Polarization is a topic of intense interest among social scientists, but there is significant dis... more Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomena and little understanding of underlying mechanics. A first problem , we argue, is that polarization appears in the literature as not one concept but many. In the first part of the paper, we distinguish nine phenomena that may be considered polarization with suggestions of appropriate measures for each. In the second part of the paper, we apply this analysis to evaluate the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization.
Identifying key agents for the transmission of diseases (ideas, technology, etc.) across social n... more Identifying key agents for the transmission of diseases (ideas, technology, etc.) across social networks has predominantly relied on measures of centrality on a static base network or a temporally flattened graph of agent interactions. Various measures have been proposed as the best trackers of influence, such as degree centrality, betweenness, and k-shell, depending on the structure of the connectivity. We consider SIR and SIS propagation dynamics on a temporally-extruded network of observed interactions and measure the conditional marginal spread as the change in the magnitude of the infection given the removal of each agent at each time: its temporal knockout (TKO) score. We argue that this TKO score is an effective benchmark measure for evaluating the accuracy of other, often more practical, measures of influence. We find that none of the network measures applied to the induced flat graphs are accurate predictors of network propagation influence on the systems studied; however, temporal networks and the TKO measure provide the requisite targets for the search for effective predictive measures.
This paper draws distinctions among various concepts related to tipping points, robustness, path ... more This paper draws distinctions among various concepts related to tipping points, robustness, path dependence, and other properties of system dynamics. For each concept a formal definition is provided that utilizes Markov model representations of systems. We start with the basic features of Markov models and definitions of the foundational concepts of system dynamics. Then various tipping point-related concepts are described, defined, and illustrated with a simplified graphical example in the form of a stylized state transition diagram. The tipping point definitions are then used as a springboard to describe, formally define, and illustrate many distinct concepts collectively referred to as "robustness". The final definitional section explores concepts of path sensitivity and how they can be revealed in Markov models. The definitions provided are presented using probability theory; in addition, each measure has an associated algorithm using matrix operations (excluded from current draft). Finally an extensive future work section indicates many directions this research can branch into and which methodological, conceptual, and practical benefits can be realized through this suite of techniques.
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2004, 2004
This paper presents a generalized methodology for propagating known or estimated levels of indivi... more This paper presents a generalized methodology for propagating known or estimated levels of individual source document truth reliability to determine the confidence level of a combined output. Initial document certainty levels are augmented by (i) combining the reliability measures of multiply sources, (ii) incorporating the truth reinforcement of related elements, and (iii) incorporating the importance of the individual elements for
2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH), 2009
... Aaron L Bramson Center for the Study of Complex Systems University of Michigan 321A West Hall... more ... Aaron L Bramson Center for the Study of Complex Systems University of Michigan 321A West Hall 1085 S. University Ave. ... Jenna Bednar & Scott Page claim, “Culture can be defined as individual and community level behavioral patterns that depend upon context and are often ...
In order to better understand whether heuristics can comprise a normative decision theory I first... more In order to better understand whether heuristics can comprise a normative decision theory I first explore some common support for heuristics and comment against their importance for the normative questions. Then I examine the role that any normative theory must fill and how we can evaluate and compare them. I conclude (tentatively) that normativity rests on the actions rather than the technique and hence we need some higher-level theory to tell us which sets of actions have greater normative force. Nevertheless there are some identifiable benefits of a heuristic normative theory that lend strong credibility to its superiority as a general decision mechanism and more usefully employed for normative tasks. I finish up by addressing points that are off the main normativity questions but nonetheless often addressed in relation to this topic. Though this paper falls far short of establishing the superiority (or inferiority) of heuristics as a normative decision theory, it does touch upon...
Abstract Empirical evidence demonstrates that cultures exist, they differ from one another, they&... more Abstract Empirical evidence demonstrates that cultures exist, they differ from one another, they're coherent and yet diversity persists within them. In this paper, we describe a multi-dimensional model of cultural formation that produces all of these properties. Our model ...
Polarization is a topic of intense interest among social scientists, but there is significant dis... more Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomena and little understanding of underlying mechanics. A first problem , we argue, is that polarization appears in the literature as not one concept but many. In the first part of the paper, we distinguish nine phenomena that may be considered polarization with suggestions of appropriate measures for each. In the second part of the paper, we apply this analysis to evaluate the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization.
Identifying key agents for the transmission of diseases (ideas, technology, etc.) across social n... more Identifying key agents for the transmission of diseases (ideas, technology, etc.) across social networks has predominantly relied on measures of centrality on a static base network or a temporally flattened graph of agent interactions. Various measures have been proposed as the best trackers of influence, such as degree centrality, betweenness, and k-shell, depending on the structure of the connectivity. We consider SIR and SIS propagation dynamics on a temporally-extruded network of observed interactions and measure the conditional marginal spread as the change in the magnitude of the infection given the removal of each agent at each time: its temporal knockout (TKO) score. We argue that this TKO score is an effective benchmark measure for evaluating the accuracy of other, often more practical, measures of influence. We find that none of the network measures applied to the induced flat graphs are accurate predictors of network propagation influence on the systems studied; however, temporal networks and the TKO measure provide the requisite targets for the search for effective predictive measures.
This paper draws distinctions among various concepts related to tipping points, robustness, path ... more This paper draws distinctions among various concepts related to tipping points, robustness, path dependence, and other properties of system dynamics. For each concept a formal definition is provided that utilizes Markov model representations of systems. We start with the basic features of Markov models and definitions of the foundational concepts of system dynamics. Then various tipping point-related concepts are described, defined, and illustrated with a simplified graphical example in the form of a stylized state transition diagram. The tipping point definitions are then used as a springboard to describe, formally define, and illustrate many distinct concepts collectively referred to as "robustness". The final definitional section explores concepts of path sensitivity and how they can be revealed in Markov models. The definitions provided are presented using probability theory; in addition, each measure has an associated algorithm using matrix operations (excluded from current draft). Finally an extensive future work section indicates many directions this research can branch into and which methodological, conceptual, and practical benefits can be realized through this suite of techniques.
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2004, 2004
This paper presents a generalized methodology for propagating known or estimated levels of indivi... more This paper presents a generalized methodology for propagating known or estimated levels of individual source document truth reliability to determine the confidence level of a combined output. Initial document certainty levels are augmented by (i) combining the reliability measures of multiply sources, (ii) incorporating the truth reinforcement of related elements, and (iii) incorporating the importance of the individual elements for
2009 IEEE Toronto International Conference Science and Technology for Humanity (TIC-STH), 2009
... Aaron L Bramson Center for the Study of Complex Systems University of Michigan 321A West Hall... more ... Aaron L Bramson Center for the Study of Complex Systems University of Michigan 321A West Hall 1085 S. University Ave. ... Jenna Bednar & Scott Page claim, “Culture can be defined as individual and community level behavioral patterns that depend upon context and are often ...
In order to better understand whether heuristics can comprise a normative decision theory I first... more In order to better understand whether heuristics can comprise a normative decision theory I first explore some common support for heuristics and comment against their importance for the normative questions. Then I examine the role that any normative theory must fill and how we can evaluate and compare them. I conclude (tentatively) that normativity rests on the actions rather than the technique and hence we need some higher-level theory to tell us which sets of actions have greater normative force. Nevertheless there are some identifiable benefits of a heuristic normative theory that lend strong credibility to its superiority as a general decision mechanism and more usefully employed for normative tasks. I finish up by addressing points that are off the main normativity questions but nonetheless often addressed in relation to this topic. Though this paper falls far short of establishing the superiority (or inferiority) of heuristics as a normative decision theory, it does touch upon...
Abstract Empirical evidence demonstrates that cultures exist, they differ from one another, they&... more Abstract Empirical evidence demonstrates that cultures exist, they differ from one another, they're coherent and yet diversity persists within them. In this paper, we describe a multi-dimensional model of cultural formation that produces all of these properties. Our model ...
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Philosophy of Science by Aaron Bramson
Papers by Aaron Bramson