Philip Garnett

The Expression of Emotions in 20th Century Books

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.

Computer simulation: the imaginary friend of auxin transport biology.

Regulated transport of the plant hormone auxin is central to many aspects of plant development. Directional transport, mediated by membrane transporters, produces patterns of auxin distribution in tissues that trigger developmental processes, such as vascular patterning or leaf formation. Experimentation has produced many, largely qualitative, data providing strong evidence for multiple feedback systems between auxin and its transport. However, the exact mechanisms concerned remain elusive and the experiments required to evaluate alternative hypotheses are challenging. Because of this, computational modelling now plays an important role in auxin transport research. Here we review some current approaches and underlying assumptions of computational auxin transport models. We focus on self‐organising models for polar auxin transport and on recent attempts to unify conflicting mechanistic explanations. In addition, we discuss in general how these computer simulations are proving to be increasingly effective in hypothesis generation and testing, and how simulation can be used to direct future experiments.

Word diffusion and climate science.

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.

Social tipping points and Earth systems dynamics

Recently, Early Warning Signals (EWS) have been developed to predict tipping points in Earth Systems. This discussion highlights the potential to apply EWS to human social and economic systems, which may also undergo similar critical transitions. Social tipping points are particularly difficult to predict, however, and the current formulation of EWS, based on a physical system analogy, may be insufficient. As an alternative set of EWS for social systems, we join with other authors encouraging a focus on heterogeneity, connectivity through social networks and individual thresholds to change.

Insight from the horsemeat scandal: Exploring the consumers’ opinion of tweets toward Tesco

– Social media has become an important part of daily interpersonal communication in contemporary society. The purpose of this paper is to explore the attitudes of UK consumers by identifying the hidden information in tweets, and provide a framework which can assist industry practitioners in managing social media data. , – Using a large-scale dataset of tweets relating to the Horsemeat scandal of 2013, a comprehensive data analysis framework, which comprises multidimensional scaling and sentiment analysis, alongside other methods, was applied to explore customers’ opinions. , – Making jokes in social media was a main trend in the tweets relating to Tesco during the Horsemeat scandal. Consumer sentiments were overall negative and burgers were the most mentioned product in the week-long period after the story broke. The posting of tweets was correlated with the timing of news coverage, which indicates that the traditional media is still crucial to public opinion formation. , – This paper presents a progressive tweet-mining framework that can serve as a tool for academia and practitioners in crisis management. The proposed framework indicates the significant importance of timely categorising the topics, identifying the sentiment of tweets and understanding the changes of consumer opinions over time in a crisis. , – The research presented in this paper is one of the limited social media research to focus on a UK food fraud issue and adds to the limited body of literature investigating consumer social media use from the side of industry practitioners.

Complexity in history: modelling the organisational demography of the British banking sector

Using a new historical data set on the ‘population’ of British Banks for the last 200 years, we consider why, since its peak of approximately 1100 banks 1810, the population of British banks has declined to its present day population of less that 100. We hypothesise that amalgamation became an advantageous way for banks to expand, and use an agent-based simulation to test this hypothesis against the baking data. We are unable to falsify the hypothesis and show that the simulation reproduces many aspects of the real data with the minimum of assumptions.

A tipping point in 300 years of banking? A conceptual simulation of the British banking system

It has become popular to describe the behaviour of certain systems as “undergoing a tipping point”. This is normally used as a description of a system that has rapidly changed from an apparently stable state to a new state with little or no warning. A wide range of complex systems can display tipping point behaviour, from climate systems to populations of people. Here we present preliminary work of using the British banking sector from 1559 to 2012 as a case study for the modelling of complex systems that show tipping point behaviour. Currently implemented in a highly abstracted form, we present a description of a conceptual model of the British banking system that is able to reproduce the general features of the changing population of British banks. However, to do so requires interventions in the system, rather than emergent properties. We discuss what future alterations to the model could be made to overcome this limitation.

Temporal Relationships Between Individualism–Collectivism and the Economy in Soviet Russia: A Word Frequency Analysis Using the Google Ngram Corpus

Collectivism and individualism are commonly used to delineate societies that differ in their cultural values and patterns of social behavior, prioritizing the relative importance of the group and the individual, respectively. Collectivist and individualist expression is likely to be intricately linked with the political and economic history of a society. Scholars have proposed mechanisms for both positive and negative correlations between economic growth and a culture of either individualism or collectivism. Here, we consider these relationships across the dramatic history of 20th- and early 21st-century Russia (1901-2009), spanning the late Russian Empire, the communist state, and the growth of capitalism. We sample Russian speakers to identify common Russian words expressing individualism or collectivism, and examine the changing frequencies of these terms in Russian publications collected in Google’s Ngram corpus. We correlate normalized individualism and collectivism expression against published estimates of economic growth (GDP and net material product [NMP]) available between 1961 and 1995, finding high collectivist expression and economic growth rate followed by the correlated decline of both prior to the end of Soviet system. Temporal trends in the published expression of individualism and collectivism, in addition to their correlations with estimated economic growth rates, are examined in relation to the change in economic and political structures, ideology and public discourse. We also compare our sampled Russian-language terms for individualism and collectivism with Twenge et al.’s equivalent collection from American English speakers.

ROLE OF NEUTRAL EVOLUTION IN WORD TURNOVER DURING CENTURIES OF ENGLISH WORD POPULARITY

Here, we test Neutral models against the evolution of English word frequency and vocabulary at the corpus scale, as recorded in annual word frequencies from three centuries of English language books. Against these data, we test both static and dynamic predictions of two neutral models, including the relation between corpus size and vocabulary size, frequency distributions, and turnover within those frequency distributions. Although a commonly used Neutral model fails to replicate all these emergent properties at once, we find that modified two-stage Neutral model does replicate the static and dynamic properties of the corpus data. This two-stage model is meant to represent a relatively small corpus of English books, analogous to a ‘canon’, sampled by an exponentially increasing corpus of books among the wider population of authors. More broadly, this model — a smaller neutral model within a larger neutral model — could represent more broadly those situations where mass attention is focused on a small subset of the cultural variants.