Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances at low cost. The digital age and the rise of social media have accelerated changes to our social systems, with poorly understood functional consequences. This gap in our knowledge represents a principal challenge to scientific progress, democracy, and actions to address global crises. We argue that the study of collective behavior must rise to a “crisis discipline” just as medicine, conservation, and climate science have, with a focus on providing actionable insight to policymakers and regulators for the stewardship of social systems.

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Investigations of collective movement and animal communication have often followed distinct, though complementary, trajectories. Both subfields are deeply concerned with how information flows between individuals and shapes subsequent behaviour. Collective movement has largely focused on the dynamics of passive, cue‐mediated group coordination, while animal communication has primarily examined the content and function of active dyadic signal exchanges in sender–receiver frameworks. However, in many social groups, network‐wide signalling and collective movement decisions are tightly linked. Here we discuss opportunities afforded by using multi‐sensor tracking tags to simultaneously monitor the fine‐scale movements and vocalisations of entire social groups. We highlight how such data can elucidate the role of vocal signals in individual and collective movement while illuminating the structures of entire vocal‐interaction sequences at previously unexamined timescales and across entire communication networks. We identify practical and analytical challenges associated with these new tools and datasets, and present avenues for addressing them. We specifically address issues associated with the deployment and synchronisation of multiple tags, the processing and interpretation of resulting multidimensional datasets, and the benefits of combining tag‐based data collection with experimental approaches. Finally, we argue that a comparative approach employing consistent methodologies across a range of environments, populations and systems is needed to shed light on the evolutionary ecology of communication and collective behaviour.

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According to signaling theory and a large body of supporting evidence, males across many taxa produce courtship signals that honestly advertise their quality. The cost of producing or performing these signals maintains signal honesty, such that females are typically able to choose the best males by selecting those that produce the loudest, brightest, longest, or otherwise highest-intensity signals, using signal strength as a measure of quality. Set against this background, human flirting behavior, characterized by its frequent subtlety or covertness, is mysterious. Here we propose that the explanation for subtle and ambiguous signals in human courtship lies in socially imposed costs that (a) vary with social context and (b) are amplified by the unusual ways in which language makes all interactions potentially public. Flirting is a class of courtship signaling that conveys the signaler's intentions and desirability to the intended receiver while minimizing the costs that would accompany an overt courtship attempt. This proposal explains humans' taxonomically unusual courtship displays and generates a number of novel predictions for both humans and non-human social animals. Individuals who are courting should vary the intensity of their signals to suit the level of risk attached to the particular social configuration, and receivers may assess this flexible matching of signal to context as an indicator of the signaler's broader behavioral flexibility and social intelligence.