Last compiled on September, 2025
In Week 1 I set up my git and github accounts and created this lab journal. I also started going through the R tutorial Jochem uploaded to Brigthspace.
In the second half of the day I learned about different kinds of
relations, types of relations, ego’s, ego characteristics and network
characteristics. After this I started on the assignment for Week 2:
finding a research question for my final assignment.
For next week we have to
Formulate initial Descriptive and Explanatory Research Questions
Find one or two relevant papers with respect to your research questions and that clearly provide a social network perspective
Be prepared to discuss your RQs and literature next week.
Update your lab journal / website. Be prepared to show you lab journal during class.
I just finished the R tutorial. I had already learned the basics of R and the tidyverse package in a course last year, but this tutorial was a great way to refresh my memory. I also picked up some new things, like the case_match function for editing variables (which I used to handle in a much more complicated way), and the simple methods for creating polished tables directly in R. Previously, I would export results to Excel and then copy them into Word to make them look nice, so these new tools will definitely save me time.
# Important R codes:
#mutate() # create or change variables
#case_match() # recode values by conditions
#across() # apply same transformation to many variables
#select() # keep or reorder columns
#filter() # keep rows by condition
#arrange() # order rows
#group_by() # define groups for calculations
#summarise() # collapse to summary stats
#ungroup() # drop grouping
#na_if() # set specific values to NA
#as.factor() # convert numeric → categorical
#levels() # rename factor categories
#rowwise() # do calculations row by row
#add_row() # append rows to a dataset
#full_join() # merge datasets by key
#stargazer() # create regression tables (LaTeX/HTML/Text)
#apa.reg.table() # APA-style regression tables (Word/RTF)
#as_flextable() # turn model or data frame into Word/PowerPoint table
#str() # structure of object
#summary() # descriptive statistics
#table() # frequency counts
#attributes() # see labels/metadataNext, I went through the Appendix B on variance, covariance, correlations and specifically the intraclass correlations. Here, I found the R scripts sometimes difficult to follow, especially the intraclass correlations part: why does it matter if data is in wide or long format? I will be asking questions on this in the next lecture and hope that will provide some clarity.
Lastly, I continued working on the assignment by developing a research question and identifying related articles. I knew I wanted to focus on gender inequality in academia, so I began exploring studies that use social network analysis on this topic. One concept that stood out to me was homophily: men often collaborate primarily with other men, while women tend to work in more diverse teams. This made me curious about how collaboration patterns relate to inequality outcomes, specifically, whether the composition of research collaborations influences the success of a paper or the researchers themselves. Do male collaborations get more prestige? If women are able to join a male collaboration, does it influence their prestige?
RQ1: To what extent does gender homophily shape collaboration patterns among researchers in Dutch sociology and politicology departments?
RQ2: How does the gender composition of collaborations among researchers influence the number of citations a paper gets?
RQ3: Do collaboration teams with higher female representation focus on different topics than teams with higher male representation?
RQ4: Are these “female-associated” topics valued less in terms of impact (e.g., citation counts, journal prestige) compared to topics more associated with male-dominated teams?
RQ5 (optional extension): Do patterns of gender homophily, topic focus, and recognition vary across universities, depending on the overall gender composition of their sociology and politicology departments?
RQ5: Are collaborations and networks more important for women than for men in citations of publications?
Two articles related to these questions would be: Collins, R., & Steffen-Fluhr, N. (2019). Hidden patterns. Equality Diversity And Inclusion An International Journal, 38(2), 265–282. https://doi.org/10.1108/edi-09-2017-0183
Torre, M., Prieto-Alonso, J. A., & Ucar, I. (2025). The uneven effects of gender parity: Trends in gender homophily in scientific publications, 1980–2019. Social Science Research, 132, 103228. https://doi.org/10.1016/j.ssresearch.2025.103228
Today I read Chapter 2, Paragraph 3.3 and Chapter 5. While I could follow Chapter 2 and Paragraph 3.3, Chapter 5 was very difficult to read and understand.