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Digital Humanities Specialist

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March 29, 2024 Updated April 14, 2025 17 minute read

A Career Guide to Becoming a Digital Humanities Specialist

Digital Humanities, often abbreviated as DH, represents a dynamic and evolving field where traditional humanities disciplines intersect with computing and digital technologies. A Digital Humanities Specialist leverages these technologies to explore, analyze, interpret, and present human culture in new ways. This involves using digital tools and methods to ask new questions of historical texts, artworks, cultural data, and more, essentially acting as a bridge between the worlds of technology and the arts, history, literature, philosophy, and other humanities fields.

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Salaries for Digital Humanities Specialist

City
Median
New York
$137,000
San Francisco
$125,000
Seattle
$123,000
See all salaries
City
Median
New York
$137,000
San Francisco
$125,000
Seattle
$123,000
Austin
$92,000
Toronto
$120,000
London
£45,000
Paris
€61,000
Berlin
€64,000
Tel Aviv
₪56,000
Singapore
S$84,000
Beijing
¥170,000
Shanghai
¥120,000
Shenzhen
¥344,000
Bengalaru
₹638,000
Delhi
₹358,000
Bars indicate relevance. All salaries presented are estimates. Completion of this course does not guarantee or imply job placement or career outcomes.

Reading list

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Classic in the field of network science, covering the mathematical and statistical foundations of network analysis. It provides a deep understanding of network properties, dynamics, and algorithms.
Provides an overview of complex networks, covering theoretical foundations, models, and applications in various domains. It can serve as a comprehensive introduction to the topic for researchers and students alike.
Provides a comprehensive overview of network science, including both theoretical foundations and practical applications. It covers various aspects of network analysis, including network structure, dynamics, and resilience.
This Spanish translation of the book "Complex Networks: Principles, Models and Applications" provides a comprehensive overview of complex networks, covering both theoretical foundations and applications in various domains. It valuable resource for Spanish-speaking readers.
Delves into the mathematical and computational aspects of complex networks, exploring topics such as network structure, dynamics, and resilience. It provides a solid foundation for understanding and modeling complex systems.
Focuses on using Python for social network analysis, covering data collection, preprocessing, visualization, and various analysis techniques. It provides practical examples and code snippets that can be applied to Gephi workflows.
Focuses on social network analysis, covering theoretical concepts, data collection methods, and various analysis techniques. It provides insights into the structure and dynamics of social networks.
While not specifically focused on Gephi, this book provides a comprehensive overview of data visualization techniques and best practices, which can be valuable for understanding the visualization aspects of network analysis.
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