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Digital Humanities in Practice

From Research Questions to Results

Stephen Osadetz, Cole Crawford, and Christine Fernsebner Eslao

From the printing press to the typewriter, there is a long history of scholars adapting to new technologies. In the last forty or fifty years, the most significant advance has been the digitization of books. We now have whole libraries—centuries of history, literature, and philosophy—available instantaneously. This new access is a wonderful benefit, but it can also be overwhelming. If you have hundreds of thousands of books available to you in an instant, where do you even start? With a bit of elementary code, you can study all of these books at once, and derive new sorts of insights.

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From the printing press to the typewriter, there is a long history of scholars adapting to new technologies. In the last forty or fifty years, the most significant advance has been the digitization of books. We now have whole libraries—centuries of history, literature, and philosophy—available instantaneously. This new access is a wonderful benefit, but it can also be overwhelming. If you have hundreds of thousands of books available to you in an instant, where do you even start? With a bit of elementary code, you can study all of these books at once, and derive new sorts of insights.

Computation is changing the very nature of how we do research in the humanities. Tools from data science can help you to explore the record of human culture in ways that just wouldn’t have been possible before. You’re more likely to reach out to others, to work across disciplines, and to assemble teams. Whether you're a student wanting to expand your skillset, a librarian supporting new modes of research, or a journalist who has just received a massive cache of leaked e-mails, this course will show you how to draw insights from thousands of documents at once. You will learn how, with a few simple lines of code, to make use of the metadata—the information about our objects of study—to zero in on what matters most, and visualize your results so that you can understand them at a glance.

In this course, you’ll work on building parts of a search engine, one tailor-made to the needs of academic research. Along the way, you'll learn the fundamentals of text analysis: a set of techniques for manipulating the written word that stand at the core of the digital humanities.

By the end of the course, you will be able to apply what you learn to what interests you most, be it contemporary speeches, journalism, caselaw, and even art objects. This course will analyze pieces of 18th-century literature, showing you how these methods can be applied to philosophical works, religious texts, political and historical records – material from across the spectrum of humanistic inquiry.

Combine your traditional research skills with data science to find answers you never might have expected.

What's inside

Learning objectives

  • Understand which digital methods are most suitable to meaningfully analyze large databases of text
  • Identify the resources needed to complete complex digital projects and learn about their possible limitations
  • Download existing datasets and create new ones by scraping websites and using apis
  • Enrich metadata and tag text to optimize the results of your analysis
  • Analyze thousands of books with digital methods such as topic modeling, vector models, and concept search
  • Test your knowledge by writing and editing code in python, and use these skills to explore new methods of search
  • By the end of this course, learners will:

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Explores text analysis, which is an essential tool for digital humanities research
Taught by instructors who are recognized for their work in digital humanities
Develops research skills in data science, which is highly relevant to academic research
Provides hands-on experience in building a search engine, which is a valuable skill for researchers
Suitable for learners with a variety of backgrounds, including students, librarians, and journalists
Requires some prior programming experience, which may be a barrier for some learners

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Career center

Learners who complete Digital Humanities in Practice: From Research Questions to Results will develop knowledge and skills that may be useful to these careers:
Data Scientist
Data Scientists study the vast amounts of data generated by modern technology to extract actionable insights. They combine domain expertise with strong quantitative, analytical, and programming abilities. This course helps build a foundation in these areas by teaching basic programming, data analysis, and visualization techniques. Furthermore, it provides hands-on experience with real-world datasets, preparing you for the challenges of working with large and complex data in the field.
Machine Learning Engineer
Machine Learning Engineers design, build, and maintain machine learning models to solve real-world problems. This course helps build a foundation in machine learning, data analysis, and programming, which are essential skills for Machine Learning Engineers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex data in the field.
Research Scientist
Research Scientists conduct scientific research to advance knowledge and develop new technologies. This course helps build a foundation in research methods, data analysis, and programming, which are essential skills for Research Scientists. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of conducting research in the field.
Software Engineer
Software Engineers apply engineering principles to the design, construction, deployment, and maintenance of software systems. This course helps build a strong foundation in programming, data structures, and algorithms, which are essential skills for Software Engineers. Additionally, it provides experience working with real-world datasets and using version control systems, preparing you for the collaborative development environment of software engineering teams.
Data Analyst
Data Analysts collect, clean, and analyze data to extract actionable insights for businesses. This course helps build a strong foundation in data analysis, statistics, and programming, which are essential skills for Data Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex data in the field.
Data Engineer
Data Engineers design, build, and maintain data pipelines to ensure that data is available, reliable, and secure for analysis. This course helps build a strong foundation in data engineering, databases, and programming, which are essential skills for Data Engineers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex data in the field.
Quantitative Analyst
Quantitative Analysts use mathematical and statistical models to analyze data and make predictions in the financial industry. This course helps build a strong foundation in data analysis, statistics, and programming, which are essential skills for Quantitative Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with large and complex financial data.
Financial Analyst
Financial Analysts provide analysis and recommendations on investments and financial markets. This course helps build a foundation in finance, data analysis, and programming, which are essential skills for Financial Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with financial data in the field.
Product Manager
Product Managers are responsible for the development and launch of new products and features. This course helps build a foundation in product management, data analysis, and programming, which are essential skills for Product Managers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of managing products in the field.
Consultant
Consultants provide advice to businesses on how to improve their performance. This course helps build a foundation in business analysis, data analysis, and programming, which are essential skills for Consultants. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of consulting in the field.
UX Researcher
UX Researchers study how users interact with products and services to improve the user experience. This course helps build a foundation in research methods, data analysis, and programming, which are essential skills for UX Researchers. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of conducting user research in the field.
Operations Research Analyst
Operations Research Analysts use mathematical and analytical techniques to solve complex problems in business and industry. This course helps build a strong foundation in operations research, data analysis, and programming, which are essential skills for Operations Research Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.
Statistician
Statisticians collect, analyze, and interpret data to provide insights for decision-making. This course helps build a strong foundation in statistics, data analysis, and programming, which are essential skills for Statisticians. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.
Business Analyst
Business Analysts analyze business processes and data to identify opportunities for improvement. This course helps build a foundation in business analysis, data analysis, and programming, which are essential skills for Business Analysts. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.
Actuary
Actuaries use mathematical and statistical techniques to assess risk and uncertainty in the insurance and financial industries. This course helps build a strong foundation in mathematics, statistics, and programming, which are essential skills for Actuaries. Additionally, it provides experience working with real-world datasets and using industry-standard software, preparing you for the challenges of working with data in the field.

Reading list

We've selected 11 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Digital Humanities in Practice: From Research Questions to Results.
Provides a comprehensive introduction to text analysis using Python. It covers the fundamentals of text analysis, including data preprocessing, text mining, and natural language processing. It also includes practical examples and exercises to help you apply your knowledge to real-world projects.
This handbook provides a comprehensive overview of the field of digital humanities. It covers the history of digital humanities, the different methods and tools used in digital humanities research, and the ethical and social implications of digital humanities work.
This reader provides a collection of essays on the field of digital humanities. It covers a variety of topics, including the history of digital humanities, the different methods and tools used in digital humanities research, and the ethical and social implications of digital humanities work.
This online journal provides a collection of tutorials and articles on the use of programming in historical research. It covers a variety of topics, including data analysis, visualization, and text mining.
This online journal provides a collection of articles on the field of digital humanities. It covers a variety of topics, including the history of digital humanities, the different methods and tools used in digital humanities research, and the ethical and social implications of digital humanities work.
This online journal provides a collection of articles on the field of digital humanities. It covers a variety of topics, including the history of digital humanities, the different methods and tools used in digital humanities research, and the ethical and social implications of digital humanities work.
This online platform provides a collection of resources for digital humanities research. It includes a variety of materials, such as datasets, tools, and tutorials.
This online journal provides a collection of articles on the field of digital scholarship. It covers a variety of topics, including the use of digital technologies in teaching and research.
This journal provides a collection of articles on the field of history. It includes a variety of topics, including the use of digital technologies in historical research.
This journal provides a collection of articles on the field of information science and technology. It includes a variety of topics, including the use of digital technologies in information management and retrieval.
This journal provides a collection of articles on the field of digital humanities. It includes a variety of topics, including the history of digital humanities, the different methods and tools used in digital humanities research, and the ethical and social implications of digital humanities work.

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