2023/09/25 by Aniket Kesari, Jae Yeon Kim, Sono Shah +3 · 1 voice
Computer Science · Social Sciences · #Computational and Text Analysis Methods #Data Analysis with R #Qualitative Comparative Analysis Research
paper · pdf · doi:10.1017/s1049096523000732
openalex publication_date 2023/09/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
ABSTRACT Social scientists with data science skills increasingly are assuming positions as computational social scientists in academic and non-academic organizations. However, because computational social science (CSS) is still relatively new to the social sciences, it can feel like a hidden curriculum for many PhD students. To support social science PhD students, this article is an accessible guide to CSS training based on previous literature and our collective working experiences in academic, public-, and private-sector organizations. We contend that students should supplement their traditional social science training in research design and domain expertise with CSS training by focusing on three core areas: (1) learning data science skills, (2) building a portfolio that uses data science to answer social science questions, and (3) connecting with computational social scientists. We conclude with practical recommendations for departments and professional associations to better support PhD students.