4. A Relational Event Framework for Social Action

@article{Butts20084AR,
  title={4. A Relational Event Framework for Social Action},
  author={Carter T. Butts},
  journal={Sociological Methodology},
  year={2008},
  volume={38},
  pages={155 - 200}
}
  • C. Butts
  • Published 1 August 2008
  • Computer Science
  • Sociological Methodology
Social behavior over short time scales is frequently understood in terms of actions, which can be thought of as discrete events in which one individual emits a behavior directed at one or more other entities in his or her environment (possibly including himself or herself). Here, we introduce a highly flexible framework for modeling actions within social settings, which permits likelihood-based inference for behavioral mechanisms with complex dependence. Examples are given for the… Expand

Figures and Tables from this paper

Inferring social structure from continuous-time interaction data.
TLDR
It is argued that consistent deviations from expected behavior, rather than solely high frequency counts, are crucial for identifying well-established underlying social relationships. Expand
Hierarchical Models for Relational Event Sequences
TLDR
A hierarchical extension for modeling multiple such sequences, facilitating inferences about event-level dynamics and their variation across sequences is presented, and the efficacy of such sharing is illustrated through a set of prediction experiments. Expand
Using the relational event model (REM) to investigate the temporal dynamics of animal social networks
TLDR
This work demonstrates how the temporal structure of social interaction sequences can be quantified from disaggregated event data using the relational event model (REM), and discusses a case study on the European jackdaw, in which temporal patterns of persistence and reciprocity of action are of interest. Expand
Modeling relational events via latent classes
TLDR
This paper describes a generative model for dyadic events, where each event arises from one of C latent classes, and the properties of the event are chosen from distributions over these entities conditioned on the chosen class. Expand
Modeling the joint dynamics of relational events and individual states
  • Aaron Schecter, N. Contractor
  • Computer Science
  • 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
  • 2016
TLDR
This work proposes a model that integrates the relational event framework with actor-oriented models for behavioral change, allowing it to model the joint dynamics of relational events and individual states. Expand
Interactions, Actors, and Time: Dynamic Network Actor Models for Relational Events
Ample theoretical work on social networks is explicitly or implicitly concerned with the role of interpersonal interaction. However, empirical studies to date mostly focus on the analysis of stableExpand
A Relational Event Approach to Modeling Behavioral Dynamics
This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnetExpand
Stochastic blockmodeling of relational event dynamics
TLDR
This work combines ideas from stochastic blockmodeling and continuous-time network models by positing a latent partition of the node set such that event dynamics within and between subsets evolve in potentially distinct ways. Expand
An illustration of the relational event model to analyze group interaction processes
A fundamental assumption in the study of groups is that they are constituted by various interaction processes that are critical to survival, success, and failure. However, there are few methodsExpand
Non-parametric estimation of reciprocity and triadic effects in relational event networks
TLDR
This paper proposes to model the dynamic structure of reciprocal and triadic effects in relational event networks via stratified baseline hazards, which avoids having to define arbitrary temporal windows for what can be considered reciprocity or triadic closure. Expand
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 98 REFERENCES
FROM FACTORS TO ACTORS: Computational Sociology and Agent-Based Modeling
■ Abstract Sociologists often model social processes as interactions among variables. We review an alternative approach that models social life as interactions among adaptive agents who influence oneExpand
9. Neighborhood-Based Models for Social Networks
We argue that social networks can be modeled as the outcome of processes that occur in overlapping local regions of the network, termed local social neighborhoods. Each neighborhood is conceived as aExpand
Random graph models for temporal processes in social networks
We generalize the graphical modeling approach of p* social influence models to develop discrete time models for the temporal evolution of social networks. Plausible general processes pertaining toExpand
9. Models for Generalized Location Systems
TLDR
By leveraging established results in the fields of social network analysis, spatial statistics, and statistical mechanics, it is argued that sociologists can model complex social systems without sacrificing inferential tractability. Expand
8. Permutation Models for Relational Data
TLDR
This work proposes here an exponential family of permutation models that is suitable for inferring the direction and strength of association among dyadic relational structures and provides an easily performed maximum pseudo-likelihood estimation procedure for the permutation model family. Expand
Network models for social influence processes
This paper generalizes thep* class of models for social network data to predict individual-level attributes from network ties. Thep* model for social networks permits the modeling of socialExpand
A frame for organizational actions and macroactions
TLDR
Using the frame theoretically, it is suggested how people bring determinacy, purposefulness, and mobilizability to events, and thereby event sequences emerge that serve as "macroactions" - productive routines conducted in social establishments, and used as purposeful actions by individuals. Expand
Languages and grammars of action and interaction: A contribution to the formal theory of action
The languages of action and interaction studied in this paper arise from a formalization of the concept of a “production system” found in several recent empirical studies of human action. From aExpand
Models for longitudinal network datain
This chapter treats statistical methods for network evolution. It is argued that it is most fruitful to consider models where network evolution is represented as the result of many (usuallyExpand
Stochastic actor-oriented models for network change
A class of models is proposed for longitudinal network data. These models are along the lines of methodological individualism: actors use heuristics to try to achieve their individual goals, subjectExpand
...
1
2
3
4
5
...