Half a Century of NVSQ: Thematic Stability Across Years and Editors

2021 ◽  
pp. 089976402110176
Author(s):  
Chul Hee Kang ◽  
Young Min Baek ◽  
Erin Hea-Jin Kim
Keyword(s):  
Expert Opinion ◽  
Topic Modeling ◽  
Nonprofit Sector ◽  
Voluntary Sector ◽  
Analytic Method ◽  
Structural Topic Modeling ◽  
Over Time

The aim of this article is to understand how the scholarship of the nonprofit sector shifted after almost half a century (1972–2019) of publication in the field’s premier journal, Nonprofit and Voluntary Sector Quarterly. Unlike previous attempts to understand the field’s scholarly evolution, we did not rely on expert opinion and analysis of themes but applied an automated content analytic method, more specifically structural topic modeling (STM). Using this method, we identified 37 key thematic topics that most optimally represent the 1,516 articles that were published in the studied period. After reporting these 37 thematic topics, we analyzed fluctuations based on three key periods of the journal and the editors’ disciplinary fields. While overall there was a trend of continuity (29 out of 37 topics) and little if any impact of the editors’ disciplines, a few thematic topics showed decline and fewer showed increase over time.

Yet Another Expert Opinion on Bilirubin Toxicity!

PEDIATRICS ◽  
1992 ◽  
Vol 89 (5) ◽  
pp. 829-831
Author(s):  
LOIS JOHNSON
Keyword(s):  
At Risk ◽  
Expert Opinion ◽  
Term Newborn ◽  
New Guidelines ◽  
The Individual ◽  
Bilirubin Toxicity ◽  
Toxic Potential ◽  
Over Time

Drs Newman and Maisels1 have provided valuable new guidelines for management of jaundice in the term newborn which take into account age at discharge from the hospital and some of the factors altering the general risk of bilirubin toxicity. They note that much of the information needed to identify the individual at risk is still unavailable and remind their readers that their "recommendations should be reevaluated periodically as new data become available." I have serious concerns, however, with the second half of their paper which almost completely downplays the toxic potential of bilirubin, its often erratic expression, and its ability to cause a spectrum of damage ranging from frank kernicterus to insults that are so minor as to be compensated for completely over time.2-4

The Nonprofit Starvation Cycle: Empirical Evidence From a German Context

2019 ◽  
Vol 48 (3) ◽  
pp. 467-491 ◽  
Author(s):  
Peter Schubert ◽  
Silke Boenigk
Keyword(s):  
Nonprofit Organizations ◽  
Empirical Evidence ◽  
Nonprofit Sector ◽  
Government Funding ◽  
Financial Data ◽  
Organizational Infrastructure ◽  
The U.S ◽  
Over Time

The nonprofit starvation cycle describes a phenomenon in which nonprofit organizations continuously underinvest in their organizational infrastructure in response to external expectations for low overhead expenditure. In this study, we draw on nonprofit financial data from 2006 to 2015 to investigate whether the German nonprofit sector is affected by this phenomenon, specifically in the form of falling overhead ratios over time. We find reported overhead ratios to have significantly decreased among organizations without government funding and that the decrease originates from cuts in fundraising expenses—two results that are in contrast to previous findings from the U.S. nonprofit sector. With this study, we contribute to nonprofit literature by engaging in a discussion around the starvation cycle’s generalizability across contexts.

Structural Topic Modeling For Social Scientists: A Brief Case Study with Social Movement Studies Literature, 2005–2017

2019 ◽  
Vol 6 (4) ◽  
pp. 307-318 ◽  
Author(s):  
Nathan C. Lindstedt
Keyword(s):  
Social Movement ◽  
Topic Modeling ◽  
Research Process ◽  
Computer Assisted ◽  
Sociological Research ◽  
Social Scientists ◽  
Modeling Framework ◽  
Social Scientific ◽  
Structural Topic Modeling

Sociologists frequently make use of language as data in their research using methodologies including open-ended surveys, in-depth interviews, and content analyses. Unfortunately, the ability of researchers to analyze the growing amount of these data declines as the costs and time associated with the research process increases. Topic modeling is a computer-assisted technique that can help social scientists to address these data challenges. Despite the central role of language in sociological research, to date, the field has largely overlooked the promise of automated text analysis in favor of more familiar and more traditional methods. This article provides an overview of a topic modeling framework especially suited for social scientific research. By way of a case study using abstracts from social movement studies literature, a short tutorial from data preparation through data analysis is given for the method of structural topic modeling. This example demonstrates how text analytics can be applied to research in sociology and encourages academics to consider such methods not merely as novel tools, but as useful supplements that can work beside and enhance existing methodologies.

Content analysis of newspaper coverage of wolf recolonization in France using structural topic modeling

2018 ◽  
Vol 220 ◽  
pp. 254-261 ◽  
Author(s):  
Marie Chandelier ◽  
Agnès Steuckardt ◽  
Raphaël Mathevet ◽  
Sascha Diwersy ◽  
Olivier Gimenez
Keyword(s):  
Content Analysis ◽  
Topic Modeling ◽  
Newspaper Coverage ◽  
Structural Topic Modeling

30 years of contemporary hospitality management

2019 ◽  
Vol 31 (7) ◽  
pp. 2641-2665 ◽  
Author(s):  
Faizan Ali ◽  
Eunhye (Olivia) Park ◽  
Junehee Kwon ◽  
Bongsug (Kevin) Chae
Keyword(s):  
Topic Modeling ◽  
Relative Weight ◽  
Hospitality Management ◽  
Academic Journal ◽  
Research Topics ◽  
Content Type ◽  
Before And After ◽  
Hospitality And Tourism ◽  
Published Research ◽  
Over Time

Purpose This paper aims to showcase the trends in the research topics and their contributors over a time period of 30 years in the International Journal of Contemporary Hospitality Management (IJCHM). To be specific, this paper uncovers IJCHM’s latent topics and hidden patterns in published research and highlights the differences across three decades and before and after Social Sciences Citation indexing. Design/methodology/approach In total, 1,573 documents published over 199 issues of IJCHM were analyzed using two computational tools, i.e. metaknowledge and structural topic modeling (STM), as the basis of the mixed method. STM was used to discover the evolution of topics over time. Moreover, bibliometrics (and network analysis) were used to highlight IJCHM’s top researchers, top-cited references, the geographical networks of the researchers and differences in the collaborative networks. Findings The number of papers published continually increased over time with changes of key researchers publishing in IJCHM. The co-authorship networks have also changed and revealed an increasing diversity of authorship and collaborations among authors in different countries. Moreover, the variety of topics and the relative weight of each topic have also changed. Research limitations/implications Based on the findings of this study, theoretical and practical implications for hospitality and tourism researchers are provided. Originality/value It is the first attempt to apply topic modeling to a leading academic journal in hospitality and tourism and explore the diversity in contemporary hospitality management research (topics and contributors) from 30 years of published research.

scholarly journals Expert Opinion and Coherence Based Topic Modeling

2018 ◽  
Vol 7 (2) ◽  
pp. 01-14 ◽  
Author(s):  
Natchanon Suaysom ◽  
Weiqing Gu
Keyword(s):  
Expert Opinion ◽  
Topic Modeling

Taiwan as ghost island? Ambivalent articulation of marginalized identities in computer-mediated discourses

2019 ◽  
Vol 31 (3) ◽  
pp. 285-306
Author(s):  
Yao-Tai Li ◽  
Yunya Song
Keyword(s):  
Critical Discourse Analysis ◽  
Topic Modeling ◽  
Mainland China ◽  
Critical Discourse ◽  
Bulletin Board ◽  
Social Critique ◽  
Computer Mediated ◽  
Discourse Historical Approach ◽  
Self Presentations ◽  
Structural Topic Modeling

This study examines the conflicting self-presentations when using the term ‘ghost island’ in Taiwan, a self-mocking way to belittle the homeland. While some view this term as a form of social critique, others consider it to be suggestive of a social malaise affecting contemporary Taiwanese. Drawing on online posts and comments from the most popular bulletin board system in Taiwan, this study combines topic modeling with a discourse-historical approach (DHA) to critical discourse analysis (CDA) to examine the constructions of ‘ghost island’ by Taiwanese netizens. A computer-aided content analysis was implemented using Structural Topic Modeling (STM) to identify discourse topics associated with netizens’ discourses on ghost island. Our findings suggest that the images of ‘us’ (the ordinary people) are presented as victims as against powerful ‘others’ (e.g. mainland China and local elites). Specifically, self-mockery was often invoked to project a loser image and marginalized status living on the island, whereas self-assertive narratives were invoked to affirm Taiwanese society’s democracy and freedom. The conflicting narratives – with a mixture of grudge, helplessness, pessimism, hope and pride – point to Taiwanese netizens’ ambivalent articulation of marginalized identities that operates to strengthen affective connectedness and virtual bonding.

Sign in / Sign up

Export Citation Format

Share Document