The research topic landscape in the literature of social class and inequality

Liang Guo; Shikun Li; Ruodan Lu; Lei Yin; Ariane Gorson-Deruel; Lawrence King

doi:10.1371/journal.pone.0199510

The research topic landscape in the literature of social class and inequality

PLoS One. 2018 Jul 2;13(7):e0199510. doi: 10.1371/journal.pone.0199510. eCollection 2018.

Authors

Liang Guo¹, Shikun Li¹, Ruodan Lu², Lei Yin³, Ariane Gorson-Deruel⁴, Lawrence King⁵

Affiliations

¹ Institute of Computational Social Science, Shandong University, Weihai, China.
² Engineering Department, Cambridge University, Cambridge, United Kingdom.
³ Institut Supérieur de Management et Communication, Paris, France.
⁴ Kantar TNS, Paris, France.
⁵ Department of Economics, University of Massachusetts, Amherst, MA, United States.

Abstract

The literature of social class and inequality is not only diverse and rich in sight, but also complex and fragmented in structure. This article seeks to map the topic landscape of the field and identify salient development trajectories over time. We apply the Latent Dirichlet Allocation topic modeling technique to extract 25 distinct topics from 14,038 SSCI articles published between 1956 to 2017. We classified three topics as "hot", eight as "stable" and 14 as "cold", based on each topic's idiosyncratic temporal trajectory. We also listed the three most cited references and the three most popular journal outlets per topic. Our research suggests that future effort may be devoted to Topics "urban inequalities, corporate social responsibility and public policy in connected capitalism", "education and social inequality", "community health intervention and social inequality in multicultural contexts" and "income inequality, labor market reform and industrial relations".

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Humans
Models, Theoretical
Publications
Research*
Social Class*
Socioeconomic Factors*

Grants and funding

Liang Guo is supported by the Qilu Project of Shandong University, China. Ruodan Lu is supported by the British EPSRC DTA fund (DTA2014). Ariane Gorson-Deruel receives salary from Kantar TNS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The specific roles of these authors are articulated in the ‘author contributions’ section.