Book review: Gathering Data for Your PhD

Gathering data for your Phd is a small but useful book. It only took me one afternoon to finish it. This book gives a brief introduction the advantages and disadvantages of different data collection approaches. For instance, questionnaire, interview(structured, semi-structured, unstructured, mobile interview, face-to-fact), focus group, participant observation, etc. You will be encourage to use/invent an approach that is suitable for your study, for example, drawing and writing for young children, storying telling, diaries and so on.

While you are reading this book, you may focus on the part that covers the research approach you are interested in. There are many useful references for each approach. Since I am conducting social media data analysis, I mainly focus on the research ethics, mobile Apps and possibly gaming data (I do wish to write a mini game to collect attention/self-monitor skill related data, because it should be easier to collect data with a game, sample could be a bit biased though)

Here I selected some useful resources from the book for my future reference


  • Research ethics:


Informed consent

Research ethics online training

introduction to research ethics


social media and research ethical resource


(I might spend some time to do the research ethics online training in the coming few days. The training center offers a certificate, not sure how useful it is, but it doesn’t seem to take me too long to finish that course.)


  • Gathering data online raises tricky ethical issues around anonymity and confidentiality, because social media blurs the boundaries between private and public.



(thousands of APIs in here!)

Author: Lucia

I’m a Ph.D. student at the University of Edinburgh, School of Informatics. My research project involves using digital data to track the affective, cognitive, and behavioral changes of users, identifying the associations between digital signals and symptoms of mental disorders. I am interested in early symptom detection as a human-centered approach to assist interventions and early prevention of mental disorders or harmful behaviors. Along the way, I deeply care about ethical research practices, model bias and fairness. My work involves understanding model biases and examining the ‘noise’ in social media signals. I am writing up my Ph.D. thesis at the moment and looking for a post-doctoral research position. I am also passionate to communicate my research and machine learning methods. Check out my YouTube channel: ML_made_simple

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