradoxical dynamics, with no optimal strategy in three-competitor systems.
Area of Science:
- Social Network Analysis
- Evolutionary Game Theory
- Computational Social Science
Background:
- Social competitions, such as political campaigns, exhibit diverse strategies, ranging from open debate to echo chamber formation.
- Traditional network analysis often assumes static and symmetric structures, limiting the study of dynamic competitor interactions.
- Network structure can be viewed as a reflection of competitor strategies, enabling the study of competition on adaptive networks.
Purpose of the Study:
- To investigate competition dynamics on adaptive networks shaped by competitor strategies.
- To explore the impact of tradeoffs between aggressiveness and defensiveness on social competition outcomes.
- To provide a game-theoretical perspective on online political debates by analyzing social network structures.
Main Methods:
- Modeling competition dynamics on adaptive networks.
- Analyzing the effects of varying levels of aggressiveness and defensiveness in competitor strategies.
- Examining two- and three-competitor systems to identify optimal strategies and paradoxical behaviors.
- Mapping emergent social network structures to payoff matrices from evolutionary game theory.
Main Results:
- Tradeoffs between aggressiveness and defensiveness generate paradoxical behaviors, including non-transitive dynamics.
- A single optimal strategy exists in two-competitor systems.
- In three-competitor systems, no optimal strategy emerges, and extreme strategies can disproportionately influence outcomes.
- The model's generated social network structures correlate with specific payoff matrices.
Conclusions:
- Adaptive network models offer insights into complex social competition dynamics.
- Understanding strategy tradeoffs is crucial for predicting competition outcomes in social and political contexts.
- Social network structure can serve as a measurable metric for social games, providing a game-theoretical lens for analyzing online political discourse.
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