What makes organizations so similar? We contend that the engine of rationalization and bureaucratization has moved from the competitive marketplace to the state and the professions. Once a set of organizations emerges as a field, a paradox arises: rational actors make their organizations increasingly similar as they try to change them. We describe three isomorphic processes-coercive, mimetic, and normative—leading to this outcome. We then specify hypotheses about the impact of resource centralization and dependency, goal ambiguity and technical uncertainty, and professionalization and structuration on isomorphic change. Finally, we suggest implications for theories of organizations and social change.

The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields (Chinese Translation)

Quasi-experimentation - design and analysis issues for field settings - cook,td, campbell,dt

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The Uses Of Argument

https://dialnet.unirioja.es/descarga/articulo/4511387.pdf

The origins of order. Self-organization and selection in evolution

Objective knowledge: an evolutionary approach

Research suggests that fact checking corrections have only a limited impact on the spread of false rumors. However, research has not considered that fact-checking may be socially contingent, meaning there are social contexts in which truth may be more or less preferred. In particular, we argue that strong social connections between fact-checkers and rumor spreaders encourage the latter to prefer sharing accurate information, making them more likely to accept corrections. We test this argument on real corrections made on Twitter between Janurary 2012 and April, 2014. As hypothesized, we find that individuals who follow and are followed by the people who correct them are significantly more likely to accept the correction than individuals confronted by strangers. We then replicate our findings on new data drawn from November 2015 to February, 2016. These findings suggest that the underlying social structure is an important factor in the correction of misinformation.

Political Fact-Checking on Twitter: When Do Corrections Have an Effect?

“Media events” generate conditions of shared attention as many users simultaneously tune in with the dual screens of broadcast and social media to view and participate. We examine how collective patterns of user behavior under conditions of shared attention are distinct from other “bursts” of activity like breaking news events. Using 290 million tweets from a panel of 193,532 politically active Twitter users, we compare features of their behavior during eight major events during the 2012 U.S. presidential election to examine how patterns of social media use change during these media events compared to “typical” time and whether these changes are attributable to shifts in the behavior of the population as a whole or shifts from particular segments such as elites. Compared to baseline time periods, our findings reveal that media events not only generate large volumes of tweets, but they are also associated with (1) substantial declines in interpersonal communication, (2) more highly concentrated attention by replying to and retweeting particular users, and (3) elite users predominantly benefiting from this attention. These findings empirically demonstrate how bursts of activity on Twitter during media events significantly alter underlying social processes of interpersonal communication and social interaction. Because the behavior of large populations within socio-technical systems can change so dramatically, our findings suggest the need for further research about how social media responses to media events can be used to support collective sensemaking, to promote informed deliberation, and to remain resilient in the face of misinformation.

/pdf/rising-tides-or-rising-stars-dynamics-of-shared-attention-on-2mllbcjg8a.pdf

Rising tides or rising stars?: Dynamics of shared attention on Twitter during media events.

Organizational communities are typically defined as populations of organizations that are tied together by networks of communication and other relations in overlapping resource niches. Traditionally, evolutionary theorists and researchers have examined organizational populations that comprise organizational communities by focusing on their properties rather than on the networks that link them. However, a full understanding of the evolution of organizational communities requires insight into both organizations and their networks. Consequently, this article presents a variety of conceptual tools for applying evolutionary theory to organizations, organizational communities, and their networks, including the notions of relational carrying capacity and linkage fitness. It illustrates evolutionary principles, such as variation, selection, and retention, that lead to the formation, growth, maintenance, and eventual demise of communication and other network linkages. This perspective allows us to understand the ways in which community survival and success are as dependent on their communication linkages as they are on the organizations they connect. The article concludes with suggestions for potential applications of evolutionary theory to other areas of human communication.

Communication Network Evolution in Organizational Communities

The prevalence of misinformation within social media and online communities can undermine public security and distract attention from important issues. Fact-checking interventions, in which users cite fact-checking websites such as Snopes.com and FactCheck.org, are a strategy users can employ to refute false claims made by their peers. While laboratory research suggests such interventions are not effective in persuading people to abandon false ideas, little work considers how such interventions are actually deployed in real-world conversations. Using approximately 1,600 interventions observed on Twitter between 2012 and 2013, we examine the contexts and consequences of fact-checking interventions.W e focus in particular on the social relationship between the individual who issues the fact-check and the individual whose facts are challenged. Our results indicate that though fact-checking interventions are most commonly issued by strangers, they are more likely to draw user attention and responses when they come from friends. Finally, we discuss implications for designing more effective interventions against misinformation.

/pdf/get-back-you-don-t-know-me-like-that-the-social-mediation-of-33q14cl3uk.pdf

Get Back! You Don’t Know Me Like That: The Social Mediation of Fact Checking Interventions in Twitter Conversations

We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential debates. Our analysis reveals the trajectories of hashtag use fall into two distinct classes: "winners" that emerge more quickly and are sustained for longer periods of time than other "also-rans" hashtags. We propose a "conversational vibrancy" framework to capture dynamics of hashtags based on their topicality, interactivity, diversity, and prominence. Statistical analyses of the growth and persistence of hashtags reveal novel relationships between features of this framework and the relative success of hashtags. Specifically, retweets always contribute to faster hashtag adoption, replies extend the life of "winners" while having no effect on "also-rans." This is the first study on the lifecycle of hashtag adoption and use in response to purely exogenous shocks. We draw on theories of uses and gratification, organizational ecology, and language evolution to discuss these findings and their implications for understanding social influence and collective action in social media more generally.

Drew Margolin

Papers

Political Fact-Checking on Twitter: When Do Corrections Have an Effect?

Rising tides or rising stars?: Dynamics of shared attention on Twitter during media events.

Communication Network Evolution in Organizational Communities

Get Back! You Don’t Know Me Like That: The Social Mediation of Fact Checking Interventions in Twitter Conversations

#Bigbirds Never Die: Understanding Social Dynamics of Emergent Hashtag