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Below are courses taught by NULab core faculty members in digital humanities and computational social science.

Art – Design

  • ARTG 5100 – Information Design Studio 1: Principles

    Explores the theories and practices of information design through studio projects. Investigates visual systems and information structures such as maps, timelines, charts, and diagrams. Emphasizes the creative process of organizing, visualizing, and communicating data by seeking to make complex information easier to understand and use.

  • ARTG 5120 – Research Methods for Design

    Examines qualitative and quantitative research methods pertinent to design. Through discussion and writing activities, offers students an opportunity to investigate varied inquiry toward the development of researchable questions, argument formation, and assessment methodologies.

  • ARTG 6100 – Information Design Studio 2: Dynamic Mapping and Models

    Continues the exploration of data representations in a variety of media. Focuses on interactive and time-based techniques. Emphasizes computational methods of data collection, manipulation, and encoding.

Business Administration

  • BUSN 6320 – Business Analytics Fundamentals

    Introduces the key concepts of data science and data analytics as applied to solving data-centered business problems. Emphasizes principles and methods covering the process from envisioning the problem; applying data science techniques; deploying results; and improving financial performance, strategic management, and operational efficiency. Includes an introduction to data-analytic thinking, application of data science solutions to business problems, and some fundamental data science tools for data analysis.

Computer Science

  • CS 6120 – Natural Language Processing

    Provides an introduction to the computational modeling of human language, the ongoing effort to create computer programs that can communicate with people in natural language, and current applications of the natural language field, such as automated document classification, intelligent query processing, and information extraction. Topics include computational models of grammar and automatic parsing, statistical language models and the analysis of large text corpuses, natural language semantics and programs that understand language, models of discourse structure, and language use by intelligent agents.

  • CS 6200 – Information Retrieval

    Provides an introduction to information retrieval systems and different approaches to information retrieval. Topics covered include evaluation of information retrieval systems; retrieval, language, and indexing models; file organization; compression; relevance feedback; clustering; distributed retrieval and metasearch; probabilistic approaches to information retrieval; Web retrieval; filtering, collaborative filtering, and recommendation systems; cross-language IR; multimedia IR; and machine learning for information retrieval.


  • ENGL 1450 – Reading and Writing in the Digital Age

    Grapples with the long and sometimes tumultuous relationship between literature—including fiction, poetry, film, and video games—and new media technologies. Offers students opportunities to historicize and engage the social and literary upheavals of our own technological moment through reading, discussion, writing projects, and practicums that seek to develop skills for analyzing the data and metadata of texts through both qualitative and quantitative methods.

  • ENGL 2150 – Literature and Digital Diversity

    Focuses on the use of digital methods to analyze and archive literary texts, emphasizing issues of diversity and inclusion. Covers three main areas: text encoding, textual analysis, and archive construction. Considers literary texts and corpora, including works by well-known authors such as Shakespeare, together with collections by marginalized writers, including slave narratives and writings by early modern women. Offers students an opportunity to explore what counts as literature and how computers, databases, and analytical tools give substance to concepts of aesthetic, cultural, and intellectual value as inflected by race and gender.

  • ENGL 3340 – Technologies of Text

    Examines innovations that have reshaped how humans share information, e.g., the alphabet, the book, the printing press, the postal system, the computer. Focuses on debates over privacy, memory, intellectual property, and textual authority that have historically accompanied the rise of new media forms and genres. Offers students an opportunity to gain skills for working with texts using the rapidly changing tools of the present, e.g., geographic information systems, data mining, textual analysis.

  • ENGL 7370 – Introduction to Digital Humanities

    Offers a critical orientation to the tools, methods, and intellectual history of the digital humanities (DH). Explores key questions such as what debates are (re)shaping DH in this moment; what central theories lead humanities scholars to experiment with computational, geospatial, and network methodologies; how visualization can illuminate literature, history, writing, and other humanities subjects; and how new modes of research and publication might influence our teaching. Balances theory and praxis: Successful students come away with a well-grounded understanding of the DH field and a set of foundational skills to support their future research.

  • ENGL 7380 – Topics in Digital Humanities: Queer Digital Curation

    Developed at the intersection of theory and practice, this course will introduce students to queer theory in the context of digital curation. Digital curation refers to the selection, organization, preservation, and representation of digital resources; it is largely focused on efficiency, structure, and use. Queer theory, on the other hand, critically investigates cultural normativities related to sex, sexuality, and gender; it often values disruption, deconstruction, and play. A queer approach to digital curation, then, will allow us to unpack the invisible norms of digital environments as we think through the effects of digital tools, particularly those used for social justice purposes. There will be a hands-on unit of this course; however, prior knowledge of LGBTQ+ issues or the digital humanities is not expected––all students are welcome in this course.


  • HIST 7370 – Texts, Maps, and Networks: Readings and Methods for Digital History

    Introduces the methods and practice of history in a digital age. Offers students an opportunity to see the wide variety of work being done computationally by historians and other humanists today and to obtain the background to be creative producers of new work and critical consumers of existing projects. The rise of computing technology and the Internet has the potential to reshape all parts of historical practice, from curation to research to dissemination. Examines the historian’s craft in three primary domains: the creation of digital sources, the algorithmic transformations that computers can enact on cultural materials like texts, and the new ecologies of publishing and scholarly communication made possible by new media.

Information Science

  • IS 4700 – Social Information Systems

    Analyzes popular social information systems, including online social networks, blogging platforms, recommendation engines, and content sharing sites. Studies the objectives, user interaction modes, policies, and design issues for social information systems. Introduces relevant theories, both computational and sociological, that model the behavior of social networks and their users. Offers students an opportunity to learn to apply such models, both theoretically and by analyzing real-world interaction data from social information systems, to answer questions such as: What causes users to form links? What mechanisms work best for encouraging collaboration? How does information spread through cyberspace? How can security and privacy goals be achieved?

Interdisciplinary Studies in Social Sciences and Humanities

  • INSH 1500 – Digital Methods for Social Sciences and Humanities

    Introduces programming skills and computational methods through application to topics in the social sciences and humanities. Methods include computational text analysis, network analysis, mapping software and analysis, computational approaches to data, big data, and/or social simulation. Offers students an opportunity to develop an understanding of the use and significance of computational tools for social sciences and humanities. No previous programming experience required.

  • INSH 2102 – Bostonography: The City through Data, Texts, Maps, and Networks

    Uses Boston as a case study for integrating computational methods with the social sciences and humanities to provide new insights into major cultural, historical, and societal questions as they relate to and extend beyond the city of Boston. Through lectures, discussions, and labs, the course examines a variety of data sets that measure geographic, historical, literary, political, civic, and institutional landscapes. Offers students an opportunity to combine analytical tools, such as geospatial mapping, data visualization, and network science, with readings, hands-on class activities, and museum or site visits, enabling a comprehensive view of complex cultural and social phenomena.

  • INSH 5301 – Introduction to Computational Statistics

    Introduces the fundamental techniques of quantitative data analysis, ranging from foundational skills—such as data description and visualization, probability, and statistics—to the workhorse of data analysis and regression, to more advanced topics—such as machine learning and networks. Emphasizes real-world data and applications using the R statistical computing language. Analyzing and understanding complex data has become an essential component of numerous fields: business and economics, health and medicine, marketing, public policy, computer science, engineering, and many more. Offers students an opportunity to finish the course ready to apply a wide variety of analytic methods to data problems, present their results to nonexperts, and progress to more advanced course work delving into the many topics introduced here.

  • INSH 5602 – Documenting Fieldwork Narratives: Oral History, Ethnography, Archival Practices

    Examines the ethics, politics, and social aspects of three primary areas of interdisciplinary research and knowledge production at the intersection of the social sciences and humanities: oral history, ethnography, and archiving. Offers students an opportunity to learn to conduct oral history, ethnography, and archiving; gain experience collecting and formatting information collected through these qualitative techniques; and be introduced to digital platforms for oral history, ethnography, and archiving. Offers instruction in critiquing examples of how researchers collect and analyze qualitative information. Studies the critical thinking skills necessary to build a research project from the formulation of a research idea through the research design planning process.

  • INSH 6406 – Analyzing Complex Digitized Data

    Introduces cutting-edge ways of structuring and analyzing complex data or digitized text-as-data using the open-source programming language Python. Scholars across multiple disciplines are finding themselves face-to-face with massive amounts of digitized data. In the humanities and social sciences, these data are often in the form of unstructured text and un- or under-structured data. Encourages students to think about novel ways they can apply these techniques to their own data and research questions and to apply the methods in their own research, whether it be in academia or in industry.

  • INSH 7910 – NULab Project Seminar

    Offers students an opportunity to learn and use digital humanities methods with others in groups and across disciplines in the collaborative space of the NULab seminar. May be repeated up to three times.


  • JRNL 6340 – Fundamentals of Digital Journalism

    Offers students an opportunity to learn the fundamentals of digital journalism and to place those skills within the context of a changing media environment. Studies multimedia tools within an intellectual framework—i.e., offers students an opportunity to learn hands-on skills and also to study best practices and theory. May include guest speakers and a consideration of the future of news. Requires students to produce a final project that consists of storytelling across a range of digital platforms.

  • JRNL 6341 – Telling Your Story With Data

    Explores select topics in data journalism and support data-driven storytelling projects of various kinds. Offers students an opportunity to learn how to navigate the often-competing demands of rigorous analysis and accessible narrative and storytelling. Course units are designed to foster moderate technical learning of applications and software, incorporate theories from relevant fields in data visualization and data science, and emphasize storytelling for broad public audiences.

Political Science

  • POLS 7334 – Social Networks

    Offers an overview of the literature on social networks, with literature from political science, sociology, economics, and physics. Analyzes the underlying topology of networks and how we visualize and analyze network data. Key topics include small-world literature and the spread of information and disease. Students who do not meet course prerequisites may seek permission of instructor.

Public Policy and Urban Affairs

  • PPUA 5262 – Big Data for Cities

    Investigates the city and its spatial, social, and economic dynamics through the lens of data and visual analytics. Utilizes large public datasets to develop knowledge about visual methods for analyzing data and communicating results. Offers students an opportunity to develop a critical understanding of data structures, collection methodologies, and their inherent biases.