Search Constraints
Search Results
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Dataset
Living with Machines alpha and beta Zooniverse 'accident' task data
Data created through crowdsourcing tasks hosted on the Zooniverse platform. Members of the public were asked to look at a selection of articles from 19th century newspapers that mentioned machines and decide if they described an industrial accident. A further task asked participants to transcribe personal, organisational and place names...Zooniverse volunteers
crowdsourcing, digital history, citizen history, Living with Machines, newspapers, and digital humanities
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Dataset
The Newspaper Press Directory (1881-1920)
Newspaper directories produced and published annually in contemporary 19th Britain by advertising agent Charles Mitchell. Newspapers listed primarily listed in alphabetical order of the town the newspaper where the title was published. Information for each title included: features connected with the district such as population and trade; principal towns in...C. Mitchell and Co. ; British Library
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Dataset
The Newspaper Press Directory (1846-1880)
Newspaper directories produced and published annually in contemporary 19th Britain by advertising agent Charles Mitchell. Newspapers listed primarily listed in alphabetical order of the town the newspaper where the title was published. Information for each title included: features connected with the district such as population and trade; principal towns in...C. Mitchell and Co. ; British Library
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Dataset
The Newspaper Press Directory (1846-1920) - enriched and structured version
Mitchell's Newspaper Press Directories contained an almost complete list of newspapers published in England, Wales, Scotland and Ireland. It was published regularly from 1846 onwards and provided a detailed description of the newspaper landscape over time. This version contains a structured, tabular representation of the directories (as CSV or Excel...C. Mitchell and Co. ; British Library
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Software
Living-with-machines/MapReader: End of LwM
This release marks the end of the current funding for MapReader during the Living with Machines (LwM) project. @kasra-hosseini @andrewphilipsmith @rwood-97 @kmcdono2 @dcsw2 @kallewesterling @kasparvonbeelenHosseini, Kasra ; Wood, Rosie ; Smith, Andy ; McDonough, Katie ; Wilson, Daniel C. S. …
computer vision and maps
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Dataset
Diachronic word embeddings from 19th-century newspapers digitised by the British Library (1800-1919)
Word vectors related to the paper "Machines in the media: semantic change in the lexicon of mechanization in 19th-century British newspapers" by Nilo Pedrazzini and Barbara McGillivray (2022). The embeddings were trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and specific parameters. The embeddings are divided into...Pedrazzini, Nilo ; McGillivray, Barbara
historical semantics, word-vectors, late-modern-english, newspapers, diachronic-embeddings, and word2vec
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Dataset
Dataset for Toponym Resolution in Nineteenth-Century English Newspapers
We present a new dataset (version 2) for the task of toponym resolution in digitised historical newspapers in English. It consists of 455 annotated articles from newspapers based in four different locations in England (Manchester, Ashton-under-Lyne, Poole and Dorchester), published between 1780 and 1870. The articles have been manually annotated...Coll Ardanuy, Mariona ; Beavan, David ; Beelen, Kaspar ; Hosseini, Kasra ; Lawrence, Jon …
nineteenth-century English, dataset, newspapers, toponym resolution, and geographic information retrieval
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Dataset
Living with Machines Zooniverse Participant Survey
Summary results from a survey of contributors to Living with Machines Zooniverse crowdsourcing projects. Responses were received between 24 May and 13 June 2022. We designed the survey so that we could align our reporting with two other audience / participant research groups. Firstly, we used the demographic categories that...British Library
online volunteering, digital participation, citizen science, citizen history, questionnaire, crowdsourcing, survey, and audience research
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Dataset
Decade-level Word2Vec models from automatically transcribed 19th-century newspapers digitised by the British Library (1800-1919)
Word embeddings trained on a 4.2-billion-word corpus of 19th-century British newspapers using Word2Vec and specific parameters. The embeddings are divided into periods of ten years each. Unlike those in this repository, these were not aligned and OCR errors skimmed from the vocabulary. See related GitHub repository for the full documentation:...Pedrazzini, Nilo
historical semantics, British newspapers, word embeddings, word vectors, word2vec, and Late Modern English
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Dataset
Diachronic and diatopic word embeddings from newspapers digitised by the British Library (1830-1889): North and South England
Diachronic word embeddings (decade-level) trained with Word2Vec (via Gensim) on different geographic subcorpora of the Heritage Made Digital British and the Living with Machines historical newspaper collections: - North England (north.zip) - South England (south.zip) At the moment, for each subcorpus, Word2Vec models are available for each decade in the...Pedrazzini, Nilo ; McGillivray, Barbara
historical semantics, diachronic embeddings, late modern English, word embeddings, word vectors, word2vec, and diatopic embeddings
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Conference paper (published)
Resolving places, past and present: toponym resolution in historical British newspapers using multiple resources
Newspapers and their metadata are richly geographical, not only in their distribution but also their content. Attending to these spatial features is a prerequisite in newspaper research. Following other projects to have geoparsed place names in newspapers, we describe our approach to linking historical geospatial information in text to real-world...Coll Ardanuy, Mariona ; McDonough, Katherine ; Krause, Amrey ; Wilson, Daniel C.S. ; Hosseini, Kasra …
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Dataset
Ordnance Survey Old / First series England and Wales 1:63360 (georeferenced sheet images)
Map sheet images for the Ordnance Survey Old Series / First Series England and Wales 1:63360, georeferenced and cropped at the neatlike (can be viewed together as a seamless composite). Geotiff format. The original (ungeoreferenced) sheet images can be found at: https://commons.wikimedia.org/wiki/Category:Ordnance_Survey_Old/First_series_England_and_Wales_1:63360_(full_sheets). The sheets were georeferenced by relating the sheet...Vane, Olivia
England, First Series, Old Series, maps, Ordnance Survey, and Wales
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Dataset
Widnes Examiner
Widnes Examiner (1876-1920) was a weekly newspaper which has been digitised by the British Library for the Living with Machines project.British Library
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Conference paper (published)
DeezyMatch: A Flexible Deep Learning Approach to Fuzzy String Matching
We present DeezyMatch, a free, open-source software library written in Python for fuzzy string matching and candidate ranking. Its pair classifier supports various deep neural network architectures for training new classifiers and for fine-tuning a pretrained model, which paves the way for transfer learning in fuzzy string matching. This approach...Hosseini, Kasra ; Nanni, Federico ; Coll Ardanuy, Mariona
Natural Language Processing, string matching, toponym matching, machine learning, and digital humanities
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Dataset
Weymouth Telegram
Weymouth Telegram (1860 - 1901) was a weekly newspaper which has been digitised by the British Library for the Living with Machines project.British Library
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Dataset
The Runcorn Examiner
The Runcorn Examiner (1870-1954) was a weekly newspaper and years 1870-1920 have been digitised by the British Library for the Living with Machines project.British Library
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Dataset
Barrow Herald and Furness Advertiser
Barrow Herald and Furness Advertiser. (1863 - 1914) was a weekly newspaper which has been digitised by the British Library for the Living with Machines projectBritish Library
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Dataset
Cradley Heath & Stourbridge Observer
Cradley Heath & Stourbridge Observer. (1864 - 1888) was a weekly newspaper which has been digitised by the British Library for the Living with Machines projectBritish Library