Topical Diversity Research Articles

REGIONAL COOPERATION IN CENTRAL EUROPE: A SYSTEMATIC REVIEW

The paper systematically reviews ten years of academic literature published from 2014 to 2023 and indexed in the Scopus database to establish the current state-of-the-art on how Central European regional groups operate. The review includes 52 publications on six regional cooperation formats: the Central European Defence Cooperation, the Slavkov/Austerlitz Triangle, the Salzburg Forum, the Three Seas Initiative, the Visegrád Group and the Bucharest Nine. The paper finds that regional cooperation research is very concentrated on selected aspects of Visegrád cooperation and follows poor methodological reporting practices. The majority of studies analyse the V4 in relation to migration and foreign policy issues, whereas research on cooperation dynamics in other policy areas and within other active regional groups is marginal. After identifying promising future research directions, the paper calls for greater methodological and topical diversity in Central European regional cooperation research.

How Does Topical Diversity Affect Source Credibility? Fact-Checking Coverage of Politics, Science, and Popular Culture

How Does Topical Diversity Affect Source Credibility? Fact-Checking Coverage of Politics, Science, and Popular Culture

Science convergence in affective research is associated with impactful multidisciplinary appeal rather than multidisciplinary content

Affectivism is a research trend dedicated to the study of emotions and their role in cognition and human behavior. Affectivism both complements and competes with cognitivism, which typically neglects affect in explaining behavior. By the nature of their subject, both affectivism and cognitivism constitute fertile grounds for studying the confluence of conceptual knowledge from diverse disciplines, which is often credited with major breakthroughs and is known as convergence science. Analyzing over half a million relevant publications from PubMed, selected according to psychologist chosen MeSH terms, we find that affectivism yields higher impact than cognitivism, as measured through normalized citations. Importantly, this higher impact is strongly associated with higher multidisciplinarity in the citations of affectivism publications but lower multidisciplinarity in the papers themselves. Hence, the case of affectivism suggests that research content of low topical diversity but broad value can generate strong and wide-ranging scholarly impact, feeding downstream convergence.

Relationships between acculturative stress, internalized weight stigma, and psychological distress among Asian, Black, and Latinx adults

ABSTRACT The present study explored the associations between acculturative stress, internalized weight stigma, and psychological distress in a sample of racially diverse U.S. immigrants (n = 200). Linear regression analyses revealed that acculturative stress was a significant predictor of internalized weight stigma, and that internalized weight stigma was a significant predictor of psychological distress both before and after controlling for acculturative stress. Findings contribute to the topical diversity of literature regarding weight- and shape-related concerns in immigrant populations and have implications for multicultural social work education and practice.

Assessing the evolution of research topics in a biological field using plant science as an example.

Scientific advances due to conceptual or technological innovations can be revealed by examining how research topics have evolved. But such topical evolution is difficult to uncover and quantify because of the large body of literature and the need for expert knowledge in a wide range of areas in a field. Using plant biology as an example, we used machine learning and language models to classify plant science citations into topics representing interconnected, evolving subfields. The changes in prevalence of topical records over the last 50 years reflect shifts in major research trends and recent radiation of new topics, as well as turnover of model species and vastly different plant science research trajectories among countries. Our approaches readily summarize the topical diversity and evolution of a scientific field with hundreds of thousands of relevant papers, and they can be applied broadly to other fields.

Right Topic, Right Source? Source Diversity and Balance in Right-Wing Alternative News Content Across Topics

ABSTRACT This article investigates how the hybrid nature of right-wing alternative news media striving for journalistic legitimacy and partisan credibility plays out on source and topical diversity and balance in article content. The article draws on a sample of 1000 randomly selected articles published by 20 right-wing alternative online news media from six countries (the US, the UK, Germany, Austria, Denmark, and Sweden) from March 2019 to February 2020 (i.e., in “routine” pre-COVID-19 times). The results show that most of the alternative media outlets in the sample cover relatively broad topical spectra. More specifically, US and UK media primarily focus on politics and policy issues, whereas Scandinavian media are more heavily geared toward societal issues and crime coverage. Overall, right-wing alternative news content is characterized by a variety of partisan and non-partisan sources. However, core partisan topic areas, such as politics and mass media, are more likely to include partisan and especially right-wing sources. Often, with respect to these topics, right-wing sources are evaluated positively, and left-wing sources are evaluated negatively. Finally, right-wing and non-right-wing sources often appear in separate articles rather than in direct confrontation.

A Global Perspective on Data Journalism Materiality: Knowledge Production across Public Transparency Infrastructure Environments

It is widely accepted that data materiality serves as the breeding ground of data journalism’s performativity, in some cases functioning as the sole ingredient for news construction. Material identity is closely tied to the historical process that originated it, yet few studies have explored how unequal public policies on government transparency affect news production in data journalism. We bring in a fresh perspective on materiality that taps into research on public transparency to offer a framework for understanding how external social actors influence data knowledge construction. This study analyzed data journalism project entries in the Global Editors Network (GEN) and Sigma Awards from 61 countries to explore data journalism process and products across transparency environments. Results suggest that journalists operating in open data infrastructure are more likely to exhibit a dependency on preprocessed public data and their output exhibits topical diversity, while journalists operating in closed data infrastructures are more likely to use Right to Information legislation and alternative data sources. This study informs the debate on the empiricism of data journalism in knowledge construction, emphasizing how data access (or lack of access) affects not only journalistic epistemology but also power relationships and journalistic roles.

Scholarly Communication over a Decade of Publications

Ten years after the journal’s first publication, we are taking a closer look at the knowledge flows of the output of the journal Publications. We analyzed the papers, topics, their authors and countries to assess the development of scholarly communication within Publications. Our bibliometric analyses show the research journal’s community, where the knowledge of this community is coming from, where it is going, and how diverse the community is based on its internationality and multidisciplinarity. We compare these findings with the scopes and topical goals the journal specifies. We aim at informing the editors and editorial board about the journal’s development to advance the journal’s role in scholarly communication. The results show that regarding topical diversity and internationality, the journal has remarkably developed. Moreover, the journal tends towards the field of library and information science, but strengthens its multidisciplinary status via its topics and author backgrounds.

BIOMEDICAL CONVERGENCE FACILITATED BY THE EMERGENCE OF TECHNOLOGICAL AND INFORMATIC CAPABILITIES

We leverage the knowledge network representation of the Medical Subject Heading (MeSH) ontology to infer conceptual distances between roughly 30,000 distinct MeSH keywords — each being prescribed to particular knowledge domains — in order to quantify the origins of cross-domain biomedical convergence. Analysis of MeSH co-occurrence networks based upon 21.6 million research articles indexed by PubMed identifies three robust knowledge clusters: micro-level biological entities and structures; meso-level representations of systems, and diseases and diagnostics; and emergent macro-level biological and social phenomena. Analysis of cross-cluster dynamics shows how these domains integrated from the 1990s onward via technological and informatic capabilities — captured by MeSH belonging to the “Technology, Industry, and Agriculture” (J) and “Information Science” (L) branches — representing highly controllable, scalable and permutable research processes and invaluable imaging techniques for illuminating fundamental yet transformative structure–function–behavior questions. Our results indicate that 8.2% of biomedical research from 2000 to 2018 include MeSH terms from both the J and L MeSH branches, representing a 291% increase from 1980s levels. Article-level MeSH analysis further identifies the increasing prominence of cross-domain integration, and confirms a positive relationship between team size and topical diversity. Journal-level analysis reveals variable trends in topical diversity, suggesting that demand and appreciation for convergence science vary by scholarly community. Altogether, we develop a knowledge network framework that identifies the critical role of techno-informatic inputs as convergence bridges — or catalyzers of integration across distinct knowledge domains — as highlighted by the 1990s genomics revolution, and onward in contemporary brain, behavior and health science initiatives.

Езиковата бележка като лингвистичен жанр

The article is devoted to the topic of the language note as a linguistic genre. The actuality of the problem is motivated by the fact that so many linguistic notes have already been accumulated that they need to be described and structured; they represent the entire topical diversity of the linguistic levels; the texts of the language notes reflect current issues and are aimed at the needs of society. Although short in length, they unfold many problems of the modern Bulgarian language in full, and orient modern language speakers in the dynamics of language development. In the text, an attempt has been made to generally distribute the problems in the topical groups of the language notes: phonetic and speech problems, lexical and word-formation problems, morphological problems, problems of syntax and word order; stylistic inaccuracies, which are subject to comment in the language notes. Peculiarities related to the headings of the language notes in historical and contemporary terms are also commented upon.

Revisiting the Recent History of Consumer Behavior in Marketing Journals: A Topic Modeling Perspective

Abstract Through the years, a great deal of research had been dedicated to understanding how consumers think, feel, and behave in the marketplace. From its early development to the present, consumer researchers have adopted different methods and followed different approaches to describe the consumption phenomena. By pursuing a probabilistic approach, the current study aims to provide in-depth insight into consumer behavior research’s evolution and transformation between 1980 and 2020. The results exhibit a strong increase on subjects like consumer trust, self-identity, digital consumption, social media engagement, consumer culture theory, consumer motivation, and brand–consumer relationships. The citation analysis shows the most impactful articles and topics in consumer behavior research. The results indicate that articles on customer service satisfaction, experiential consumption, consumer trust, digital consumption, and social media engagement tend are heavily cited. And to understand each journals contribution an analysis based on citations, journal impact and topical diversity is also included. The study also includes the possible research directions for the future of consumer behavior.

A self-study of editorial board diversity at Biological Invasions

The editorial board of this journal, Biological Invasions, aims to publish research that informs understanding of the patterns and processes of invasions and discussion of relevant policy and conservation issues related to controlling invasions. Because the scope of the journal's interests is global, building an editorial board that represents the demographic, geographic, and topical diversity within the invasion sciences would best serve the journal's readership and reflect the scope of Biological Invasions' global interests. We suspect that an editorial board comprised of members representing the diversity in invasion science can improve data and knowledge on biological invasions and increase participation in Biological Invasions' publication process from more geographic regions and diverse perspectives. To initiate a process of self-reflection and a discussion on editorial representation at Biological Invasions, we are, for the first time, reporting demographic data for the historical and current editorial board membership. As of January 2021, we find skewed representation of certain demographic, geographic, and topical expertise. Over 85% of editors identify as white, > 70% speak English as their primary language, > 60% identify as male, and nearly 50% of editors are nationals of the United States. The editorship predominantly conducts research in temperate biomes, with most editors considering plants or invertebrates as their organismal expertise. These results highlight geographic and topical areas with uneven expertise that can guide us as we work to diversify the board of Biological Invasions.

Topical Interest and Degree of Involvement of Bilingual Editors in Wikipedia

Language reveals a lot of information about its speakers. Speakers of one language usually share common cultural habits or regional characteristics, and their similarities become more obvious within the context where there are multiple languages in use. We focus on studying bilingual users of Wikipedia, one of the largest multilingual user-generated content platforms. In Wikipedia, we can observe the patterns in the English edition, where users of multiple languages come together to express their thoughts and interests in the common language of English. To understand the specific topics edited by bilingual users, we analyze them in terms of revision counts, topics, and country names. We find that bilingual users are generally interested in more local topics, and their language is highly related with their topics. Also, we observe that the topical diversity decreases with the proportion of English edits, and more concentrates on topics related with countries and cultures.

Toward a fairer information retrieval system

With the increasing popularity and social influence of information retrieval (IR) systems, various studies have raised concerns on the presence of bias in IR and the social responsibilities of IR systems. Techniques for addressing these issues can be classified into pre-processing , in-processing and post-processing. Pre-processing reduces bias in the data that is fed into machine learning models. In-processing encodes fairness constraints as a part of the objective function or learning process. Post-processing operates as a top layer over the trained model to reduce the presentation bias exposed to users. This dissertation explored ways to bring the pre-processing and post-processing approaches, together with the fairness-aware evaluation metrics, into a unified framework as an attempt to break the vicious cycle of bias and improve fairness in IR. We first investigated the existing bias presented in search engine results. Specifically, we focused on the top-k fairness ranking in terms of statistical parity fairness and disparate impact fairness definitions. With Google search and a general purposed text cluster as a lens, we explored several topical diversity fairness ranking strategies to understand the relationship between relevance and fairness in search results. Our experimental results showed that different fairness ranking strategies resulted in distinct utility scores and performed differently with distinct datasets. Second, to further investigate the relationship of data and fairness algorithms, we developed a statistical framework that was able to facilitate various analysis and decision making. Our framework could effectively and efficiently estimate the domain of data and solution space. We derived theoretical expressions to identify the fairness and relevance bounds for data of different distributions, and applied them to both synthetic datasets and real world datasets. We presented a series of use cases to demonstrate how our framework was applied to associate data and provide insights to fairness optimization problems. Third, we proposed an evaluation metric FAIR for the ranking results that encoded fairness, diversity, novelty and relevance. This metric offered a new perspective of evaluating fairness-aware ranking results. Based on this metric, we developed an effective ranking algorithm that jointly optimized for fairness and utility. Our experiments showed that our new metric was able to highlight results that achieved good user utility and fair information exposure at the same time. We showed how FAIR metric related to existing metrics through correlation analysis and case studies, and demonstrated the effectiveness of our FAIR-based algorithm.

A topic network analysis of the system turn in the environmental sciences

The concept of Earth system science denotes a shift in the scientific discourse from disciplinary accounts of isolated components of the global environment towards the holistic and interdisciplinary treatment of their complex, functional interactions. We measure to what extent the environmental scientific literature of the past three decades reflects this system turn. Our initial dataset consists of 133,670 articles published in 95 relevant journals since 1990. We apply a combination of topic modelling and network analysis. Correlated Topic Models identify latent themes (“topics”) in the scientific discourse as well as intertopic correlations. This allows the generation of topic networks and thus the application of network-analytic techniques. We generate and analyze 2 topic networks. The first network focuses on climate linkages in a subset of our corpus consisting only of environmental journals without a climate-specific orientation: as the climate system is constitutional for the notion of Earth system science, a system turn should reflect itself in strong linkages between climate- and non-climate environmental topics. The second network, based on the full dataset, applies community detection to identify broader topical clusters. Here, we expect the system turn to manifest itself in communities with high topical diversity regarding the components of the global environment as well as types of human-nature interactions, rather than reflecting the boundaries between broader research fields. Our results show that climate topics are comparatively weakly connected and less integrated into broader thematic packages than other topics; that linkages frequently reflect conceptual debates rather than functional interactions between substantive environmental components; and that the scientific discourse splits into 4 broader domains, two of those being topically homogeneous and the other two comprising only marginally diverse topics. We conclude that the concept of Earth system science is primarily aspirational in nature rather than reflecting an empirical shift in the structure of the scientific discourse.

Evaluating Public Library Events using a Combination of Methods

Abstract Public libraries hold an increasing number of events, where they face the very important, but often neglected, challenge of evaluation. This paper presents various studies performed to evaluate events for adults at the largest public library in Slovenia, Mestna knjižnica Ljubljana (Ljubljana City Library). A combination of methods was used: content analysis of library website and promotional brochures, interviews with both attendees and librarians, observation of events and a relatively large survey. Additionally, based on this research, seven personas representing typical user groups of events for adults were developed. While attendees were generally highly satisfied with the existing events, our research found room for improvement, especially regarding planning for particular user groups, scheduling and topical diversity of events and promotion aimed at both existing and potential visitors. Based on this research, Ljubljana City Library prepared guidelines for their future events for adults. Additionally, the general outline of the evaluation should be of benefit to any library regardless of type, size or location.

Do synthesis centers synthesize? A semantic analysis of topical diversity in research

Synthesis centers are a form of scientific organization that catalyzes and supports research that integrates diverse theories, methods and data across spatial or temporal scales to increase the generality, parsimony, applicability, or empirical soundness of scientific explanations. Synthesis working groups are a distinctive form of scientific collaboration that produce consequential, high-impact publications. But no one has asked if synthesis working groups synthesize: are their publications substantially more diverse than others, and if so, in what ways and with what effect? We investigate these questions by using Latent Dirichlet Analysis to compare the topical diversity of papers published by synthesis center collaborations with that of papers in a reference corpus. Topical diversity was operationalized and measured in several ways, both to reflect aggregate diversity and to emphasize particular aspects of diversity (such as variety, evenness, and balance). Synthesis center publications have greater topical variety and evenness, but less disparity, than do papers in the reference corpus. The influence of synthesis center origins on aspects of diversity is only partly mediated by the size and heterogeneity of collaborations: when taking into account the numbers of authors, distinct institutions, and references, synthesis center origins retain a significant direct effect on diversity measures. Controlling for the size and heterogeneity of collaborative groups, synthesis center origins and diversity measures significantly influence the visibility of publications, as indicated by citation measures. We conclude by suggesting social processes within collaborations that might account for the observed effects, by inviting further exploration of what this novel textual analysis approach might reveal about interdisciplinary research, and by offering some practical implications of our results.

Improving data access democratizes and diversifies science

The foundation of the scientific method rests on access to data, and yet such access is often restricted or costly. We investigate how improved data access shifts the quantity, quality, and diversity of scientific research. We examine the impact of reductions in cost and sharing restrictions for satellite imagery data from NASA's Landsat program (the longest record of remote-sensing observations of the Earth) on academic science using a sample of about 24,000 Landsat publications by over 34,000 authors matched to almost 3,000 unique study locations. Analyses show that improved access had a substantial and positive effect on the quantity and quality of Landsat-enabled science. Improved data access also democratizes science by disproportionately helping scientists from the developing world and lower-ranked institutions to publish using Landsat data. This democratization in turn increases the geographic and topical diversity of Landsat-enabled research. Scientists who start using Landsat data after access is improved tend to focus on previously understudied regions close to their home location and introduce novel research topics. These findings suggest that policies that improve access to valuable scientific data may promote scientific progress, reduce inequality among scientists, and increase the diversity of scientific research.

Audit Partner Style in Key Audit Matter Reporting Decisions

We examine the relative importance of audit firm-level versus audit partner-level styles in key audit matter (KAM) outcomes. We define style as stable within-firm (partner) similarities and between-firm (partner) differences in KAM reporting over time and across clients and industries with respect to the volume of KAMs, their topical diversity, and the linguistic manner in which they communicate KAMs to users. Using a sample of UK KAMs, we find that firms and partners have unique styles for KAM reporting volume, topical diversity, and communication. Partner-level styles are the locus of KAM reporting decisions, adding 10 to 19 percent improvement in explanatory power versus firms’ two to five percent. Partner demographics do not meaningfully explain KAM reporting outcomes. We find that partners make unique KAM reporting judgments, countering concerns that audit firms’ standardization will yield boilerplate KAMs, but lending credence to concerns that KAM reporting judgments may lack comparability across partners.

Resurrecting Leather-Stocking: Pathfinding in Jacksonian America

Resurrecting Leather-Stocking: Pathfinding in Jacksonian America