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1 | User's email | Tool name and version | Tool type | Tool references | Use case short description | Use case documentation | User's affiliation | Feedback | TaDiRAH | @dropdown | |||||||||||||||||
2 | Your name, as the person providing this piece of information | Your email, just in case we need to check some information with you | The computational tool, software or library whose use you are going to describe. Please use unique referent identifiers (Handle, Pid, ...) whenever available and specifiy the version if applicable. | Specify what type of tool it is, web application, command line tool, library, ... | Add bibliography and or link to web page of the tool, and or page of existing repositories | The real world DLS use case (research, teaching) where the tool was used. Notice: PLEASE DO NOT INTRODUCE A TOOL DEVELOPED BY YOURSELF OR AD-HOC TOOLS. We are interested in recent use cases (within the last five years) of off-the-shelf tools. - Create one line per use case/tool. | Insert here reference to 1) published research (papers, books, blog posts) with links or 2) projects, or 3) academic courses - please use unique identifier of the publication (ISBN, DOI...) for publications whenever possible | Affiliation of the people using the tool at time of RESEARCH/USE, Institution - City - Country | Brief and constructive report on strengths and weaknessess of the tool/version that you used. Usability with regard to your research question | Optional. Add link to TaDiRAH taxonomy http://tadirah.dariah.eu/vocab/ | |||||||||||||||||
3 | Francesca Frontini | francescafrontini@gmail.com | FactoMiner 1.24 | R library | Husson 2011 Husson, F., Josse, J., Le, S., and Mazet, J. "FactoMineR: Multivariate Exploratory Data Analysis and Data Mining with R", R package version 1.24 (2011). http://factominer.free.fr/ | Stylistic comparison of four French novels. The FactoMiner R library was used to perform CA on a set of extracted syntactic patterns in order to compare the style of four French novel. | Francesca Frontini, Mohamed Amine Boukhaled, Jean-Gabriel Ganascia: Mining for characterising patterns in literature using correspondence analysis: an experiment on French novels. Digital Humanities Quarterly 11(2) (2017) | Labex OBVIL, Université Pierre et Marie Curie Paris 6, Paris, France | http://tadirah.dariah.eu/vocab/index.php?tema=31&/stylistic-analysis | ||||||||||||||||||
4 | Simone Rebora | simone.rebora81@gmail.com | Stylo 0.6.8 | R library | Eder, M., Rybicki, J. and Kestemont, M. (2016). Stylometry with R: a package for computational text analysis. R Journal, 8(1): 107-121, url: https://journal.r-project.org/archive/2016/RJ-2016-007/index.html | Attribution to Robert Musil of a series of articles published in the journal "Tiroler Soldaten-Zeitung" | Rebora, Simone, J. Berenike Herrmann, Massimo Salgaro, and Gerhard Lauer. 2018. “Robert Musil, a War Journal, and Stylometry: Tackling the Issue of Short Texts in Authorship Attribution”. Digital Scholarship in the Humanities, [in press]. https://doi.org/10.1093/llc/fqy055 | University of Verona, Verona, Italy; University of Basel, Basel, Switzerland | The tool was perfectly fit for our research (for both validation and experiments) and it was easily integrated in a series of ad-hoc scripts. Only (minor) shortfalls: it imposed a series of operations not immediately useful for our goal, thus increasing computation time; we had to slightly modify the "oppose" code in order to make all the most preferred/avoided words appear into the graph. | http://tadirah.dariah.eu/vocab/index.php?tema=31&/stylistic-analysis | |||||||||||||||||
5 | Berenike Herrmann | juliaberenike@gmail.com | koRpus 0.10-2 | R library | Michalke, Meik: koRpus: An R Package for Text Analysis (Version 0.10-2), 2017. URL: https://reaktanz.de/?c=hacking&s=koRpus | Used koRpus to measure text fragments for readability, focusing on Flesch index. Readability scores were correlated with other style markers (POS and relation to metaphor) to approximate a combined measure of "vividness" of the prose. | Herrmann, J. B. (accepted). Operationalisierung der Metapher zur quantifizierenden Untersuchung deutschsprachiger literarischer Texte im Übergang von Realismus zur Moderne. In Jannidis, Fotis (Ed.), Tagungsband des DFG-Symposiums „Digitale Literaturwissenschaft”, Villa Vigoni, De Gruyter. | University of Basel, Basel, Switzerland; University of Göttingen, Göttingen, Germany | http://tadirah.dariah.eu/vocab/index.php?tema=31&/stylistic-analysis; http://tadirah.dariah.eu/vocab/index.php?tema=30&/structural-analysis | ||||||||||||||||||
6 | Nanette Rißler-Pipka | nanette.rissler@gmail.com | Stylo 0.6.5 | R library | Eder, M., Rybicki, J. and Kestemont, M. (2016). Stylometry with R: a package for computational text analysis. R Journal, 8(1): 107-121, url: https://journal.r-project.org/archive/2016/RJ-2016-007/index.html | Testing several candidates for the authorship of the second volume of the "Quijote", published under the pseudonym Fernández de Avellaneda and discussing the differences in style between the "Quijote II" by Cervantes and the apocryph version by Avellaneda. Testing cluster analysis and rolling delta. | Nanette Rißler-Pipka: Die Digitalisierung des goldenen Zeitalters – Editionsproblematik und stilometrische Autorschaftsattribution am Beispiel des Quijote. In: Zeitschrift für digitale Geisteswissenschaften. Wolfenbüttel 2018. text/html Format. DOI: 10.17175/2018_004 | Karlsruhe Institute of Technology, Karlsruhe, Germany; University of Siegen, Siegen, Germany | Perfect to proof unliable methods in authorship attribution wrong. Not convincing enough for the community of "cervantistas". | http://tadirah.dariah.eu/vocab/index.php?tema=31&/stylistic-analysis | |||||||||||||||||
7 | Octave Julien | firstname.lastname@univ-paris1.fr | TXM | Desktop or Web application | textometrie.ens-lyon.fr / Heiden, S., Magué, J-P., Pincemin, B. (2010). TXM : Une plateforme logicielle open-source pour la textométrie – conception et développement. In I. C. Sergio Bolasco (Ed.), Proc. of 10th International Conference on the Statistical Analysis of Textual Data - JADT 2010) (Vol. 2, p. 1021-1032). Edizioni Universitarie di Lettere Economia Diritto, Roma, Italy. Online. / Heiden, S. (2010). The TXM Platform : Building Open-Source Textual Analysis Software Compatible with the TEI Encoding Scheme. In K. I. Ryo Otoguro (Ed.), 24th Pacific Asia Conference on Language, Information and Computation (p. 389-398). Institute for Digital Enhancement of Cognitive Development, Waseda University. | PIREH, Université Paris 1 Panhéon Sorbonne | Multipurpose, opensource text analysis software, integrates TreeTagger for lemmatisation, supports CQL queries, and multiple common formats for corpora encoding. | ||||||||||||||||||||
8 | Octave Julien | firstname.lastname@univ-paris1.fr | Iramuteq | Desktop application | http://www.iramuteq.org/ | PIREH, Université Paris 1 Panhéon Sorbonne | Text analysis software, useful for its implementation of the Reinert/Alceste method (classification of text segments) and cooccurences analysis. Graphical interface, based on R, also produces R outputs. | ||||||||||||||||||||
9 | Octave Julien | firstname.lastname@univ-paris1.fr | Lexico3 (beta of version 5 available) | Desktop application | http://www.lexi-co.com/index.html | PIREH, Université Paris 1 Panhéon Sorbonne | Multipurpose text analysis software. Can deal easily with verly large corpora (millions of words). Implements specific and powerful tools for the analysis of chronological evolutions within a corpus, of syntagms, and of patterns of repetitions of a word or syntagm within a corpus | ||||||||||||||||||||
10 | Dominique Legallois | dominique.legallois@sorbonne-nouvelle.fr | Quanteda, tidytext, TM, | R library | Kenneth Benoit, julia Silge | textometry | |||||||||||||||||||||
11 | Dominique Legallois | dominique.legallois@sorbonne-nouvelle.fr | SDMC | https://tal.lipn.univ-paris13.fr/sdmc/ | extraction of syntactic patterns | ||||||||||||||||||||||
12 | Jan Rybicki | jkrybicki@gmail.com | Docuscope | Desktop application | https://www.cmu.edu/dietrich/english/research/docuscope.html | rhetorical analysis | Jonathan Hope, Michael Witmore (2014). "Quantification and the language of later Shakespeare," Actes des congrès de la Société française Shakespeare. 123-149. doi: 10.4000/shakespeare.2830. | Strathclyde U., UK | suite of interactive visualization tools for corpus-based rhetorical analysis | ||||||||||||||||||
13 | Jan Rybicki | jkrybicki@gmail.com | TRACER | Desktop application | https://www.etrap.eu/research/tracer/ | analysis of intertextuality, versioning, comparing translations | Franzini, G. (2016) ‘English translations of Pan Tadeusz: a comparison with TRACER‘, Corpus-based Research in the Humanities workshop. January, 19. Online. | University of Göttingen, Germany | TRACER is a suite of 700 algorithms, whose features can be combined to create the optimal formula for detecting those words, sentences and ideas that have been reused across texts. Created by Marco Büchler, TRACER is designed to facilitate research in text reuse detection and many have made use of it to identify plagiarism in a text, as well as verbatim and near verbatim quotations, paraphrase and even allusions. The thousands of feature combinations that TRACER supports allow to investigate not only contemporary texts, but also complex historical texts where reuse is harder to spot. | ||||||||||||||||||
14 | Jan Rybicki | jkrybicki@gmail.com | WCopyFind | Desktop Application | http://plagiarism.bloomfieldmedia.com/wordpress/software/wcopyfind/ | plagiarism detection, common word n-gram detection | Anna FIlipek (2014). „Pan Tadeusz”, or Translating the Untranslatable: An Analysis of English Translations, M.A. Thesis. Kraków: Uniwersytet Jagielloński | Jagiellonian University, Kraków, Poland | WCopyfind is an open source windows-based program that compares documents and reports similarities in their words and phrases. | ||||||||||||||||||
15 | Allen Riddell | riddella@indiana.edu | lxml | Python package | https://pypi.org/project/lxml/ | Loading data | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
16 | Allen Riddell | riddella@indiana.edu | matplotlib | Python package | https://pypi.org/project/matplotlib | Plotting | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
17 | Allen Riddell | riddella@indiana.edu | nltk | Python package | https://pypi.org/project/nltk | Text analysis | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
18 | Allen Riddell | riddella@indiana.edu | numpy | Python package | https://pypi.org/project/numpy | Text analysis | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
19 | Allen Riddell | riddella@indiana.edu | scipy | Python package | https://pypi.org/project/scipy | Text analysis | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
20 | Allen Riddell | riddella@indiana.edu | pandas | Python package | https://pypi.org/project/pandas | Loading data, summarizing data | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
21 | Allen Riddell | riddella@indiana.edu | pystan | Python package | https://pypi.org/project/pystan | Analyzing data | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
22 | Allen Riddell | riddella@indiana.edu | scikit-learn | Python package | https://pypi.org/project/scikit-learn | Analyzing data, making predictions | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
23 | Allen Riddell | riddella@indiana.edu | statsmodels | Python package | https://pypi.org/project/statsmodels | Analyzing data, making predictions | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
24 | Allen Riddell | riddella@indiana.edu | pytorch | Python package | https://pytorch.org/ | Analyzing data, making predictions | Indiana University Bloomington, Bloomington, USA | Easier to use than Tensorflow for building language models of text. | |||||||||||||||||||
25 | Allen Riddell | riddella@indiana.edu | cartopy | Python package | https://pypi.org/project/cartopy | Making maps | Indiana University Bloomington, Bloomington, USA | None; it's a mature, well-tested Python package. | |||||||||||||||||||
26 | Jonathan Reeve | jonathan.reeve@columbia.edu | text-matcher | Python package | https://pypi.org/project/text-matcher/ | Text reuse detection, plagiarism detection | Jonathan Reeve, Milan Terlunen, and Sierra Eckert. "Middlemarch Critical Histories." [Forthcoming] | Columbia University, New York City, USA | Needs test suite, better documentation. | ||||||||||||||||||
27 | Jonathan Reeve | jonathan.reeve@columbia.edu | macro-etym | Python package | https://github.com/JonathanReeve/macro-etym | Macro-etymological text analysis | Reeve, Jonathan. "A macro-etymological analysis of James Joyce’s A Portrait of the Artist as a Young Man." Reading Modernism with Machines. Palgrave Macmillan, London, 2016. 203-222. | Columbia University, New York City, USA | Needs test suite, some bugfixes, better packaging for data in PyPi. | ||||||||||||||||||
28 | Jonathan Reeve | jonathan.reeve@columbia.edu | chapterize | Python package | https://pypi.org/project/chapterize/ | Text segmentation | Columbia University, New York City, USA | Needs a less deterministic approach to chapter detection | |||||||||||||||||||
29 | Jonathan Reeve | jonathan.reeve@columbia.edu | spacy | Python package | https://spacy.io/ | Natural language processing | Language models are often difficult to install | ||||||||||||||||||||
30 | Jonathan Reeve | jonathan.reeve@columbia.edu | textacy | Python package | https://pypi.org/project/textacy/ | Natural language processing | Some open bugs (see GitHub issues) | ||||||||||||||||||||
31 | Fotis Jannidis | fotis@jannidis.de | gensim | Python package | https://radimrehurek.com/gensim/ | Natural language processing | |||||||||||||||||||||
32 | Fotis Jannidis | fotis@jannidis.de | spacy | Python package | https://spacy.io/ | Natural language processing | |||||||||||||||||||||
33 | Fotis Jannidis | fotis@jannidis.de | umap-learn | Python package | https://github.com/lmcinnes/umap | Dimensionality reduction | |||||||||||||||||||||
34 | Fotis Jannidis | fotis@jannidis.de | seaborn | Python package | https://seaborn.pydata.org/ | Visualization | |||||||||||||||||||||
35 | Fotis Jannidis | fotis@jannidis.de | keras | Python package | https://keras.io/ | Deep Learning Framework | |||||||||||||||||||||
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