TY - JOUR
KW - computational social science
KW - doctoral students
KW - Mental Health
KW - supervision
KW - taboo
AU - Saule Bekova
AU - Ivan Smirnov
AB - Improving the experience and well-being of doctoral students requires a deep and nuanced understanding of their challenges. Traditionally, researchers have used reactive methods, such as surveys and interviews, to address these issues. However, some topics may be difficult to capture through these approaches, particularly those that are intentionally avoided or hard to discuss openly—what we might call ‘taboo’ topics. In this paper, we propose an approach to addressing this challenge by using nonreactive data sources, particularly from social media platforms and other online forums. We operationalise taboo as topics that are raised as explicitly anonymous questions by doctoral students, suggesting their prohibited or restricted nature. Our goal is twofold: first, to understand the whole range of challenges discussed by doctoral students on social platforms, and second, to determine which of these challenges are considered taboo by comparing explicitly anonymous and nonanonymous questions. By relying on large-scale computational analysis of social media data, our approach offers a comprehensive and unfiltered view of graduate student concerns and experiences. Our results highlight the prevalence of questions related to the taboo in academia, particularly concerning mental health and supervision.
BT - Higher Education Quarterly
DA - 2026
DO - 10.1111/hequ.70145
IS - 3
LA - en
N2 - Improving the experience and well-being of doctoral students requires a deep and nuanced understanding of their challenges. Traditionally, researchers have used reactive methods, such as surveys and interviews, to address these issues. However, some topics may be difficult to capture through these approaches, particularly those that are intentionally avoided or hard to discuss openly—what we might call ‘taboo’ topics. In this paper, we propose an approach to addressing this challenge by using nonreactive data sources, particularly from social media platforms and other online forums. We operationalise taboo as topics that are raised as explicitly anonymous questions by doctoral students, suggesting their prohibited or restricted nature. Our goal is twofold: first, to understand the whole range of challenges discussed by doctoral students on social platforms, and second, to determine which of these challenges are considered taboo by comparing explicitly anonymous and nonanonymous questions. By relying on large-scale computational analysis of social media data, our approach offers a comprehensive and unfiltered view of graduate student concerns and experiences. Our results highlight the prevalence of questions related to the taboo in academia, particularly concerning mental health and supervision.
PY - 2026
EP - e70145
ST - ‘I Don't Want to Kill Any More Mice’
T2 - Higher Education Quarterly
TI - ‘I Don't Want to Kill Any More Mice’: Taboo and Silence in PhD Education
UR - https://onlinelibrary.wiley.com/doi/abs/10.1111/hequ.70145
VL - 80
Y2 - 2026-05-23
SN - 1468-2273
ER -