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How does cognitive diversity in a group affect its performance? Prior research suggests that group cognitive diversity poses a performance tradeoff: Diverse groups excel at creativity and innovation, but struggle to take coordinated action. Building on the insight that group cognition is not static, but is instead dynamically and interactively produced, we introduce the construct of discursive diversity, a manifestation of group cognitive diversity, which reflects the degree to which the meanings conveyed by group members in a given set of interactions diverge from one another. We propose that high-performing teams are ones that have a collective capacity to modulate shared cognition to match changing task requirements: They exhibit higher discursive diversity when engaged in ideational tasks and lower discursive diversity when performing coordination tasks. We further argue that teams exhibiting congruent modulation-that is, those with low group-level variance in members' within-person semantic shifts to changing task requirements-are more likely to experience success than teams characterized by incongruentmodulation. Using the tools of computational linguistics to derive a measure of discursive diversity and drawing on a novel longitudinal data set of intragroup electronic communications and performance outcomes for 117 remote software development teams on an online platform (www.gigster.com), we find support for our theory. Our findings suggest that the performance tradeoff of group cognitive diversity is not inescapable: Groups can navigate it by aligning their levels of discursive diversity to match their task requirements and by having members stay aligned with one another as theymake these adjustments.

Recent years have seen a growing sociological interest in meaning. In fact, some argue that sociology cannot confront its foundational questions without addressing meaning. Yet sociologists mean many things when they talk about meaning. We propose a practical approach that conceptualizes meaning as an instance of an actor interpreting a stimulus. Reviewing existing literature, we find that most sociological accounts understand interpretation either as categorization or as semantic association. We show that an integrated approach is analytically useful for conceptualizing shared interpretation and the process by which people coordinate their interpretations. This provides a framework for addressing interpretative heterogeneity when studying attitudinal or behavioral variance. We conclude by highlighting how recent advances in computational linguistics have opened exciting new possibilities for the study of interpretation, and suggest several avenues for future research. [ABSTRACT FROM AUTHOR]

In their insightful comment, DellaPosta and Davoodi argue that our finding (Goldberg and Stein 2018) that segmented networks inhibit cultural differentiation does not generalize to large networks. However, their demonstration rests on an incorrect implementation of the preference updating process in the associative diffusion model. We show that once this discrepancy is corrected, cultural differentiation is more pronounced in fully connected networks, irrespective of network size and even under extreme assumptions about cognitive decay. We use this as an opportunity to discuss the associative diffusion model's assumptions and scope conditions, as well as to critically reassess prevailing contagion-based diffusion models. [ABSTRACT FROM AUTHOR]

Network models of diffusion predominantly think about cultural variation as a product of social contagion. But culture does not spread like a virus. We propose an alternative explanation we call associative diffusion. Drawing on two insights from research in cognition—that meaning inheres in cognitive associations between concepts, and that perceived associations constrain people’s actions—we introduce a model in which, rather than beliefs or behaviors, the things being transmitted between individuals are perceptions about what beliefs or behaviors are compatible with one another. Conventional contagion models require the assumption that networks are segregated to explain cultural variation. We show, in contrast, that the endogenous emergence of cultural differentiation can be entirely attributable to social cognition and does not require a segregated network or a preexisting division into groups. Moreover, we show that prevailing assumptions about the effects of network topology do not hold when diffusion is associative. [ABSTRACT FROM AUTHOR]