The Digital Humanities Lab is an inter-institutional research group connecting digital humanities research across the three KNAW HuC institutes. The lab is focused on advancing humanities research through digital methods for which they bring together expertise from humanities, computational linguistics, social science and semantic web. Since its inception, DHLab has worked on automatically extracting information from text archives, improving historical image classification, and mapping online debates.
Cultural AI, Language Technology, Semantic Web
evolution of ideas
cultural ai, natural language processing, text analytics, machine learning, language variation, Dutch
user interfaces, network analysis, spatial humanities, digital hermeneutics, uncertainty, ontologies
literary text modeling, digital scholarly editing, automated collation, textual scholarship, markup, ontologies for text and semantic markup
social media, polarization, combining qualitative and quantitative methodologies, religion, emotion, affect, politics, discourse, affective publics
cultural evolution, folklore, complexity theory, Bayesian statistics
Text Mining, Sentiment Mining, Concept Mining, Emotion Mining, 3d visualisations, ontologies, sensory mining
maritime history, economic history
Text & meaning modeling. Narrative modeling. Automatic inference. Stylometrics.
Literary Studies, Sociology of Art, Stylometry, Name Studies (Onomastics), Translation Studies
(socio-economic) history, semantic web, data modelling, data analysis
Political and Institutional History, International Relations, Migration history, Information History, Editing
Information Retrieval, Recommender Systems, Digital History, Digital Literary Studies, Methodology, Data Science
medieval manuscripts, medieval intellectual history
digital musicology, music encoding, linked data, research data management
Spelling and OCR post-correction, corpus building, Digital Humanities infrastructure development, diachronical Dutch lexica and word embeddings
(Global) Social History; Innovating Methods; Digital Sources; Slavery; Asia; VOC
Literature, Literary culture, Reading, Text analysis, Digital Scholarly Editing, LIWC, and more
Computational musicology, folk song research, modeling of musical style, melody, music information retrieval, music and religion.
social inequality, structured data, Linked Data, multi-level models, replication
spatial humanities, GIS, gazetteers, history, middle ages
Textual variation, witness collation, document modelling, formal languages such as markup languages, knowledge representation, markup semantics, ontologies, machine learning
Religion, Politics, Identity, Social Media, Activism
Folktales, databases, literature (esp. Middle Dutch), classifications, sentiment analysis, stylometrics
Commodity Frontiers, Consumption
Art history, mapping, transmission of ideas, network analysis
Global apple pie investigates the relationship between sugar import and export and recipes as well as opinions on health.
This projects aims to computationally extract job advertisements from the nineteenth century digitized newspapers provided by the Dutch National Library.
The Amsterdam Time Machine is a digital commons for the history of Amsterdam. DHLab is involved in modelling and mapping Amsterdam’s linguistic history together with researchers from the Meertens Institute.