Inputs and results of "A quantitative and qualitative citation analysis to retracted articles in the humanities domain"

This repository contains the datasets and visualizations generated in our work: <strong>"A quantitative and qualitative citation analysis to retracted articles in the humanities domain"</strong>. <strong>Note:</strong> the data are all contained inside the <strong><em>data.zip</em> </strong>file. You need to unzip the container to get access to all the files and directories listed below. The data (citations) gathered accompanied by their annotated characteristics are stored in <strong><em>data/</em>:</strong> <em>cits.csv: </em>a dataset containing all the entities (rows in the CSV) which have cited a retracted article in the humanities domain. Each citing entity (row) is accompanied by a set of features (columns) that characterizes it.<br> <strong>Note: </strong>this dataset is licensed under a Creative Commons public domain dedication (CC0). <em>content.csv: </em>a dataset containing the abstracts and the in-text citation contexts of all the citing entities gathered.<br> <strong>Note: </strong>the data keep their original license (the one provided by their publisher). This dataset is provided in order to favor the reproducibility of the results obtained in our work. <strong>Topic modeling</strong> We run a topic modeling analysis on the textual features gathered (i.e. abstracts and citation contexts). The results are stored inside the <em><strong>topic_model/</strong></em> directory. The topic modeling has been done using MITAO, a tool for mashing up automatic text analysis tools and creating a completely customizable visual workflow [1]. The directory <em><strong>workflow/ </strong></em>contains the workflows used in MITAO. The topic modeling results for each textual feature are separated into two different folders, <em><strong>abstract/</strong></em> for the abstracts, and <em><strong>cits_context/</strong></em> for the in-text citation contexts. Both the directories contain the following directories/files: <em><strong>datasets_and_views/: </strong></em>the datasets and visualizations generated using MITAO. <em><strong>ldamodel_corpus_dict/: </strong></em>it contains the dictionary, the LDA topic model, and the tokenized and vectorized corpus. <em><strong>rawdata/: </strong></em>the textual collection, metadata, and stopwords used as input in the workflow of MITAO <strong>References</strong> [1] Ferri, P., Heibi, I., Pareschi, L., &amp; Peroni, S. (2020). MITAO: A User Friendly and Modular Software for Topic Modelling [JD]. PuntOorg International Journal, 5(2), 135–149. https://doi.org/10.19245/25.05.pij.5.2.3