Development studies research 1975-2014 in academic journal articles: The end of economics?

Abstract

The field of development studies analyses causes and potential solutions for global poverty and inequality. Since the Second World War there have been major changes in theories about the root causes of global poverty and the strategies necessary to tackle it. This article views the history of development studies from the perspective of the role of economics during . A topic modelling analysis of published journal articles from Scopus suggests that there has been a relative decline in research that focuses on economics, and particularly for research concerned with firms and growth. In parallel, the analysis suggests that there has been a relatively slow increase in interest in the environment, a lack of scholarly interest in BRICS and dependency theory, and a relatively homogeneous treatment of gender issues. KeywordsDevelopment studies; Trends analysis; Topic models; Scientometrics; Bibliometrics; Economics. ResumenEn los estudios sobre desarrollo se analizan las causas y las posibles soluciones para la pobreza y la desigualdad globales. Desde la Segunda Guerra Mundial se han producido cambios importantes en las teorías sobre las causas de la pobreza mundial y las estrategias necesarias para hacerle frente. En este artículo se revisan los estudios de desarrollo publicados en el período 1975-2014 desde la perspectiva del papel jugado por la economía. Un análisis de los temas de los artículos publicados en revistas indexadas en Scopus sugiere que ha habido una disminución relativa de la investigación centrada en la economía, y en particular en la investigación sobre empresas y crecimiento. Paralelamente, el análisis sugiere que se ha producido un lento aumento en el interés por el medio ambiente, falta de interés del mundo académico por los países BRICS y la teoría de la dependencia, y un tratamiento bastante homogéneo de las cuestiones de género.

How to Identify Hot Topics in Psychology Using Topic Modeling

“…A topic was defined as hot if it showed an increasing linear trend in popularity and cold if it showed a decreasing linear trend in popularity. This approach was adapted in several other research fields, for example, to identify the major biological concepts from a corpus of protein-related publication titles and abstracts (Zheng, McLean, & Lu, 2006), to conduct a bibliometric analysis of aquaculture literature (Natale, Fiore, & Hofherr, 2012), to analyze the field of development studies (Thelwall & Thelwall, 2016), or to explore hydropower research (Jiang, Qiang, & Lin, 2016). The current study is the first to apply LDA-based topic modeling for a scientometric analysis of psychological research in the German-speaking countries.…”

“…Griffiths and Steyvers (2004) examined different values of k and compared the resulting log-likelihoods. Yet another approach would be to test various values of k and determine the optimal k intellectually, that is, by expert judgment to decide whether the topics are in balance between too broad or too specific (Thelwall & Thelwall, 2016). In this study, we follow the first approach.…”

Social network and HIV/AIDS: A bibliometric analysis of global literature

“…As a result, we could use LDA to annotate the topic of the papers to find hidden themes and gain a comprehensive understanding of the patterns of HIV/AIDS and social networks ( 44 ). A total of 15 topics emerged based on consultation with HIV and social network experts ( 45 ). Each topic was labeled by referring to the topic's 15 most frequent terms as well as titles/abstracts within the topic.…”

Identification of Topics and Their Evolution in Management Science: Replicating and Extending an Expert Analysis Using Semi-Automated Methods

“…LDA has been used to identify trends in journals as diverse as Computers and Industrial Engineering (Uys, Shutte, & Van Zyl, 2011) and the Journal of Economic History (Wehrheim, 2017). There are many multi-journal reviews using topic modeling, including: a review of the field of development studies using 26,685 articles from 30 journals with 15 years of data (Thelwall & Thelwall, 2016), a review of physics using 3,448 articles across five journals (Peskin & Dima, 2017), and a corpus of scientific abstracts containing 5,225 abstracts with 28,414 unique terms (Blei et al, 2003).…”