In times of covid-19, virtual workshops can be quite hard for organizers as well as for participants. On the other hand, they offer a unique opportunity to try unconventional methods to improve the situation for both sides. Dr. Demival Vasques Filho, in cooperation with Anna Aschauer, grasped such an opportunity at the DARIAH-DE-workshop Network Analysis with Python for Beginners, when he decided to simultaneously code and explain the basis on network analysis. Furthermore, he managed to address academics from different research areas with the help of some well-known fictional characters.
The code-along concept
The workshop, planned for a daily session on the 24th February 2021 and a short presentation and feedback session the day after, actually started a week earlier with access to some preparing material on GitHub (Python programming, Data Analysis with Python). This was a pleasant way to get in touch with python and Jupyter notebook for those who never heard of it and to remind the others of the essential commands needed for the workshop.
The different starting points of the attendees, occupied by themselves during the introduction session on Wednesday, matched perfectly with the code-along concept. While there were detailed explanations of every step from creating a network, to analyze and visualize the same, there also was space for additional demonstrations. So, the participants could ask questions concerning the use of code for their own projects or to get further remarks on problems they already struggled with in their own analyses. Because of this kind of freedom in the procedure, it was uncomplicated to react to the group members‘ needs and their speed. Besides all these advantages the method has shown one challenge: it is much more difficult to schedule the different aspects of the workshop when running the code in time. Which should not act as a deterrent for it.
The uniting element of pop culture
Digital humanities unite not just people from different levels of coding experience but members from different research areas. Therefore, it is sometimes not easy to find datasets supporting the explanations and making difficult aspects more understandable instead of diminishing the understanding. In this case, it was an inventive step to take datasets related to pop culture. It was far easier to learn about centrality measures and the meaning of the output in statistical analysis when already having a feeling for the network. Because of this, the attendees were able to think of the results while the code was running. Of course, this possibility is not given in real research and analysing situations, but it helped to get to know the different parameters. While learning with some Game of Thrones datasets the practical work on the afternoon of the first day went on with analysing the networks for each of the six Star Wars episodes.
In groups of two or three, the participants tried to reproduce the steps they learned about in the morning and to apply them in an adequate way to the new datasets. Instead of the prepared ones, it was also possible to work on an own dataset, which was also used once. Especially when working on a project alone this might be a useful option.
For the rest of the day, the groups worked in zoom break-out rooms while the two coordinators went from to room to support and offer help with individual problems. In this Situation, the Jupyter notebooks from the preparation as well as from the morning session formed a good base to work through and play with the datasets. The use of different data formats in the workshop was a nice feature that forced the group members to think about the content of the code and avoided getting into a copy and paste workflow.
The feedback of the “Beginners”
Presenting the results, the next day to the others was a great ending for the workshop in so far as not just technical issues could be discussed once more but also a nice discussion about the networks of the different episodes came up. The participants have appreciated the content of the workshop as well as the realization. The exchange on problems the participants had during the workshop was of particular interest. It appeared that they were rather similar and at least not directly relating to the topic or the workshop itself. The issues that showed up were mostly connected to creating a base for the actual analysis with python. As the classification of the workshop related to the actual topic, there was no specific introduction on working with GitHub, different data formats, or in general fundamentals of IT like paths when importing data or how to avoid them.
It might not be a solution to include these basics in every Beginner’s offer but in times of home office and online workshops, it has to be highlighted that these are part of the fundamental structures that have to consolidate in each DH context for barrier-free digital performances.