Elevate your computing and data-related skills through workshop sessions on data processing, replication, and qualitative analysis.
Workshops are open to the Cornell community!
CCSS workshops are held in person at 291 Clark Hall and via Zoom. Get Directions.
Message socialsciences@cornell.edu workshop-related questions.
Web Scraping in Python | Sept 4 | 1:00pm - 1:50pm
Description:
Web scraping is the process of extracting text and numeric data from a webpage using software. Join this workshop to discover how Python, the most popular software for web scraping, makes it easy to extract the data you need from a webpage and store it in a data frame.
Learning Objectives:
- Identify and extract HTML data from a webpage with the inspect feature.
- Use Python’s BeautifulSoup library to extract data and store it in a data frame.
- Demonstrate how Python’s Selenium package allows for advanced data extraction using website interactions such as mouse clicks, filling out forms, etc.
- Understand HTML format, including tags, attributes, etc.
- Distinguish between extracting data through web scraping vs APIs.
Helpful Information:
- Install python (Python, jupyter notebook, google colab)
Python web scraping packages (BeautifulSoup, Selenium)
HTML tags, HTML attributes, HTML tags vs elements vs attributes, HTML attributes list
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Jacob Grippin
Extracting the American Community Survey (ACS) Housing and Population Data | Sept 10 | 11:10am - 12:00pm
Description:
The American Community Survey (ACS) is an annual survey conducted by the U.S. Census Bureau that gathers housing and population data for the United States. Researchers can access the ACS data through the IPUMS and Census Bureau websites. Workshop participants will gain hands-on experience using the tools on the IPUMS and Census Bureau websites to find and extract the ACS data needed for their research.
Learning Objectives:
- Create a custom dataset on the IPUMS website by selecting housing and population variables.
Import custom dataset into a programming language (Stata, SAS, R) for analysis.
Find and create summary tables using ACS data on the data.census.gov website.
Filter ACS data by county, year, household size, household income, etc.
- Review popular articles written by Cornell authors that include the ACS data.
Helpful Information
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Samantha De Leon Sautu
Research Opportunities at the Cornell FSRDC | Oct 18 | 1:40pm - 3:00pm
Description:
The Cornell Federal Statistical Research Data Center (FSRDC) provides access to confidential federal data from several agencies, including the U.S. Census Bureau. The Cornell FSRDC administrator, Nichole Szembrot, will give an overview of the available data and proposal process. This workshop is recommended for faculty and Ph.D. students.
Learning Objectives:
- Understand the advantages of working with confidential data compared to public-use data
- Become familiar with the data available through the Cornell FSRDC
- Understand the process of applying for access to confidential data
Helpful Information
Instructor: Nichole Szembrot
Psychophysiological Measures for Social Research | Oct 29 | 11:10am - 12:00pm
Description:
This workshop will introduce participants to psychophysiological measures, the physiological correlates of psychological processes. It will describe common psychophysiological measures and their collection methods, analytical processes, and interpretation.
Learning Objectives:
Examine psychophysiology as a field of study and pupil diameter, skin conductance, and heart rate monitoring as psychophysiological measures.
Instructor: Samantha De Leon Sautu
Web Scraping in R | Nov 5 | 1:00pm - 1:50pm
Description:
Web scraping is the process of extracting text and numeric data from a webpage using software like R. Join this workshop to discover how R makes it easy to extract the data you need from a webpage and store it in a data frame.
Learning Objectives:
Identify and extract HTML data from a webpage with the inspect feature.
Use R’s Rvest package to extract data and store it in a data frame.
Demonstrate how R’s RSelenium package allows for advanced data extraction using website interactions such as mouse clicks, filling out forms, etc.
Understand HTML format, including tags, attributes, etc.
Distinguish between extracting data through web scraping vs APIs.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Jacob Grippin
Health Biomarkers for Social Research | Nov 12 | 11:10am - 12:00pm
Description:
This workshop, geared toward social scientists, will explore the biomarker data hidden in our bodily fluids and the best methods for collecting and analyzing that data. After establishing a conceptual framework, participants will explore biomarker data in existing databases and the methods for collecting their own.
Learning Objectives:
- Define biomarkers and classify them by biological system.
- Explore biomarkers’ predictive, diagnostic and provisional values and their relevance to social science research.
- Identify common methods for collecting biomarkers in bodily fluids.
- Evaluate the usefulness of biomarker data based on research question and design.
Instructor: Samantha De Leon Sautu
Using Stata to Create Data Visualizations | Sept 18 | 11:00am - 11:50am
Description:
In this workshop series we will use Stata to generate tables and figures directly from statistical output. You will never have to cut-and-paste results, making published works easily replicable. You will learn how to generate tables for word or LaTex output formats. Preparing your code and results so they can be comfortably uploaded to a repository. There are no pre-requisites, though some familiarity with Stata will be helpful.
*Example of Multiple Regressions table
*Figure of Violin Plot to show distribution of data
Learning Objectives:
Increase awareness of the need for reproducible data visualizations.
- Use Stata code to create and save reproducible tables and figures that require no additional formatting.
- Apply formatting code to improve the appearance of tables and figures.
- Learn how to maintain code for later reproducibility.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Jacob Grippin
Using R to Create Data Visualizations | Sept 24 | 11:10am - 12:00pm
Description:
In this workshop series we will use R to generate tables and figures directly from statistical output. You will never have to cut-and-paste results, making published works easily replicable. You will learn how to generate tables for word or LaTex output formats. Preparing your code and results so they can be comfortably uploaded to a repository. There are no pre-requisites, though some familiarity with R will be helpful.
*Example of multiple regressions table
*Figure of Density Plot split by group
Learning Objectives:
- Increase awareness of the need for reproducible data visualizations.
- Use R code to create and save reproducible tables and figures that require no additional formatting.
- Apply formatting code to improve the appearance of tables and figures.
- Learn how to maintain code for later reproducibility.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Samantha De Leon Sautu
Using Stata to Display Advanced Formatting Features in Data Visualizations | Sept 25 | 11:00am - 11:50am
Description:
This workshop is a continuation of the previous one 'Using Stata to Create Data Visualizations'. In this workshop series we will use Stata to generate tables and figures directly from statistical output. You will never have to cut-and-paste results, making published works easily replicable. You will learn how to generate tables for word or LaTex output formats. Preparing your code and results so they can be comfortably uploaded to a repository. There are no pre-requisites, though some familiarity with Stata will be helpful.
*Example of full and restricted Regression models
*Figure of Bubble Chart split by type
Learning Objectives:
Use Stata code to create and save reproducible data visualizations.
- Apply advanced formatting code so data visualizations display features like data markers, color mapping, significance, and legends.
Embed advanced data visualizations into a manuscript.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Jacob Grippin
Using R to Display Advanced Formatting Features in Data Visualizations | Oct 8 | 11:10am - 12:00pm
Description:
This workshop is a continuation of the previous one 'Using R to Create Data Visualizations'. In this workshop series we will use R to generate tables and figures directly from statistical output. You will never have to cut-and-paste results, making published works easily replicable. You will learn how to generate tables for word or LaTex output formats. Preparing your code and results so they can be comfortably uploaded to a repository. There are no pre-requisites, though some familiarity with R will be helpful.
*Example of Descriptive Statistics Table
*Figure of Correlation Plot
Learning Objectives:
- Use R code to create and save reproducible data visualizations.
- Apply advanced formatting code so data visualizations display features like data markers, color mapping, significance, and legends.
Embed advanced data visualizations into a manuscript.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Samantha De Leon Sautu
Preparing Qualitative Data for Analysis | Sept 5 | 12:00pm - 12:50pm
Description:
Before you can analyze your qualitative data, you need to organize it! This workshop will share techniques to help attendees organize their qualitative data and format their transcripts so they’re ready for analysis using software like Atlas.ti and MaxQDA. Attendees will also leave the workshop with an understanding of what information to collect from their respondents and the ideal timeline for preparing and analyzing their qualitative data using qualitative software.
Learning Objectives:
- Identify types of files most often used in qualitative analysis.
- Format transcripts and structure folders for the best organization of qualitative data.
Create folders and sub-folders based on data type.
Set up folders for project teams.
Establish the importance of preparing and analyzing qualitative data after the first interview.
- Discover computing resources at Cornell that are suited for qualitative analysis.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Florio Arguillas
Coding and Summarizing Qualitative Data with MaxQDA | Sept 12 | 12:00pm - 1:15pm
Description:
MaxQDA is a popular qualitative analysis software. This workshop covers importing qualitative data files into MaxQDA and using the software to identify themes and trends within text. It will also take participants through the steps of using MaxQDA’s AI Assist to summarize and explore their qualitative data.
Learning Objectives:
- Import qualitative files including transcripts and recordings into MaxQDA.
- Create and apply codes in MaxQDA to identified themes.
Generate reports for specific coded segments and query results.
Use MaxQDA’s AI Assist to summarize coded segments and documents, identify themes, and utilize suggested codes.
- Properly save MaxQDA projects.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Florio Arguillas
Exploring Mixed Methods and Visualization Tools in MaxQDA | Sept 19 | 12:00pm - 12:50pm
Description:
MaxQDA is a popular qualitative analysis software. This workshop will explore the various tools in MAXQDA that can analyze and visualize qualitative data.
Learning Objectives:
- Discover mixed methods tools in MaxQDA for analyzing qualitative data, including cross tabulations and quantitizing (transforming codes into variables).
Visualize qualitative data using MaxMaps, Code Matrix Browser, Code Relation Browser, Word Cloud, and more.
- Create worksheets in MaxQDA’s Questions-Theories-Themes (QTT) workspace to organize results by research question, theory, or theme.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Florio Arguillas
Coding and Summarizing Qualitative Data with Atlas.ti | Sept 30 | 12:00pm - 12:50pm
Description:
Atlas.ti is a popular qualitative analysis software. This workshop covers importing qualitative data files into Atlas.ti and using the software to identify themes and trends within text. It will also take participants through the steps of using Atlas.ti’s AI features to summarize and explore their qualitative data.
Learning Objectives:
- Import qualitative files including transcripts, interviews, audio and video recordings into Atlas.ti.
- Create and apply codes in Atlas.ti to identify themes and trends within text.
Create folders and sub-folders to organize coded segments by theme.
Use Atlas.ti’s AI features to summarize coded segments and documents, identify themes, and utilize suggested codes.
- Properly save Atlas.ti projects.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Jacob Grippin
Qualitative Data Analysis and Visualizations with Atlas.ti | Oct 7 | 12:00pm - 12:50pm
Description:
Atlas.ti is a popular qualitative analysis software. This workshop will explore the various tools in Atlas.ti that can analyze and visualize qualitative data.
Learning Objectives:
- Use the Query Tool, Code Co-Occurrence Tool, and Code Document Table to analyze and visualize qualitative data.
Generate reports for specific coded segments and query results.
Perform sentiment analysis to categorize text segments by positive, negative, and neutral emotions.
Discuss how Atlas.ti can facilitate collaboration in a project team.
Helpful Information:
To follow along hands-on during the workshop and/or use the software after the workshop: Request access to CCSS Cloud Computing resources
Instructor: Jacob Grippin