11 to 20 of 111 Results
May 16, 2024
Karmanov, Fedor; Kotin, Joshua, 2024, "Replication Data for: A Counterfactual Canon", https://doi.org/10.7910/DVN/JOKRHF, Harvard Dataverse, V1, UNF:6:6tgZne1vS0YDF2AzXm/rbA== [fileUNF]
The following code and data was used in the research phase of the Cultural Analytics and Modernism/modernity article "A Counterfactual Canon." The article analyzes the relationship between gender and taste at Shakespeare and Company. Using the Shakespeare and Company Project datasets, we discover that the majority of the books in the lending librar... |
Maria Antoniak; David Mimno; Rosamond Thalken; Melanie Walsh; Matthew Wilkens; Gregory Yauney, 2024, "Replication Data for: The Afterlives of Shakespeare and Company in Online Social Readership", https://doi.org/10.7910/DVN/EZSAL2, Harvard Dataverse, V1
The growth of social reading platforms such as Goodreads and LibraryThing enables us to analyze reading activity at very large scale and in remarkable detail. But twenty-first century systems give us a perspective only on contemporary readers. Meanwhile, the digitization of the lending library records of Shakespeare and Company provides a window in... |
May 9, 2024
Koeser, Rebecca; LeBlanc, Zoe, 2024, "Replication Code and Data for: Missing Data, Speculative Reading", https://doi.org/10.7910/DVN/IFSAMY, Harvard Dataverse, V1, UNF:6:m3Qi4o2Yq9pmCilpqz1Jhw== [fileUNF]
Replication code and data for Missing Data, Speculative Reading Python code, Jupyter notebooks and related data. Applies a combination of time series forecasting, evolutionary models, and recommendation systems to estimate the extent of missing information in the Shakespeare and Company Project datasets (v1.2) and speculatively fill in some gaps. |
May 9, 2024
Frishkopf, Michael, 2024, "Poet-Composer Collaborations in Modern Egyptian Song", https://doi.org/10.7910/DVN/8QYNVS, Harvard Dataverse, V1, UNF:6:zFK38rA3XWOR5iJgGhOv4w== [fileUNF]
Cleaned database of songs, and Pajek bipartite network (.net file) listing and connecting poets and composers of 12,523 songs as provided by Egyptian Radio. |
May 9, 2024
van Lit, Cornelis, 2024, "Replication Data for: Neither Corpus Nor Edition: Building a Pipeline to Make Data Analysis Possible on Medieval Arabic Commentary Traditions", https://doi.org/10.7910/DVN/3KCFRT, Harvard Dataverse, V1, UNF:6:RIcnXy3Si+7u61ORRA8sXw== [fileUNF]
This data is in support of the article in the Journal of Cultural Analytics entitled Neither Corpus Nor Edition: Building a Pipeline to Make Data Analysis Possible on Medieval Arabic Commentary Traditions. Please note that in this dataset we only include the data of the extracted text from Fusus al-hikam, as discussed in the article. The entire sof... |
Leontyeva, Xenia, 2024, "Replication Data for 'Gender (im)balance in the Russian cinema: on the screen and behind the camera'", https://doi.org/10.7910/DVN/ISVTB4, Harvard Dataverse, V1
There are two CSV datasets in this publication used initially in the master thesis in sociology of Xenia Leontyeva at HSE University Saint Petersburg, titled "Popularity Factors of Domestic Films: Gender Characteristics and State Support Measures" (2022), and lately for the article by Leontyeva, Xenia, Olessia Koltsova, and Deb Verhoeven, titled "G... |
Apr 23, 2024
Sarwar, Raheem, 2024, "Replication Data for: Exploring Gender Differences in Fatwa through Machine Learning", https://doi.org/10.7910/DVN/ASAJ4Y, Harvard Dataverse, V1
Replication Data for: Exploring Gender Differences in Fatwa through Machine Learning |
Apr 22, 2024
Mohamed, Eid, 2024, "Al-Manar Magazine", https://doi.org/10.7910/DVN/T0X9UX, Harvard Dataverse, V1
Al-Manar magazine published between 1898 and 1935 in Egypt. |
Mohamed, Eid, 2024, "Data for the two magazines of Al-Risala and Al-Manar", https://doi.org/10.7910/DVN/6BJUJN, Harvard Dataverse, V1
The attached files include 3980 text files and 6.740.567 words from al-Manār and 13755 text files and 15,228,812 words from al-Risālah in addition to the graphs and topic modelling derived from this corpus |
Apr 9, 2024
Gilkison, Aaron; Kurzynski, Maciej, 2024, "Metadata and Code for "Vectors of Violence: Legitimation and Distribution of State Power in the People's Liberation Army Daily (Jiefangjun Bao)"", https://doi.org/10.7910/DVN/DLKIAC, Harvard Dataverse, V1, UNF:6:uq0d77TcKYkzz45AFHoj9Q== [fileUNF]
This dataset contains code and metadata for the paper "Vectors of Violence: Legitimation and Distribution of State Power in the People’s Liberation Army Daily (Jiefangjun Bao)." We provide the MALLET topic model, the lists of Chinese stopwords and violent terms, the Python code for acquiring the journal articles, the Python code to reproduce the re... |
