Ngram Viewer Research Articles

Investments support for Sustainable Development Goal 7: Research gaps in the context of post-COVID-19 recovery

Successful achievement of the 17 Sustainable Development Goals (SDGs), including SDG 7: Affordable and Clean Energy, is impossible without proper financial support, especially after the devastating impact of the COVID-19 pandemic. Despite more than million academic papers related to SDG 7, only very few of them address the financial aspects of achieving SDG 7. To test the hypothesis, “SDG 7 related academic studies ignore the issue of investment in general and responsible investment in particular”, a meta-analysis is performed that includes a number of specific instruments and technics such as SciVal by Elsevier, VosViewer, Google trends, Google Books Ngram Viewer and Google Data. The results show a lack of appropriate academic support (methodology, empirical results, econometric models etc.) for practitioners to fill the existing financial gap and successfully achieve SDG 7. Among 1.2 million SDG 7 related papers, less than 100 deal with the financial gap problem measured by trillions of dollars in achieving SDG 7. This paper identifies the most promising and relevant topics for study related to SDG 7 and investment: the impact of the pandemic on decisions in the energy sector; efficiency of SDG 7 investment support and methodology for its assessment; green bonds, green loans, sovereign green bonds as responsible investment tools to advance SDG 7. Acknowledgments Inna Makarenko gratefully acknowledges support from the Supreme Council of Ukraine (0122U201796).The research was supported by the Scientific Grant Agency of the Ministry of Education, Science, Research, and Sport of the Slovak Republic and the Slovak Academy Sciences (VEGA), project No 1/0364/22: Research on eco-innovation potential of SMEs in the context of sustainable development.

Effect of IUCN Red List category on public attention to mammals.

Cultural data is a powerful tool to analyze public awareness of key societal issues, including the conservation of nature. I used two publicly available repositories of cultural data, Google Trends and Google Ngram, to quantify the effect of the International Union for the Conservation of Nature (IUCN) Red List conservation status on public attention toward 4539 mammal species. With Google Trends, I calculated whether Google searches for their common and scientific names have been increasing or decreasing over time. I also ran an anomaly detection analysis to investigate whether a change in red-list status directly results in an increase in Google searches. Additionally, I quantified the mentions of species' common and scientific names in English texts with Google Ngram. Overall, Google searches for most mammal species remained at similar levels or increased since 2008. The severity of species' IUCN Red List status was a significant predictor of increasing Google searches, although the effect size was relatively small. Red-list status seemed strongly confounded with mammal body size. Species that moved to a higher-risk category spiked significantly in Google searches directly after the new designation. The mention of species' common names in the Google Ngram's English 2019 corpus significantly increased as the red-list category increased. These results provide valuable insight into the importance of the IUCN Red List for increasing public awareness and the usefulness of publicly available cultural data on examining the effectiveness of specific conservation efforts and thus evaluating targets for support and funding.

Tea for Two: Language and Bilateral Trade with China

The article assesses the importance of cultural discourse in economics by exploring the extroversive cultural link between language use frequency and bilateral trade flows. Using linguistic data from Google n-grams and data on bilateral trade flows with China over the 1821–2008 period, we test whether the frequency of use of the word “tea” in a Chinese trading partner’s language is associated with the nominal value of its trade flows with China. Our findings suggest that the frequency of use of the word tea predicts current and future trade flows with China, and trade flows affect the frequency of use of the word tea albeit to a lesser extent. The frequency of use of the word tea is influenced by the overall size of the Chinese economy irrespective of the size of the economy of China’s trading partner, but smaller countries use the word tea more and increase its use faster. We conclude that the creation of a cultural discourse is endogenous to economic power, and cultural discourse amplifies trade flows. These findings validate the importance of narrative economics and the Culture-Based Development perspective.

ТРАНСФОРМАЦІЇ ГЕНДЕРНОЇ КОНЦЕПТУАЛІСТИКИ В ПОЛІТИЧНОМУ ДИСКУРСІ США (2017-2021)

The current article studies transformations of gender conceptualization in the political discourse of the USA from 2017 to 2021. In recent years, numerous large-scale protests in the United States of America, such as #MeToo, have affected political discourse, in particular in the United States. It should be noted that specific changes were also caused by the publication of UN recommendations on the use of more inclusive language in political communication, which did not rely on a binary understanding of gender, suggesting for the first time the use of gender-neutral terms and the avoidance of words that indicate masculinity (for example, congressman, etc.). These events lead to the transformation of the English language and weaken the binary understanding of gender, which can potentially affect the English speakers’ language world model. The article aims to investigate changes in the gender component in the language of USA political discourse associated with the introduction of gender-inclusive language and its impact on changes in the modern English language. To study the transformations of gender concept in the political discourse of the United States, a corpus linguistic analysis of the language of the United States Congress is proposed. Using two language corpora, namely the Google Books Ngram Viewer and the Congressional Regional Corpus, the article compares the frequency of use of gender marked words that are associated with a specific gender (e. g., congressman, spokesperson, etc.) with the frequency of their gender-neutral equivalents (representative, spokesperson, etc.). The comparative analysis allows us to draw a conclusion about changes in the political discourse of the USA, in particular in its gender conceptualisation: the gender component is becoming more inclusive, the binary understanding of gender is becoming less unambiguous, and the attitude towards non-binary personalities is becoming more tolerant.

P&T-Inf: A Result Inference Method for Context-Sensitive Tasks in Crowdsourcing

Context-Sensitive Task (CST) is a complex task type in crowdsourcing, such as handwriting recognition, route plan, and audio transcription. The current result inference algorithms can perform well in simple crowdsourcing tasks, but cannot obtain high-quality inference results for CSTs. The conventional method to solve CSTs is to divide a CST into multiple independent simple subtasks for crowdsourcing, but this method ignores the context correlation among subtasks and reduces the quality of result inference. To solve this problem, we propose a result inference algorithm based on the Partially ordered set and Tree augmented naive Bayes Infer (P&T-Inf) for CSTs. Firstly, we screen the candidate results of context-sensitive tasks based on the partially ordered set. If there are parallel candidate sets, the conditional mutual information among subtasks containing context information in external knowledge (such as Google n-gram corpus, American Contemporary English corpus, etc.) will be calculated. Combined with the tree augmented naive (TAN) Bayes model, the maximum weighted spanning tree is used to model the dependencies among subtasks in each CST. We collect two crowdsourcing datasets of handwriting recognition tasks and audio transcription tasks from the real crowdsourcing platform. The experimental results show that our approach improves the quality of result inference in CSTs and reduces the time cost compared with the latest methods.

The Keys to Clean Energy Technology: Impact of Environmental Taxes on Biofuel Production and Consumption

The growing level of modern environmental problems and the need to ensure energy security creates new challenges for the development of the energy sector. Nowadays, countries must balance their international competitiveness and progress in achievement the Sustainable Development Goals. This provides a necessity for the development of alternative energy technologies. Modern trends in the development of alternative energy indicate a gradual increase in the relevance of biofuel production. At the same time, the development of clean energy technologies needs significant investments, and their commercial implementation is a long process. Moreover, energy industry transformations require significant changes in the functioning of complementary spheres. That makes necessary the use of additional incentives for the development of the bioenergy sector. Thus, an assessment of the impact of environmental taxes on biofuel production and consumption becomes crucial. This research is aimed at the identification of contextual and causal relationships between environmental taxation (transport and energy taxes) and biofuel production and consumption. Contextual links were identified by the methods of bibliometric analysis (VOSviewer and Google Books Ngram Viewer results), while causal links were determined by the methods of panel regression modeling (panel-corrected standard errors model) with a time lag from 0 to 4 years. A sample of nine European countries (Austria, France, Germany, Hungary, Italy, The Netherlands, Poland, Spain, U.K.) was formed for the assessment. The research period includes 2010–2020. The conducted bibliometric analysis proved the presence of a wide range of relationships between environmental taxation and the development of the bioenergy industry. Panel regression modeling proved the existence of a significant impact of environmental taxation on the volumes of biofuel production and consumption. The increase in revenues from transport and energy taxes determines the growth in indicators of biofuel production and consumption. Such effects are medium term for transport taxes and short term for energy taxes. These results made a huge contribution in the development of the system of state regulation methods of alternative energy stimulation and energy production and consumption transformations.

Temporal and Geographic Patterns of Documentation of Sexual Orientation and Gender Identity Keywords in Clinical Notes.

Disclosure of sexual orientation and gender identity correlates with better outcomes, yet data may not be available in structured fields in electronic health record data. To gain greater insight into the care of sexual and gender-diverse patients in the Veterans Health Administration (VHA), we examined the documentation patterns of sexual orientation and gender identity through extraction and analyses of data contained in unstructured electronic health record clinical notes. Salient terms were identified through authoritative vocabularies, the research team's expertise, and frequencies, and the use of consistency in VHA clinical notes. Term frequencies were extracted from VHA clinical notes recorded from 2000 to 2018. Temporal analyses assessed usage changes in normalized frequencies as compared with nonclinical use, relative growth rates, and geographic variations. Over time most terms increased in use, similar to Google ngram data, especially after the repeal of the "Don't Ask Don't Tell" military policy in 2010. For most terms, the usage adoption consistency also increased by the study's end. Aggregated use of all terms increased throughout the United States. Term usage trends may provide a view of evolving care in a temporal continuum of changing policy. These findings may be useful for policies and interventions geared toward sexual and gender-diverse individuals. Despite the lack of structured data, the documentation of sexual orientation and gender identity terms is increasing in clinical notes.

The Possibilities and Limitations of Using Google Books Ngram Viewer in Research on Management Fashions

Google Books Ngram Viewer (GNV) is an analytical tool that uses quantitative methods to analyze digitized text. This paper looks at the possibilities and limitations of using GNV in management fashion research, an area of management research that examines the lifecycle and evolution of management concepts and ideas. GNV provides a historical big picture of the lifecycle and popularity of specific terms and phrases in books. It is argued that this tool could have a natural application in the study of management fashions, since books are a medium through which popular management concepts and ideas have traditionally been diffused. The paper provides several illustrative examples of how GNV can be applied to study management fashions and identifies the tool’s main possibilities and limitations. Although GNV has obvious advantages such as accessibility and user-friendliness, researchers should exercise caution, as it only provides a partial picture of the impact of management fashions.

From Sustainable Development to Social Responsibility: A perspective of Scientific Production Indicators and General Interest in Spanish

Context: In the last decades, one has the impression that the term sustainable development has evolved towards social responsibility and that the activities carried out by organizations and institutions are very similar. Nevertheless, this paper presents a theoretical discussion of the contribution of social responsibility. The question of this research is: through indicators of general interest and scientific production, it is possible to determine the evolution of sustainable development towards social responsibility? Methodology: Using the non-participatory method of secondary data analysis, secondary data from articles in the Redalyc, WorldCat, Microsoft Academic, Scopus, and Web of Science databases and specialized books on the topics were analyzed. Google Ngram Viewer and Google Trends were used to compare the variations of the indicators of scientific production and interest. Results: Through secondary data analysis, it was possible to establish indicators of general interest and scientific production. A discussion is presented on the evolution of sustainable development towards social responsibility. Conclusions: The results showed that the evolution of sustainable development towards social responsibility was not surpassed over time, except at some moments and in specific geographical locations. Method: Using the non-participatory method of secondary data analysis, secondary data from articles in the Redalyc, WorldCat, Microsoft Academic, Scopus, Web of Science databases and specialized books on the topics were analyzed. The Google Ngram Viewer and Google Trends software were used to compare the variations of the indicators of scientific production and interest. Results: Through secondary data analysis, it was possible to establish indicators of general interest and scientific production. A discussion is presented on the evolution of sustainable development towards social responsibility. Conclusions: The results showed that the evolution of sustainable development towards social responsibility was not overcome through time, except in some moments and geographical places.

Libraries and Archives in the Digital Age

Libraries and Archives in the Digital Age

Discerning cultural shifts in China? Commentary on Hamamura et al. (2021).

By examining the changes in the conceptual associations between individualism-collectivism and 10 other concepts based on the Google Ngram Chinese Corpus from the 1950s to the 1990s, Hamamura et al. (2021) inferred (a) no rise in individualism; (b) continuing collectivism; and (c) no effect of modernization on individualism in contemporary China. We question the validity of these conclusions given the following issues in their research: (a) misinterpretation of statistical results; (b) improper calculation of cultural associations; and (c) inappropriate generalization of specific findings. Contrary to their original findings, our reanalysis of their data suggests that individualism has been increasingly accepted and associated with some positive (vs. negative) aspects of life (e.g., income vs. loss, richness vs. poverty) over recent decades in China. Future research should use more rigorous methods and diverse corpora to clarify and explain changes in individualism and collectivism in China. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Artificial Friends and Becoming-Machine: A Digital Humanities and Posthuman Reading of Kazuo Ishiguro’s Klara and the Sun

Kazuo Ishiguro’s latest novel, Klara and the Sun presents a society with dormant layers that obscure the issues surrounding the human and the alterity of machines. With its technological advancements in gene editing and androids called Artificial Friends, Ishiguro’s novel presents a posthuman world where the posthuman concept of becoming-machine is seemingly mired in aporia. This paper attempts to examine this notion of “becoming-machine” and its entanglements in Ishiguro’s novel with digital humanities tools, Google Books NGram Viewer and Voyant Tools and a posthuman lens. I argue the claim that the diegetic process of child lifting and Klara’s sense of ethics, reveal the seemingly intertwined, but distinct notions of becoming within the text. One, becoming the machine, is a tangible, yet precarious process of humanity losing their ethical sense. While the other is one where Artificial Friends are ethically, in a posthuman sense, gaining ethical agency, or becoming-machine.

THE DISCURSIVE EMOTIONAL ASPECT OF IDEOLOGICAL TRANSITIONS IN THE VICTORIAN AGE

Introduction. The discursivity of emotions in ideology enactment is frequently questioned in ideology critique, whereas modern historical, psychological and social studies recognize the pertinence of emotions in shaping discursive practices. The current study argues the modulatory function of moral emotions in defining the complex phenomenon of Victorian ideology. Therefore, the dynamics of ideology proliferation is believed to ground in the emotional coherence of moral judgments.Purpose. The paper aims at investigating the large-scale process of ideology transitions characteristic of the Victorian period and beyond. The study lies in the assumption that ideological shifts pertaining to the period of the late 18th through early 20th centuries can be additionally tested in the term frequency of ideologically relevant issues as represented in the British English corpus brought by Google Books.Methods. Successive implementation of dictionary entry analysis, componential analysis, and machine based frequency analysis has testified to the plausibility of presumptions on the correlation of ideology long-term dynamics to the dominant emotional repertoires of the times.Results. The inventory of relevant ideologies has been provided in conformity with the earlier findings on the association of lexical representation of ideologies and moral emotions labels. The list of propositional ideologemes as fundamental doctrinal units of ideologies has been established basing on the common semantic features of nouns and adjectives defining the respective social practices in the contemporary dictionary entries. A frequency analysis aided by Google Books Ngram Viewer has evinced the heterogeneous process of ideologeme rises and declines.Conclusions. The ideological nature of moral emotions translates to their potency of modification or adjustment of propositional ideologemes in their further processing both for maintenance and/or transit. The trends are displayed in the dynamics of interest to the relevant ideological matters, in the changes of the semantic structure of lexicalized ideologemes andthe co-occurrence of emotion labels with the doctrinal linguoideologemes.

Measurement and prediction of the international reputation of Chinese women’s apparel and accessories

Chinese women’s apparel and accessories have been often mentioned by other countries in history and nowadays, and the underlying culture along with these apparel and accessories contributes to this developing world to some extent. The assessment of the international reputation for these kinds of apparel and accessories is important for better understanding the worldwide cultural exchange, globalization, social development and so on; however, it remains unknown. This study presents a work with the overall objective to measure and predict the international reputation of Chinese women’s apparel and accessories. To reach this objective, the study first proposes a data mining procedure to use online query volume data from the Google Ngram corpus to construct a reputation index in order to measure the international reputation of Chinese women’s apparel and accessories. Then, by establishing a series of socio-economic and political determinants associated with the international reputation of Chinese women’s apparel and accessories, several forms of support vector machine based models are developed, aiming to predict their international reputation. There are two contributions out of this work: (1) presenting the first ever large-scale quantitative examination of the trend and measurement of the international reputation of Chinese women's apparel and accessories, which provides a new method to identify the dynamic transition of sociocultural development; (2) constructing a quantitative model to predict the international reputation of Chinese women's apparel and accessories, which generalizes an implication to understand the other sociocultural object and its impact factors.

Moral foundations tracked over 200 years of lexicographic data, and their predictors

The prediction that reduction of negative selection decreases group-level competitiveness, as reflected in increased individual-focused and diminished group-focused moral foundations, is tested. To measure this hypothesized shift in moral foundations, we conduct a culturomic analysis of the utilization frequencies of items sourced from the moral foundations item pool, tracked among Britannic populations from 1800 to 1999 using Google Ngram Viewer. The resultant higher-order factor, which tracks increasing individualizing values and decreasing binding values, is termed Asabiyyah (capturing social cohesion and collective purpose). Two predictors of this factor are examined: change in the strength of intergroup competition and change in levels of indicators of developmental instability. Both the strength of intergroup competition and levels of developmental instability associate with Asabiyyah. Rising developmental instability mediates the impact of inter-group competition, indicating that reduced between-group competition might have relaxed negative selection against mutations, which might reduce Asabiyyah via their effects on inter-genomic transactions. These results must be interpreted carefully, given the clear real-world evidence that explicit commitment to group-oriented values often features in harmful and maladaptive social and political ideologies of an extreme character.

“Merciless Indian Savages”: Deconstructing Anti-Indigenous Framing

In this article, we identify and develop the specific anti-Indigenous subframe of the long dominant larger white racial frame. Using sociological concepts of systemic racial oppression, we show how the anti-Indigenous subframe co-naturalizes race concepts and specific racist language, embedding a deep and lasting negative framing of Native Americans in the U.S. society. We utilize the Google Ngram Viewer for digitized document identification and retrieval, an important social science tool for finding major historical documents for analysis. Using important documents, we identify a very specific language of Indigenous oppression and examine its central role in anti-Indigenous racial framing, past and present. We demonstrate how powerful and influential political, religious, and scholarly figures and major institutions have developed this racist framing over centuries of systemic Indigenous oppression in the United States. Our analysis adds to the body of social science knowledge by explicating how Indigenous oppression on a systemic level has been perpetuated, rationalized, and legitimated by means of a broad white racial frame and its powerful anti-Indigenous subframe.

INTERNATIONAL CONVERGENCE OF FINANCIAL REPORTING

The purpose of this article is to study the state of global convergence of financial reporting standards at the present stage, as well as to consider the key points of the process of unification of International Financial Reporting Standards (IFRS) and Generally Accepted Accounting Principles (GAAP). To achieve this goal, the article considers the concepts of convergence, harmonization and standardization, presents an analysis of the intensity of use of these concepts, which are associated with the dynamic development of recent global accounting transformations and major trends in international convergence of financial reporting. The key stages of the process of unification of International Financial Reporting Standards (IFRS) and Generally Accepted Accounting Principles (GAAP) are considered. For decades, the European Union, the International Organization of Securities Commissions (IOSCO) and the Committee on International Accounting Standards have supported international efforts to harmonize US GAAP and IFRS. accounting and reporting standards used in different countries. We have determined that while both IFRS and GAAP aim to provide transparency, informational content and usability in financial statements, these standards use different approaches to achieve this. We indicated that at present IFRS is the dominant accounting and reporting system, in fact, only third world countries do not apply it. We have proven that in the process of achieving convergence, a single set of understandable and feasible international accounting standards must be developed, requiring high quality, transparent and comparable information in financial statements in order to ensure convergence of IFRS and GAAP. We analyzed the intensity of the use of the concepts of IFRS and GAAP, which are associated precisely with the convergence of these accounting systems using the Google Ngram Viewer (GNV) tool. We have proved that the Convergence of IFRS and GAAP also applies to Ukraine, since the convergence is bilateral, any change in IFRS will ultimately affect the Ukrainian accounting and reporting system.

Culturomic Explorations of Literary Prominence Using Google Books: A Pilot Study

The availability of databases of digitised literary materials, such as Google Books, Europeana and historical newspaper databases, has revolutionised many disciplines, e.g., linguistics and history. So far, the use of digitised materials has not been very frequent in the history of books and the history of reading. This article presents tools, methodologies and practices that offer new possibilities in the study of book history and the history of reading. The use of these tools makes it possible to study vast amounts of data quickly and effectively, to present results in helpful visualisations, to make it possible to follow the line of reasoning and, if necessary, to check the reliability of the research by presenting the data for control. The examples presented are drawn from the Google Books database using a simple piece of software that exploits the API of the Google Books Ngram Viewer tool that is available free of charge.

Using Digital Humanities for Understanding COVID-19: Lessons from Digital History about Earlier Coronavirus Pandemic

(digital) history can give us about the past pandemics and dealing with them. We show that the Google Ngram Viewer (GNV) can discover hidden patterns in history (of pandemics). Our study is searching for evidence that the COVID-19 is not a unique phenomenon in human history. By using the approach of Digital Humanities, we are testing the hypothesis that the flu-like illness that caused loss of taste and smell in the late 19th century (Russian flu) was caused by a coronavirus. This approach could give hints on how the COVID-19 might develop in the following years. The objective was to calculate the ratio of increasing to decreasing trends in the changes in frequencies of the selected words representing symptoms of the Russian flu and COVID-19. The primary methodological concept of our approach is to analyse the ratio of increasing to decreasing trends in the changes in frequencies of the selected words representing symptoms of the Russian flu and COVID-19 with the Google NGram analytical tool. Initially, keywords were chosen that are specific and common for the Russian flu and COVID-19. We show the graphic display on the Y-axis what percentage of words in the selected corpus of books (collective memory) over the years (X-axis) make up the word. To standardise the data, we requested the data from 1800 to 2019 in English, German and Russian (to 2012) book corpora and focused on the ten years before, during and after the outbreak of the Russian flu. We compared this frequency index with “non-epidemic periods” to test the model’s analytical potential and prove the significance of the results. The limitation of this study is that it is difficult to formulate a hypothesis for a microbiological aetiology of a pandemic that occurred 133 years ago based on symptoms. There are indications that COVID-19 is not unique because the Russian flu (1889-1891) might be a coronavirus infection. The most crucial observation of similarities between the Russian flu pandemic and COVID-19 is the loss of smell and taste (anosmia and ageusia). Results show that all the three analysed book corpora (including newspapers and magazines) show the increase in the mention of the symptoms “loss of smell” and “loss of taste” during the Russian flu (1889-1891), which are today undoubtedly proven to be key symptoms of COVID-19. The mention of symptoms and the pandemic-related words fell sharply after the pandemic stopped. According to our analysis of historical records with the approach of GNV, 1) the ‘natural’ length of a pandemic is two to five years; 2) the pandemic stops on its own; 3) the viruses weaken over time; 4) the so-called “herd immunity” is not necessary to stop the pandemic; 5) Our approach has shown that a significant crisis does not need to occur after the COVID-19 pandemic. According to our study, GNV clearly shows the influence that social changes have on word frequency. The results of this study open a discussion on the usefulness of the Google Ngram insights possibilities into past socio-cultural development, i.e. epidemics and pandemics that can serve as lessons for today. However, this method has severe limitations and can be useful only under cautious handling and testing. Despite the numerous indications, we are aware that this thesis still cannot be confirmed and that it requires further historical and medical research. Keywords: Google Ngram, big data, epidemic, COVID-19, Russian flu, digital Humanities

Integrated reporting: bibliometric landscape

The growing importance of non-financial disclosure and development of integrated reporting concept necessitates a formation of complex systematic theoretical background, in particular, by means of the bibliometric analysis. Use of special software (VOSviewer, SciVal, Publish or Perish, inbuilt database analysis tools in Scopus, Web of Science and GoogleScholar; Google Trends and Google Books Ngram Viewer) expands the analytical capabilities of bibliometric analysis and helps to cover the entire array of existing papers on integrated reporting. In particular, this paper covers: the assessment ofgeneral dynamics of publications; systematisation of the chronological and regional specifics of publications; study of the thematic specifics of publications by analysing keywords, subject areas, and thematic clusters.