Shaw, L. 2015. Mechanics and dynamics of social construction: Modeling the emergence of culture from individual mental representation. Poetics. 52:75-90

Katherine Stovel and Lynette Shaw. 2012. Brokerage. Annual Review of Sociology. 38:7.1-7.20


Manuscripts in Preparation 

Shaw, L. What is bitcoin?: Adoption, co-option, and the robust object of digital currency. (In progress).


In less than a decade, Bitcoin has gone from being the obscure monetary experiment of a small group of “techno-Libertarians” to becoming the basis of a new multi-billion dollar financial technology industry – an industry dominated by the very same institutions and actors the digital currency was initially intended to subvert. Alongside this rise, the persistent question of what Bitcoin actually is has accompanied it. The goal of this work will be to demonstrate how this definitional ambiguity has enabled Bitcoin’s success while also simultaneously laying the groundwork for its co-option by the powerful actors it was originally meant to challenge. Using an array of evidence and analytical approaches, including the documented history of Bitcoin’s evolution, the application of automated content analysis and topic modeling methods to thousands of news reporting articles that have appeared on it, and consideration of trends in quantitative metrics reflecting Bitcoin related searches, venture capital funding, and price and market activity, this work will show how Bitcoin’s multivalent identity initially facilitated its adoption by a multiplicity of groups, but also, ultimately left it vulnerable to being preferentially defined in ways that best benefitted powerful actors in the existing structure. By charting the rise of Bitcoin and linking it to the collective definitional processes that have surrounded it, this work will seek to not only contribute to existing literatures on social constructions of money and value, but also, point the way to developing a broader understanding of the social dynamics that surround such “robust objects” and the role they play in enabling the reproduction of existing power structures in new fields and arenas of social life.


Shaw, L. A Bitcoin’s worth: Talks of money and value at the advent of digital currency. (In progress).


In the wake of the Great Recession, a monetary object born of a novel combination of cryptography, computation, and anti-centralization politics was introduced to the world: Bitcoin. Since its inception, the valuation of Bitcoin and the other digital currencies that followed it has risen in a meteoric, and often extremely volatile, fashion. With this rise has also come a sustained disruption to some of the most deeply taken-for-granted concepts in modern life, money and value. Using text gathered from 100,000s of messages posted by individuals in the main communities surrounding Bitcoin, this work uses a combination of automated and traditional content analysis to explore the “talks” (Swidler 2001) of money and value that individuals have employed to deal with this upheaval. The resulting analysis traces the manner in which the initial metallist views that first inspired the creation of this form of “digital gold” (Popper 2015a) continues to heavily influence these discourses and the way in which members have had to go beyond those founding ideas in order to make sense of the novel monetary project they have undertaken. In exploring these variegated, sometimes contradictory, discussions of the economic, political, and social origins of money and value, this analysis will seek to shed light on the ways the individuals at the advent of digital currency are making sense of this new arena of economic activity and how they might be creatively reworking established notions of money and value to explain what Bitcoin is and where its worth comes from.


Shaw, L. Something out of nothing: a computational model for social valuation processes. (In progress).


The recent rise of digital currencies such as Bitcoin has brought in its wake any number of both industrial and conceptual disruptions. One of the most prominent challenges it has posed has been to prevailing models of the origins of money and explanations of how money acquires and holds value. Absent a backing such as gold convertibility or the state, the question of how digital currencies have attained significant real world value remains a major puzzle to standard economic thinking. This work uses a series of agent-based models (ABM) based on Bayesian updating agents to explore how sociological models of value construction may be able to help “solve” this theoretical problem. Specifically, it demonstrates how a reconceptualization of valuation as a process of learning under uncertainty can faithfully unite economic and sociological models of value in a way that easily accounts for how “something” can legitimately come from “nothing” in social valuation processes. Having established this foundation, this work then goes further to more deeply explore the differences between social versus non-social valuation processes, the high dependency of social valuation processes on time, initial states, and the actions of early actors, and the massive delays that a mix of non-social and social feedbacks can lead to in a system’s ability to arrive at the “correct” assessment of an object’s underlying value. This work then shows how these theoretical results provide for a more rigorously developed basis for arguments which assert that social processes provide for a legitimate and stable source of value and that the inclusion of social components in valuation processes requires us to modify our current expectations and assumptions about how real-world markets operate.



Shaw, L. Revelation as revolution: Conscious availability and the stability (and instability) of social orders. (In progress).


This paper defines a connection between the cognitive mechanisms which govern the transition between unconscious and conscious processing in individuals and the stability and instability of social orders. By building on prior modeling work that systematically demonstrated how shared social realities can emerge from individual mental representation processes, the present work is able to identify the key role of representational confirmation/disconfirmation in the establishment and disruption of the taken-for-grantedness of social life. Having identified this critical mechanism, then extends its implications another step further to begin outlining scenarios which are likely to engender an enhanced capacity for dramatic social change. This paper then concludes by briefly exploring the concept of “revelatory practices” as collective endeavors which intentionally pursue the disconfirmation of prevailing social representations and thereby instigate destabilizations of otherwise stabilized taken-for-granteds.


Shaw, L., Cesare, N., and Esposito, M. From meaning to behavior: Mental representation, the structuring of social life, and cultural analysis. (In progress).


This paper looks at the relationship between mental representation processes and the emergence of profiles of human action and statement that are detectable via methods currently favored “big data” analyses. In particular, this paper begins with the role of mental networks of association in shaping not only humans’ sense-making in situations but also in generating their repertories of observable behaviors. After delimiting the basic mechanics of this process, this work then considers the implications of it for classic sociological issues of polysemy, socially shared (i.e. collective) vs. idiosyncratic representations, and representational/cultural change. The paper then uses the examples of cluster analysis, multiple correspondence and principle component analysis, and topic modeling to consider how this link between behavior and mental representations can systematically increase the analytical leverage of our existing approaches to the empirical study of culture. In the final section, the paper then offers a demonstration of how this perspective can be used to motivate and guide a “data mining for culture” approach via the example of using Yelp reviews to identify shared patterns of consumption and speech in large-scale social data.