Summer Institute for Computational Social Science (SICSS) festival
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Megan Kang
Jun 14, 2021, 10:02:21 AM6/14/21
to Computational Sociology
Dear colleagues,
We're happy to announce the schedule for the 2021 SICSS Festival (https://sicss.io/festival), which begins in one week.
You can find the full schedule below or in this twitter thread: [link here]
Please spread the word to people that might be interested.
Best,
Megan Kang
### Using images and video data for social science: Challenges and opportunities
Time: Tuesday, June 22, 2021. 11am-12pm EDT
Speakers: Bryce Dietrich (Assistant Professor of Social Science Informatics at the University of Iowa), Laura Nelson (Assistant Professor of Sociology at Northeastern University), Michelle Torres (Assistant Professor of Political Science at Rice), and Han Zhang (Assistant Professor in Division of Social Science at The Hong Kong University of Science and Technology)
Moderator: Thomas Davidson (Assistant Professor of Sociology at Rutgers University)
Description: Social life is increasingly mediated through images and video and recent advances in machine learning make it possible to analyze these data at scale. It has become commonplace for computational social scientists to work with text and other complex, unstructured data, but we are only just seeing work that uses computational methods to study images and video. This panel focuses on this innovative area of research, exploring how scholars are using such data in cutting-edge research and the technical and ethical challenges involved in such analyses.
Open to: Unlimited registered participants
Register: https://forms.gle/FaBQ1afa9nNdAppw8
### Introduction to Text Analysis in Python: A Hands-on Tutorial
Time: Tuesday, June 22, 2021. 1pm-2pm EDT
Speakers: Austin van Loon (SICSS-Princeton 19)
Description: The increased availability of machine-readable text provides a unique opportunity for social scientists, granting us unprecedented access to many aspects of both historical and contemporary social life. This tutorial aims to introduce researchers to text analysis in Python, an open-source programming language. Specifically, the tutorial consists of a conceptual overview of the core analytic challenges of harnessing text data, how to access Twitter data through the new Twitter API v2, pre-processing text data, and a few conceptually accessible methods for quantitatively analyzing text (closed- and open-vocabulary analysis of unigram frequencies). We will walk through a publicly available Google Colab notebook that can be run in one’s browser without the download of any software (coming soon). Example code for using various Twitter API endpoints (assuming one has an API key) will be provided, along with code to scrape some of that same data from a public GitHub repository (and does not require an API key).
Open to: 45 registered participants
Register: https://forms.gle/2uWTZ4A6AAjobkrt5
### Panel discussion on the non-academic job market in computational social science
Time: Wednesday, June 23, 2021. 12-1pm EDT
Speakers: TBA
Moderator: [Chris Bail](https://www.chrisbail.net/) (SICSS-Princeton 17, 19, 21, SICSS-Duke 18, 20)
Description: Computational social science leads to a wide range of interdisciplinary job opportunities outside academia. These panelists will share their experiences in industry settings and will offer thoughts about how an academic research program in the field could lead to a variety of fulfilling careers.
Open to: Unlimited registered participants
Register: https://forms.gle/ixdR3wC4WzRRwpBS7
### Taking Quantitative Description Seriously
Time: Thursday, June 24, 2021. 1-2pm EDT
Speakers: Andy Guess (Assistant Professor of Politics and Public Affairs at Princeton), Eszter Hargittai (Professor of Communication and Media Research at the University of Zurich), and Jen Pan (Assistant Professor of Communication, Political Science and Sociology at Stanford University)
Moderator: Kevin Munger (Assistant Professor of Political Science and Social Data Analytics at Penn State)
Description: We introduce the rationale for a new peer-reviewed scholarly journal, the Journal of Quantitative Description: Digital Media. The journal is intended to create a new venue for research on digital media and address several deficiencies in the current social science publishing landscape. First, descriptive research is undersupplied and undervalued. Second, research questions too often only reflect dominant theories and received wisdom. Third, journals are constrained by unnecessary boundaries defined by discipline, geography, and length. Fourth, peer review is inefficient and unnecessarily burdensome for both referees and authors. We outline the journal’s scope and structure, which is open access, fee-free and relies on a Letter of Inquiry (LOI) model. Quantitative description can appeal to social scientists of all stripes and is a crucial methodology for understanding the continuing evolution of digital media and its relationship to important questions of interest to computational social scientists.
Open to: Unlimited registered participants
Register: https://forms.gle/tRF7ttu4RoQKxfAJ7
### Creating your own virtual lab experiment with Empirica
Time: Friday, June 25, 2021. 9am-1pm EDT
Speakers: Abdullah Almaatouq (MIT Sloan, Empirica founder & developer), Joshua Becker (UCL School of Management, tutorial author), and Sam Dupret (UCL School of Management, tutorial author)
Description: This is a self-guided, do-it-yourself workshop that will enable you to create virtual lab experiments with Empirica (https://empirica.ly/). Empirica is an open-source framework that makes creating virtual lab experiments more fun and less painful. During this event, participants will first watch a set of introductory videos (https://youtube.com/playlist?list=PLPQelvUwyVgiawBDk3Sp74QMfL8RPgORW) (about 10 mins) that provide a conceptual overview. Participants will then proceed through a written tutorial (https://docs.empirica.ly/guides/tutorial-your-first-experiment) that will walk them step-by-step through building a multi-player experiment with chatrooms and automated bots. Upon completing the tutorial, participants will have created an experiment that they can further customize and that is ready to deploy to real research participants. Faculty members with extensive experience using Empirica for research—and other workshop participants—will be available in the Empirica Slack during the workshop period to help participants through the tutorial and answer more general questions, both about Empirica and related topics like subject recruitment. Outside the workshop period, the Empirica Slack remains available for general discussion and questions both with the faculty and other community members.
Expected programming background: Empirica is a platform built on ReactJS, but participants do not need to know javascript to complete the tutorial. The tutorial is designed to be self-sufficient for anyone with strong coding skills who can learn on the go. Knowledge of basic HTML is helpful.
Expected computing environment: While Empirica can run on Windows, we strongly recommend a Linux/MacOS terminal for ease-of-use and these will be made available upon request.
References:
Empirica: a virtual lab for high-throughput macro-level experiments: https://link.springer.com/article/10.3758/s13428-020-01535-9
Empirica tutorial: Your First Experiment https://docs.empirica.ly/guides/tutorial-your-first-experiment
Open to: Unlimited registered participants
Register: https://forms.gle/QDgPF25g8P5VJ6te7
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