Spring 2019: CITS Research Computing Skills Workshops
(Watch for registration information in your email)
The Center for Information Technology and Society, with UCSB Library’s Interdisciplinary Research Collaboratory, are offering workshops to CITS students and faculty to broaden their technical knowledge. The CITS/IT&S workshops will focus on Big Data, Social Network Analysis, and Scraping/ Gathering Data for Social Media Analyses. Workshops are taught by Dr. Ziad Matni and Devin Cornell.
No previous experience with specific software tools is required. However, for those who are unfamiliar with R (for Big Data and for Network Analysis) or Python (for Gathering Data from Social Media), the library Collaboratory is offering CITS priority reservations at its 2-day Software Carpentry Workshops.
|April 11-12: Software Carpentry Using R||May 9-10: Software Carpentry Using Python|
|April 20: Big Data Uses||May 16: Social Network Analysis|
|May 31-June 1: Social Media: Scraping/Gathering Data and Analyses|
2-day Software Carpentry Workshop using R (April 11-12)*
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including command line scripting, version control, data management, and task automation with the R statistical programming language. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
2-day Software Carpentry Workshop using Python (May 9-10)*
Software Carpentry aims to help researchers get their work done in less time and with less pain by teaching them basic research computing skills. This hands-on workshop will cover basic concepts and tools, including command line scripting, version control, data management, and task automation with the Python programming language. Participants will be encouraged to help one another and to apply what they have learned to their own research problems.
*These workshops are targeted at novice users. The only prerequisite is that you can successfully install and configure the software on your own laptop before arriving at the workshop.
Big Data Uses in Social Media Research (April 20) -Created and taught by Dr. Ziad Matni
This 1 day (6-8 hour) workshop explores uses of Big Data (and more generally, Data Science) methods for use with extracting, analyzing, and visualizing social media data in the context of social science and humanities research questions. The workshop covers basic concepts of Big Data and Data Science, including hands-on exercises of data analysis and data visualization utilizing a “Big” data set extracted from one or several social media sources. The goal of the workshop is to give the participant enough of a background to have an appreciable understanding of the role of Big Data and its value, and some techniques involved in analyzing it.
Social Network Analysis (May 16) -Created and taught by Devin Cornell
This one day workshop will cover the practical and theoretical foundations of Social Network Analysis methodologies. The workshop will begin with some fundamental concepts and a basic history of the methodology up to currently active areas of research. Next, we will review both traditional network data collection through surveys and modern tools for collecting digital social media data, and start working hands-on with pre-collected data of both types. We will cover how to use Gephi for visualization and basic analysis, then do more advanced statistical analyses in R. Finally, the workshop will end with an overview of different tools that can be used for network analysis, and how you might apply them to your own research.
Scraping/Gathering Data and Analyses of Social Media (May 31-June 1) -Created and taught by Dr. Ziad Matni
This is 2-day workshop uses the Python programming language, a versatile and very popular data analysis technology. Little or no prior experience with programming is assumed. The workshop will aim at teaching basic use of the Python language features to obtain data from social media, what initial steps can be taken to curate it for analytical use, and how to analyze them in a variety of ways of interest to the social sciences and humanities (e.g., statistical analysis, content analysis, natural language processing, machine learning). Participants who have not been exposed to Python are encouraged to complete the Data Carpentry Workshop Using Python (see above) prior to this workshop.