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Background Seldom in history does one get a ‘front row seat’—with large-scale dynamic data—on how online news media narratives shift with a global pandemic. News media narratives matter because they shape societal perceptions and influence the core tent poles of our society, from the economy to elections. Given its importance—and with the benefit of hindsight—we provide a systematic framework to analyze news narratives of Covid-19, laying the groundwork to evaluate policy and risk communications. Objectives We leverage a 10-billion-word-database of online news, taken from over 7,000 English newspapers and magazines across 20 countries, culminating in 28 million articles. First, we track the volume of Covid-19 conversations across 20 countries from before to during the pandemic (Oct’19 to May’20). Second, we distill the phases of global pandemic narratives, and elucidate regional differences. Methods To track the volume of Covid-19 narratives, we identified 10 target terms—Coronavirus, Covid-19, Covid, nCoV, SARS-CoV-2, Wuhan Virus, Virus, Disease, Epidemic, Pandemic—and tracked their combined monthly prevalence across eight months from October 2019 through May 2020. Globally, across 20 countries, we identified 18,042,855 descriptors of the target terms. Further, these descriptors were analysed with natural language processing models to generate the top five topics of Covid-19 that were labelled by two independent researchers. This process was repeated across six continents to distil regional topics. Results Our model found four phases of online news media narratives: Pre-pandemic, Early, Peak and Recovery. Pre-pandemic narratives (Oct’19–Dec’19) were divergent across regions with Africa focused on monkeypox, Asia on dengue fever, and North America on Lyme disease and AIDS. Early (Jan–Feb’20) and Peak Pandemic (Mar–May’20) evidenced a global convergence, reflecting the omnipresence of Covid-19. The brief transition from early to peak pandemic narratives underscored the pandemic’s rapid spread. Emerging from the embers of the pandemic’s peak were nascent recovery words that are regionally divergent—Oceania focused on hope and an uncertain future while North America centered on re-opening the economy and tackling discrimination. Conclusions Practically, we presented a media barometer of Covid-19, and provided a framework to analyse the pandemic’s impact on societal perceptions—laying the important groundwork for policy makers to evaluate policy communications, and design risk communication strategies.

This article applies scientometric techniques to study the evolution of the field of entrepreneurship between 1990 and 2013. Using a combination of topic mapping, author and journal co-citation analyses, and overlay visualization of new and hot topics in the field, this article makes important contribution to the entrepreneurship research by identifying 46 topics in the 24-year history of entrepreneurship research and demonstrates how they appear, disappear, reappear and stabilize over time. It also identifies five topics that are persistent across the 24-year study period--institutions and institutional entrepreneurship, innovation and technology management, policy and development, entrepreneurial process and opportunity, and new ventures--which I labeled as The Pentagon of Entrepreneurship. Overall, the analyses revealed patterns of convergence and divergence and the diversity of topics, specialization, and interdisciplinary engagement in entrepreneurship research, thus offering the latest insights on the state of the art of the field.

There is increasing evidence that science & engineering PhD students lose interest in an academic career over the course of graduate training. It is not clear, however, whether this decline reflects students being discouraged from pursuing an academic career by the challenges of obtaining a faculty job or whether it reflects more fundamental changes in students’ career goals for reasons other than the academic labor market. We examine this question using a longitudinal survey that follows a cohort of PhD students from 39 U.S. research universities over the course of graduate training to document changes in career preferences and to explore potential drivers of such changes. We report two main results. First, although the vast majority of students start the PhD interested in an academic research career, over time 55% of all students remain interested while 25% lose interest entirely. In addition, 15% of all students were never interested in an academic career during their PhD program, while 5% become more interested. Thus, the declining interest in an academic career is not a general phenomenon across all PhD students, but rather reflects a divergence between those students who remain highly interested in an academic career and other students who are no longer interested in one. Second, we show that the decline we observe is not driven by expectations of academic job availability, nor by related factors such as postdoctoral requirements or the availability of research funding. Instead, the decline appears partly due to the misalignment between students’ changing preferences for specific job attributes on the one hand, and the nature of the academic research career itself on the other. Changes in students’ perceptions of their own research ability also play a role, while publications do not. We discuss implications for scientific labor markets, PhD career development programs, and science policy.

Anecdotes abound regarding the decline of basic research in industrial and governmental settings, but very little empirical evidence exists about the phenomenon. This article provides a systematic and historical analysis of the contribution of various institutional sectors to knowledge production at the world and country levels across the past four decades. It highlights a dramatic decline in the diffusion of basic research by industrial and governmental sectors across all countries—with a corresponding increase in the share from universities—as well as an increase of partnerships between universities and other sectors. Results also shows an increase in the relative share of industries in applied research, as measured through patents. Such divergence in university and industry research activities may hinder industries’ ability to translate basic knowledge into technological innovation, and could lead to a growing misalignment between doctoral training and future job expectations. Industries and universities must rethink strategies for partnerships and publishing to maximize scientific progress and to ensure the greatest gains for society.

In this paper we analyse the word frequency profiles of a set of works from the Shakespearean era to uncover patterns of relationship between them, highlighting the connections within authorial canons. We used a text corpus comprising 256 plays and poems from the 16th and 17th centuries, with 17 works of uncertain authorship. Our clustering approach is based on the Jensen-Shannon divergence and a graph partitioning algorithm, and our results show that authors' characteristic styles are very powerful factors in explaining the variation of word use, frequently transcending cross-cutting factors like the differences between tragedy and comedy, early and late works, and plays and poems. Our method also provides an empirical guide to the authorship of plays and poems where this is unknown or disputed.

International audience; The epidemiological transition has provided the theoretical background for the expectation of convergence in mortality patterns. We formally test and reject the convergence hypothesis for a sample of industrialized countries in the period from 1960 to 2008. After a period of convergence in the decade of 1960 there followed a sustained process of divergence with a pronounced increase at the end of the 1980's, explained by trends within former Socialist countries (Eastern countries). While Eastern countries experienced abrupt divergence after the dissolution of the Soviet Union, differences within Western countries remained broadly constant for the whole period. Western countries transitioned from a strong correlation between life expectancy and variance in 1960 to no association between both moments in 2008 while Eastern countries experienced the opposite evolution. Taken together, our results suggest that convergence can be better understood when accounting for shared structural similarities amongst groups of countries rather than through global convergence.

While interdisciplinarity continues to increase in popularity among funders and other scientific organizations, its potential to promote scientific advances remains under-examined. For HIV/AIDS research, we examine the dynamics of disciplinary integration (or lack thereof) providing insight into a field's knowledge base and those questions that remain unresolved. Drawing on the complete histories of two interdisciplinary journals, we construct bibliographic coupling networks based on overlapping citations to identify segregation into research clusters and estimate topic models of research content. We then compare how readily those bibliographic coupling clusters account for the structuring of topics covered within the field as it evolves over two decades. These comparisons challenge one-dimensional and/or cross-sectional approaches to interdisciplinarity. Some topics are increasingly coordinated across disciplinary boundaries (e.g., vaccine development); others remain relatively segmented into disconnected disciplinary domains for the full period (e.g., drug resistance). This divergence indicates heterogeneity in interdisciplinarity and emphasizes the need for critical approaches to studying the organization of science.

Online social media are increasingly facilitating our social interactions, thereby making available a massive "digital fossil" of human behavior. Discovering and quantifying distinct patterns using these data is important for studying social behavior, although the rapid time-variant nature and large volumes of these data make this task difficult and challenging. In this study, we focused on the emergence of "collective attention" on Twitter, a popular social networking service. We propose a simple method for detecting and measuring the collective attention evoked by various types of events. This method exploits the fact that tweeting activity exhibits a burst-like increase and an irregular oscillation when a particular real-world event occurs; otherwise, it follows regular circadian rhythms. The difference between regular and irregular states in the tweet stream was measured using the Jensen-Shannon divergence, which corresponds to the intensity of collective attention. We then associated irregular incidents with their corresponding events that attracted the attention and elicited responses from large numbers of people, based on the popularity and the enhancement of key terms in posted messages or "tweets." Next, we demonstrate the effectiveness of this method using a large dataset that contained approximately 490 million Japanese tweets by over 400,000 users, in which we identified 60 cases of collective attentions, including one related to the Tohoku-oki earthquake. "Retweet" networks were also investigated to understand collective attention in terms of social interactions. This simple method provides a retrospective summary of collective attention, thereby contributing to the fundamental understanding of social behavior in the digital era. Language: en

We report here trends in the usage of "mood" words, that is, words carrying emotional content, in 20th century English language books, using the data set provided by Google that includes word frequencies in roughly 4% of all books published up to the year 2008. We find evidence for distinct historical periods of positive and negative moods, underlain by a general decrease in the use of emotion-related words through time. Finally, we show that, in books, American English has become decidedly more "emotional" than British English in the last half-century, as a part of a more general increase of the stylistic divergence between the two variants of English language. © 2013 Acerbi et al. Leverhulme Trust "Tipping Points" program; "Uniquely Human" project funded by the Swedish Research Council; Newton International Fellowship; TrendMiner project (EU-FP7-ICT n.287863)

Understanding the influence of the built environment on human movement requires quantifying spatial structure in a general sense. Because of the difficulty of this task, studies of movement dynamics often ignore spatial heterogeneity and treat movement through journey lengths or distances alone. This study analyses public bicycle data from central London to reveal that, although journey distances, directions, and frequencies of occurrence are spatially variable, their relative spatial patterns remain largely constant, suggesting the influence of a fixed spatial template. A method is presented to describe this underlying space in terms of the relative orientation of movements toward, away from, and around locations of geographical or cultural significance. This produces two fields: one of convergence and one of divergence, which are able to accurately reconstruct the observed spatial variations in movement. These two fields also reveal categorical distinctions between shorter journeys merely serving diffusion away from significant locations, and longer journeys intentionally serving transport between spatially distinct centres of collective importance. Collective patterns of human movement are thus revealed to arise from a combination of both diffusive and directed movement, with aggregate statistics such as mean travel distances primarily determined by relative numbers of these two kinds of journeys. Language: en

We recently used computational phylogenetic methods on lexical data to test between two scenarios for the peopling of the Pacific. Our analyses of lexical data supported a pulse-pause scenario of Pacific settlement in which the Austronesian speakers originated in Taiwan around 5,200 years ago and rapidly spread through the Pacific in a series of expansion pulses and settlement pauses. We claimed that there was high congruence between traditional language subgroups and those observed in the language phylogenies, and that the estimated age of the Austronesian expansion at 5,200 years ago was consistent with the archaeological evidence. However, the congruence between the language phylogenies and the evidence from historical linguistics was not quantitatively assessed using tree comparison metrics. The robustness of the divergence time estimates to different calibration points was also not investigated exhaustively. Here we address these limitations by using a systematic tree comparison metric to calculate the similarity between the Bayesian phylogenetic trees and the subgroups proposed by historical linguistics, and by re-estimating the age of the Austronesian expansion using only the most robust calibrations. The results show that the Austronesian language phylogenies are highly congruent with the traditional subgroupings, and the date estimates are robust even when calculated using a restricted set of historical calibrations.

One of the best known claims about human communication is that people's behaviour and language use converge during conversation. It has been proposed that these patterns can be explained by automatic, cross-person priming. A key test case is structural priming: does exposure to one syntactic structure, in production or comprehension, make reuse of that structure (by the same or another speaker) more likely? It has been claimed that syntactic repetition caused by structural priming is ubiquitous in conversation. However, previous work has not tested for general syntactic repetition effects in ordinary conversation independently of lexical repetition. Here we analyse patterns of syntactic repetition in two large corpora of unscripted everyday conversations. Our results show that when lexical repetition is taken into account there is no general tendency for people to repeat their own syntactic constructions. More importantly, people repeat each other's syntactic constructions less than would be expected by chance; i.e., people systematically diverge from one another in their use of syntactic constructions. We conclude that in ordinary conversation the structural priming effects described in the literature are overwhelmed by the need to actively engage with our conversational partners and respond productively to what they say.