Mateusz Kostrzewski March 2, 2021

The author’s method is based on finding for each word a table of variations and a set of derived terms or synonyms. Firstly, the register with synonyms and related words is created. The words are then declensioned according to their form. Manual rejection of words incorrectly assigned is required in order to remove them from the final file. The process is shown in Diag.1.

Diag.1. Process of gathering negative words dataset

The rvest library and Google Chrome developer tools were used for this task. The pl.wikitionary.org elements were examined. XPaths to html objects (nodes) were read. Nodes store information such as form, tables of varieties by numbers, degrees and cases, and lists of related words and synonyms. There was need of using regular expressions for text reduction. Text modification was possible with using the following libraries: magrittr, tm and reshape2

Essential in handling http requests is the use of exceptions. It is possible that an endpoint with a particular word has not been created. In order to prevent the server from suspecting the use of a DOS attack, the script waits 1.5 seconds after each request.

The script loads a file hatred_speech_words.csv containing a list of words. For each word, the .html file is downloaded from the pl.wikitionary.org subpage. A registry is created (OutputData/register_hatred.csv) supplemented with synonyms and related words, for which words with similar meaning are also searched. The process is repeated until the fixed number of iterations is reached. A single word in the register is distinguished based on its individual multi-column identifier. The words are then declensioned. The subprocess is shown in Diag.2.

Diag.2. Process of input list supplementation

The registry requires manual rejection of words incorrectly assigned as a synonym, variant, or derivered term and removing them from the final file. Cleanese/cleanese.R filters out misread word texts and discards all variations based on the modified registry containing the words determined as incorrect. The result file is Cleanese/declension_hatred_cleaned.csv. Before running the script, the registry file and variations should be moved to the Cleanese/ folder.

MIT License