My Computing Skills
Python: Pandas, NLTK, TextBlob, scikit-learn, StatsModel, gensim, matplotlib, BeautifulSoup
R: tm, stm, topicmodels, RTextTools, sna, igraph
Future and Past Events:
- SocInfo 2019 - Program Committee Chair
- Program Committees:
- SocInfo 2020 (senior PC)
- CWSM 2018-Present
- IC2S2 2016-Present
- TheWebConf 2018, 2019
- ICWS 2018
- International Conference on Computational Social Science
- 17-20 July 2020, MIT
- 17-20 July 2019, University of Amsterdam, Netherlands
- 12-15 July 2018, Northwestern University
- 10-13 July 2017, GESIS, Cologne, Germany
- 23-26 June 2016, Northwestern University
- Computational Social Science Summit, 15-17 May 2015, Northwestern University
- Big Cities, Big Data: Big Opportunities for Computational Social Science, 15-16 August 2014, D-Lab, UC Berkeley
Workshops I have taught:
Computer-Assisted Text Analysis:
- The Hitchhiker's Guide to Python
- Neal Caren's tutorials on Python and text analysis
- Justin Grimmer's course on applied text analysis (pdf)
- Rodeo: A Data Science IDE for Python
Women in Tech
I'm passionate about making the tech scene more friendly toward women, and getting more women trained in computational methods. Here are some resources:
On Computational Social Science:
- "Computational social science: Obstacles and Opportunities." David Lazer et al. Science.
- "Data ex Machina: Introduction to Big Data." David Lazer and Jason Radford. Annual Review of Sociology.
- "Big Data. Big Obstacles." Dalton Conley et al., The Chronicle of Higher Education.
- "Computational Social Science: Exciting Progress and Future Directions." Duncan J. Watts, National Academy of Engineering.
- "Computational Social Science." David Lazer et al. Science
- "Is Bigger Always Better?" Eszter Hargittai, The ANNALS of the American Academy of Political and Social Science.