There are well-understood psychological limits on our capacity to process information. As information proliferation—the consumption and sharing of information—increases through social media and other ...communications technology, these limits create an attentional bottleneck, favoring information that is more likely to be searched for, attended to, comprehended, encoded, and later reproduced. In information-rich environments, this bottleneck influences the evolution of information via four forces of cognitive selection, selecting for information that is belief-consistent, negative, social, and predictive. Selection for belief-consistent information leads balanced information to support increasingly polarized views. Selection for negative information amplifies information about downside risks and crowds out potential benefits. Selection for social information drives herding, impairs objective assessments, and reduces exploration for solutions to hard problems. Selection for predictive patterns drives overfitting, the replication crisis, and risk seeking. This article summarizes the negative implications of these forces of cognitive selection and presents eight warnings that represent severe pitfalls for the naive “informavore,” accelerating extremism, hysteria, herding, and the proliferation of misinformation.
Although explicit verbal expression of prejudice and stereotypes may have become less common due to the recent rise of social norms against prejudice, prejudice in language still persists in more ...subtle forms. It remains unclear whether and how language patterns predict variance in prejudice across a large number of minority groups. Informed by construal level theory, intergroup-contact theory, and linguistic expectancy bias, we leverage a natural language corpus of 1.8 million newspaper articles to investigate patterns of language referencing 60 U.S. minority groups. We found that perception of social distance among immigrant groups is reflected in language production: Groups perceived as socially distant (vs. close) are also more likely to be mentioned in abstract (vs. concrete) language. Concreteness was also strongly positively correlated with sentiment, a phenomenon that was unique to language concerning minority groups, suggesting a strong tendency for more socially distant groups to be represented with more negative language. We also provide a qualitative exploration of the content of outgroup prejudice by applying Latent Dirichlet Allocation to language referencing minority groups in the context of immigration. We identified 15 immigrant-related topics (e.g., politics, arts, crime, illegal workers, museums, food) and the strength of their association and relationship with perceived sentiment for each minority group. This research demonstrates how perceived social distance and language concreteness are related and correlate with outgroup negativity, provides a practical and ecologically valid method for investigating perceptions of minority groups in language, and helps elaborate the connection between theoretical positions from social psychology with recent studies from computer science on prejudice embedded in natural language.
Industrial processes account for one-third of global energy demand. The iron and steel, cement and refining sectors are particularly energy-intensive, together making up over 30% of total industrial ...energy consumption and producing millions of tonnes of CO2 per year. The aim of this paper is to provide a comprehensive overview of the technologies for reducing emissions from industrial processes by collating information from a wide range of sources. The paper begins with a summary of energy consumption and emissions in the industrial sector. This is followed by a detailed description of process improvements in the three sectors mentioned above, as well as cross-cutting technologies that are relevant to many industries. Lastly, a discussion of the effectiveness of government policies to facilitate the adoption of those technologies is presented. Whilst there has been significant improvement in energy efficiency in recent years, cost-effective energy efficient options still remain. Key energy efficiency measures include upgrading process units to Best Practice, installing new electrical equipment such as pumps and even replacing the process completely. However, these are insufficient to achieve the deep carbon reductions required if we are to avoid dangerous climate change. The paper concludes with recommendations for action to achieve further decarbonisation.
Highlights • The exploration–exploitation trade-off is a ubiquitous problem across domains. • Common search strategies and formal solutions scale from individuals to societies. • Internal and ...external search rely on shared neurocognitive mechanisms. • Search represents a key evolutionary force in the development of cognition.
Bias in Zipf’s law estimators Pilgrim, Charlie; Hills, Thomas T
Scientific reports,
08/2021, Letnik:
11, Številka:
1
Journal Article
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The prevailing maximum likelihood estimators for inferring power law models from rank-frequency data are biased. The source of this bias is an inappropriate likelihood function. The correct ...likelihood function is derived and shown to be computationally intractable. A more computationally efficient method of approximate Bayesian computation (ABC) is explored. This method is shown to have less bias for data generated from idealised rank-frequency Zipfian distributions. However, the existing estimators and the ABC estimator described here assume that words are drawn from a simple probability distribution, while language is a much more complex process. We show that this false assumption leads to continued biases when applying any of these methods to natural language to estimate Zipf exponents. We recommend that researchers be aware of the bias when investigating power laws in rank-frequency data.
Cognitive science invokes semantic networks to explain diverse phenomena, from memory retrieval to creativity. Research in these areas often assumes a single underlying semantic network that is ...shared across individuals. Yet, recent evidence suggests that content, size, and connectivity of semantic networks are experience-dependent, implying sizable individual and age-related differences. Here, we investigate individual and age differences in the semantic networks of younger and older adults by deriving semantic networks from both fluency and similarity rating tasks. Crucially, we use a megastudy approach to obtain thousands of similarity ratings per individual to allow us to capture the characteristics of individual semantic networks. We find that older adults possess lexical networks with smaller average degree and longer path lengths relative to those of younger adults, with older adults showing less interindividual agreement and thus more unique lexical representations relative to younger adults. Furthermore, this approach shows that individual and age differences are not evenly distributed but, rather, are related to weakly connected, peripheral parts of the networks. All in all, these results reveal the interindividual differences in both the content and the structure of semantic networks that may accumulate across the life span as a function of idiosyncratic experiences.
A considerable amount of research has claimed that animals' foraging behaviors display movement lengths with power-law distributed tails, characteristic of Lévy flights and Lévy walks. Though these ...claims have recently come into question, the proposal that many animals forage using Lévy processes nonetheless remains. A Lévy process does not consider when or where resources are encountered, and samples movement lengths independently of past experience. However, Lévy processes too have come into question based on the observation that in patchy resource environments resource-sensitive foraging strategies, like area-restricted search, perform better than Lévy flights yet can still generate heavy-tailed distributions of movement lengths. To investigate these questions further, we tracked humans as they searched for hidden resources in an open-field virtual environment, with either patchy or dispersed resource distributions. Supporting previous research, for both conditions logarithmic binning methods were consistent with Lévy flights and rank-frequency methods-comparing alternative distributions using maximum likelihood methods-showed the strongest support for bounded power-law distributions (truncated Lévy flights). However, goodness-of-fit tests found that even bounded power-law distributions only accurately characterized movement behavior for 4 (out of 32) participants. Moreover, paths in the patchy environment (but not the dispersed environment) showed a transition to intensive search following resource encounters, characteristic of area-restricted search. Transferring paths between environments revealed that paths generated in the patchy environment were adapted to that environment. Our results suggest that though power-law distributions do not accurately reflect human search, Lévy processes may still describe movement in dispersed environments, but not in patchy environments-where search was area-restricted. Furthermore, our results indicate that search strategies cannot be inferred without knowing how organisms respond to resources-as both patched and dispersed conditions led to similar Lévy-like movement distributions.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Story retelling is a fundamental medium for the transmission of information between individuals and among social groups. Besides conveying factual information, stories also contain affective ...information. Though natural language processing techniques have advanced considerably in recent years, the extent to which machines can be trained to identify and track emotions across retellings is unknown. This study leverages the powerful RoBERTa model, based on a transformer architecture, to derive emotion-rich story embeddings from a unique dataset of 25,728 story retellings. The initial stories were centered around five emotional events (joy, sadness, embarrassment, risk, and disgust-though the stories did not contain these emotion words) and three intensities (high, medium, and low). Our results indicate (1) that RoBERTa can identify emotions in stories it was not trained on, (2) that the five emotions and their intensities are preserved when they are transmitted in the form of retellings, (3) that the emotions in stories are increasingly well-preserved as they experience additional retellings, and (4) that among the five emotions, risk and disgust are least well-preserved, compared with joy, sadness, and embarrassment. This work is a first step toward quantifying situation-driven emotions with machines.
Foraging‐ and feeding‐related behaviors across eumetazoans share similar molecular mechanisms, suggesting the early evolution of an optimal foraging behavior called area‐restricted search (ARS), ...involving mechanisms of dopamine and glutamate in the modulation of behavioral focus. Similar mechanisms in the vertebrate basal ganglia control motor behavior and cognition and reveal an evolutionary progression toward increasing internal connections between prefrontal cortex and striatum in moving from amphibian to primate. The basal ganglia in higher vertebrates show the ability to transfer dopaminergic activity from unconditioned stimuli to conditioned stimuli. The evolutionary role of dopamine in the modulation of goal‐directed behavior and cognition is further supported by pathologies of human goal‐directed cognition, which have motor and cognitive dysfunction and organize themselves, with respect to dopaminergic activity, along the gradient described by ARS, from perseverative to unfocused. The evidence strongly supports the evolution of goal‐directed cognition out of mechanisms initially in control of spatial foraging but, through increasing cortical connections, eventually used to forage for information.
Previous studies demonstrated that statistical properties of adult generated free associates predict the order of early noun learning. We investigate an explanation for this phenomenon that we call ...the associative structure of language: early word learning may be driven in part by contextual diversity in the learning environment, with contextual diversity in caregiver speech correlating with the cue–target structure in adult free association norms. To test this, we examined the co-occurrence of words in caregiver speech from the CHILDES database and found that a word’s contextual diversity—the number of unique word types a word co-occurs with in caregiver speech—predicted the order of early word learning and was highly correlated with the number of unique associative cues for a given target word in adult free association norms. The associative structure of language was further supported by an analysis of the longitudinal development of early semantic networks (from 16 to 30
months) using contextual co-occurrence. This analysis supported two growth processes: The lure of the associates, in which the earliest learned words have more connections with known words, and preferential acquisition, in which the earliest learned words are the most contextually diverse in the learning environment. We further discuss the impact of word class (nouns, verbs, etc.) on these results.
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