Overview

As part of the Societal Analytics Lab goal to foster methodological innovation, we offer internship opportunities to students and scholars at different career stages (from master all the way to postdoc).

Applicants should have a background in computational social science, computational communication science, or computer science. As the Societal Analytics Lab aims to have a culture that enables everyone to develop their individual skills and competencies, candidates will be recruited solely on the basis of their qualifications, i.e. age, gender, religion, etc, won’t play any role. The Lab mostly operates in English. Depending on the time of the year and the year, we may also be able to fund a one-day attendance of a Dutch based conference, such as ODISSEI or ETMAAL.

These opportunities are open the whole year, except for December and August when we all are on holidays. Please feel free to send us your open application any time. However, keep in mind that from our side the whole recruiting and HR approval procedure can take up to four months. So, consider this together with your institution deadlines.

Requirements

Application must include your CV (including your full name, institutional email, and pronouns), and a maximum 2 A4 pages research plan. Font : Arial 11 pt., line distance 1. Applications deviating from this format may not be considered. The research plan should include the following information:

Full name and pronouns. Do not include any pictures!
Intended time you will be with us.
How you will fund your stay. Unfortunately, the Lab does not always have the resources to provide scholarships. If so, we will announce them in our “Job opportunities” section.
What you will be doing during your stay:
- Summary of what you will be working on. You can choose one of the three areas mentioned beneath.
- Timeline detailing your activities and goals per month.Please consider that we do not work neither in December nor in August.
- Some preliminary ideas on the methods and resources you will use to achieve your monthly-goals. Back-up this information with things you have learned during different moments of your academic career. For example, “During my bachelor’s I followed a course on … . Therefore, I would use these learnings to … .”

Main internship areas

1. Co-develop software as a service

The Lab is continuously developing software to facilitate researchers’ work. If you choose to work on this branch during your internship, then you will strengthen and practice your knowledge on back- and front-end development. For this, you are expected to know or have experience using Git, JavaScript or python, and (optionally) R. At the end of the internship, you will be expected to have pulled, pushed, and written (either for the AmCAT book or as a blog post) all the improvements you have done to the software.

Currently, we are mostly working on AmCAT and Annotinder.

AmCAT

A key challenge to open science practices, such as sharing and reusing data, is that many researchers consider it a burdensome afterthought rather than a core part of the research itself. AmCAT (Amsterdam Content Analysis Toolkit) addresses these needs by providing an open collaboration environment. As a collective benefit, AmCAT offers an open source and decentralized solution for storing and analysing potentially sensitive documents, decreasing dependence on commercial or foreign providers and their terms of use throughout the research life cycle. It also facilitates non-consumptive research when full data access is impossible. Combining a user-friendly GUI with a powerful API, AmCAT ensures researchers with varying computational skills can participate.

Annotinder

One bottleneck for scholars working in communication and computational social science is the lack of annotated datasets that they could use in their research. A possible way to ease this struggle is to provide scholars with the necessary software to annotate their own. Annotinder aims to be such a tool. Annotinder is an R-based software that launches an easy to use interface to perform crowd annotation.

2. Co-author a scientific article

In the Lab, we aim to multiplicate interdisciplinary work. Therefore, we offer researchers at the Faculty of Social Science the opportunity to work with scholars that could complement their work. In this branch of the internship, you will be paired with a researcher to work on the methodological part of their work. This could include retrieving and cleaning digital traces, and sometimes also part of the analysis. You will also be expected to help write the data and methods part of the work. If we are unable to pair you with a researcher, then you will be expected to work on one of the other two branches. Please keep this in mind.

3. Co-author a data article

As part of our goals, we aim to Increase Open Science through better reproducibility and transparency. One way we do so is by retrieving and annotating new datasets that could be used for communication and social science research, as well as benchmarks for computer scientists. In this branch of the internship, you work together with us to retrieve and annotate a multimodal (i.e. text, audio, image, or video) dataset. For this, you will be expected to help retrieve the data and to do the necessary research to come up with a thorough code book to train coders, and then to test the consistency of the coders work. At the end of the internship, you will be expected to have a first draft of a data paper following (Gebru et al., 2021). Some possible research fields for the data to be used:

Memes main supervisor Wouter van Atteveldt webpage
Journalism main supervisor Kasper Welbers webpage
Climate Change or AI risks main supervisor Sofia Gil-Clavel webpage

References

Gebru, T., Morgenstern, J., Vecchione, B., Vaughan, J. W., Wallach, H., Iii, H. D., & Crawford, K. (2021). Datasheets for datasets. Communications of the ACM, 64(12), 86–92. https://doi.org/10.1145/3458723

Internship Opportunities