In a recent New York Times column (April 15, 2013), David Brooks discussed how the big-data agenda lacks a coherent framework of social theory – a deficiency that the Bentley, O'Brien, and Brock (henceforth BOB) model was meant to overcome. Or, stated less pretentiously, the model was meant as a first step in that direction – a map that hopefully would serve as a minimal, practical, and accessible framework that behavioral scientists could use to analyze big data. Rather than treating big data as a record of, and also a predictor of, where and when certain behaviors might take place, the BOB model is interested in what big data reveal about how decisions are being made, how collective behavior evolves from daily to decadal time scales, and how this varies across communities.
The behavioral sciences have flourished by studying how traditional and/or rational behavior has been governed throughout most of human history by relatively well-informed individual and social learning. In the online age, however, social phenomena can occur with unprecedented scale and unpredictability, and individuals have access to social connections never before possible. Similarly, behavioral scientists now have access to "big data" sets - those from Twitter and Facebook, for example - that did not exist a few years ago. Studies of human dynamics based on these data sets are novel and exciting but, if not placed in context, can foster the misconception that mass-scale online behavior is all we need to understand, for example, how humans make decisions. To overcome that misconception, we draw on the field of discrete-choice theory to create a multiscale comparative "map" that, like a principal-components representation, captures the essence of decision making along two axes: (1) an east-west dimension that represents the degree to which an agent makes a decision independently versus one that is socially influenced, and (2) a north-south dimension that represents the degree to which there is transparency in the payoffs and risks associated with the decisions agents make. We divide the map into quadrants, each of which features a signature behavioral pattern. When taken together, the map and its signatures provide an easily understood empirical framework for evaluating how modern collective behavior may be changing in the digital age, including whether behavior is becoming more individualistic, as people seek out exactly what they want, or more social, as people become more inextricably linked, even "herdlike," in their decision making. We believe the map will lead to many new testable hypotheses concerning human behavior as well as to similar applications throughout the social sciences.
Studies of the evolution of collective behavior consider the payoffs of individual versus social learning. We have previously proposed that the relative magnitude of social versus individual learning could be compared against the transparency of payoff, also known as the "transparency" of the decision, through a heuristic, two-dimensional map. Moving from west to east, the estimated strength of social influence increases. As the decision maker proceeds from south to north, transparency of choice increases, and it becomes easier to identify the best choice itself and/or the best social role model from whom to learn (depending on position on east-west axis). Here we show how to parameterize the functions that underlie the map, how to estimate these functions, and thus how to describe estimated paths through the map. We develop estimation methods on artificial data sets and discuss real-world applications such as modeling changes in health decisions.
Vibration response imaging (VRI) is a bedside technology to monitor ventilation by detecting lung sound vibrations. It is currently unknown whether VRI is able to accurately monitor the local distribution of ventilation within the lungs. We therefore compared VRI to electrical impedance tomography (EIT), an established technique used for the assessment of regional ventilation.
For the 20(th) century since the Depression, we find a strong correlation between a 'literary misery index' derived from English language books and a moving average of the previous decade of the annual U.S. economic misery index, which is the sum of inflation and unemployment rates. We find a peak in the goodness of fit at 11 years for the moving average. The fit between the two misery indices holds when using different techniques to measure the literary misery index, and this fit is significantly better than other possible correlations with different emotion indices. To check the robustness of the results, we also analysed books written in German language and obtained very similar correlations with the German economic misery index. The results suggest that millions of books published every year average the authors' shared economic experiences over the past decade.
The lectin-like domain of TNF-? mimicked by an inhaled TIP peptide represents a novel approach to attenuate a pulmonary edema in respiratory failure, which is on the threshold to clinical application. In extension to a previously published study, which reported an improved pulmonary function following TIP peptide inhalation in a porcine model of lavage-induced lung injury, a post-hoc comparison to additional experiments was conducted. This analysis addresses the hypothesis that oleic acid injection-induced capillary leakage and alveolar necrosis blunts the previously reported beneficial effects of TIP peptide inhalation in a porcine model.
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.
In oscine songbirds, song phenotypes arise via gene-culture coevolution, in which genetically transmitted learning predispositions and culturally transmitted song forms influence one anothers evolution. To assess the outcome of this process in a population of chestnut-sided warblers (Dendroica pensylvanica), we recorded songs at intervals over a 19-year period. These recordings revealed the pattern of cultural evolution of songs in our study area, from which we inferred likely learning predispositions and mechanisms of cultural transmission. We found that the species two song categories form two distinct cultural traditions, each with its own pattern of change over time. Unaccented-ending songs have undergone continual, rapid turnover of song and element types, consistent with a model of neutral cultural evolution. Accented-ending songs, in contrast, persisted virtually unchanged for the entire study period, with extraordinarily constant song form and only one appearance of a new song type. Our results indicate that in songbirds, multiple independent cultural traditions and probably multiple independent learning predispositions can evolve concurrently, especially when different signal classes have become specialized for different communicative functions.
Effective communication strategies regarding health issues are affected by the way in which the public obtain their knowledge, particularly whether people become interested independently, or through their social networks. This is often investigated through localized ethnography or surveys. In rapidly-evolving situations, however, there may also be a need for swift, case-specific assessment as a guide to initial strategy development. With this aim, we analyze real-time online data, provided by the new Google Trends tool, concerning Internet search frequency for health-related issues. To these data we apply a simple model to characterise the effective degree of social transmission versus decisions made individually. As case examples, we explore two rapidly-evolved issues, namely the world-wide interest in avian influenza, or bird flu, in 2005, and in H1N1, or swine flu, from late April to early May 2009. The 2005 bird flu scare demonstrated almost pure imitation for two months initially, followed by a spike of independent decision that corresponded with an announcement by US president George Bush. For swine flu in 2009, imitation was the more prevalent throughout. Overall, the results show how interest in health scares can spread primarily by social means, and that engaging more independent decisions at the population scale may require a dramatic announcement to push a populace over the tipping point.
The extent to which colonizing farmer populations have overwhelmed or "replaced" indigenous forager populations, as opposed to having intermarried with them, has been widely debated. Indigenous-colonist "admixture" is often represented in genetic models as a single parameter that, although parsimonious and simple, is incongruous with the sex-specific nature of mtDNA and Y-chromosome data. To help interpret genetic patterns, we can construct useful null hypotheses about the generalized migration history of females (mtDNA) as opposed to males (Y chromosome), which differ significantly in almost every ethnographically known society. We seek to integrate ethnographic knowledge into models that incorporate new social parameters for predicting geographic patterns in mtDNA and Y-chromosome distributions. We provide an example of a model simulation for the spread of agriculture in which this individual-scale evidence is used to refine the parameters.
The explosion of interest in H1N1, more popularly called swine flu, across the world, from late April to early May 2009, exemplified how information transmission in modern online society can affect the spread of the disease itself. A simple but effective model based on cultural evolutionary theory can characterise in such data the effective degree of social transmission versus independent decision. In a novel approach that applies this model to Google Trends search data, we find significant differences in social transmission of the exact phrase swine flu in 2009, compared with bird flu in 2005. The methodology can thus inform policies for addressing public awareness of health issues, which can be more effective with knowledge of how the information is being spread or learned.
Human culture has evolved through a series of major tipping points in information storage and communication. The first was the appearance of language, which enabled communication between brains and allowed humans to specialize in what they do and to participate in complex mating games. The second was information storage outside the brain, most obviously expressed in the "Upper Paleolithic Revolution" - the sudden proliferation of cave art, personal adornment, and ritual in Europe some 35,000-45,000?years ago. More recently, this storage has taken the form of writing, mass media, and now the Internet, which is arguably overwhelming humans ability to discern relevant information. The third tipping point was the appearance of technology capable of accumulating and manipulating vast amounts of information outside humans, thus removing them as bottlenecks to a seemingly self-perpetuating process of knowledge explosion. Important components of any discussion of cultural evolutionary tipping points are tempo and mode, given that the rate of change, as well as the kind of change, in information storage and transmission has not been constant over the previous million years.
As public and political debates often demonstrate, a substantial disjoint can exist between the findings of science and the impact it has on the public. Using climate-change science as a case example, we reconsider the role of scientists in the information-dissemination process, our hypothesis being that important keywords used in climate science follow "boom and bust" fashion cycles in public usage. Representing this public usage through extraordinary new data on word frequencies in books published up to the year 2008, we show that a classic two-parameter social-diffusion model closely fits the comings and goings of many keywords over generational or longer time scales. We suggest that the fashions of word usage contributes an empirical, possibly regular, correlate to the impact of climate science on society.
Community differentiation is a fundamental topic of the social sciences, and its prehistoric origins in Europe are typically assumed to lie among the complex, densely populated societies that developed millennia after their Neolithic predecessors. Here we present the earliest, statistically significant evidence for such differentiation among the first farmers of Neolithic Europe. By using strontium isotopic data from more than 300 early Neolithic human skeletons, we find significantly less variance in geographic signatures among males than we find among females, and less variance among burials with ground stone adzes than burials without such adzes. From this, in context with other available evidence, we infer differential land use in early Neolithic central Europe within a patrilocal kinship system.
Cyclic alveolar recruitment/derecruitment (R/D) is an important mechanism of ventilator-associated lung injury. In experimental models this process can be measured with high temporal resolution by detection of respiratory-dependent oscillations of the paO2 (?paO2). A previous study showed that end-expiratory collapse can be prevented by an increased respiratory rate in saline-lavaged rabbits. The current study compares the effects of increased positive end-expiratory pressure (PEEP) versus an individually titrated respiratory rate (RRind) on intra-tidal amplitude of ? paO2 and on average paO2 in saline-lavaged pigs.
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