topic_preprocess: Preprocess Twitter for topic modelling

In BeaJJ/ComTxt: Twitter text analysis (ComTxt)

Description

This function retrives lemma version of text data.

Usage

topic_preprocess(df, ud_lang, stop_words)

Arguments

df	twitter data frame
ud_lang	Udpipe langauge
stopwords_lang	stopwords langauges

Value

df	rtweet data frame
ud_lang	"spanish","afrikaans-afribooms", "ancient_greek-perseus", "ancient_greek-proiel", "arabic-padt", "armenian-armtdp", "basque-bdt", "belarusian-hse", "bulgarian-btb", "buryat-bdt", "catalan-ancora", "chinese-gsd", "classical_chinese-kyoto", "coptic-scriptorium", "croatian-set", "czech-cac", "czech-cltt", "czech-fictree", "czech-pdt", "danish-ddt", "dutch-alpino", "dutch-lassysmall", "english-ewt", "english-gum", "english-lines", "english-partut", "estonian-edt", "estonian-ewt", "finnish-ftb", "finnish-tdt", "french-gsd", "french-partut", "french-sequoia", "french-spoken", "galician-ctg", "galician-treegal", "german-gsd", "gothic-proiel", "greek-gdt", "hebrew-htb", "hindi-hdtb", "hungarian-szeged", "indonesian-gsd", "irish-idt", "italian-isdt", "italian-partut", "italian-postwita", "italian-vit", "japanese-gsd", "kazakh-ktb", "korean-gsd", "korean-kaist", "kurmanji-mg", "latin-ittb", "latin-perseus", "latin-proiel", "latvian-lvtb", "lithuanian-alksnis", "lithuanian-hse", "maltese-mudt", "marathi-ufal", "north_sami-giella", "norwegian-bokmaal", "norwegian-nynorsk", "norwegian-nynorsklia", "old_church_slavonic-proiel", "old_french-srcmf", "old_russian-torot", "persian-seraji", "polish-lfg", "polish-pdb", "polish-sz", "portuguese-bosque", "portuguese-br", "portuguese-gsd", "romanian-nonstandard", "romanian-rrt", "russian-gsd", "russian-syntagrus", "russian-taiga", "sanskrit-ufal", "serbian-set", "slovak-snk", "slovenian-ssj", "slovenian-sst", "spanish-ancora", "spanish-gsd", "swedish-lines", "swedish-talbanken", "tamil-ttb", "telugu-mtg", "turkish-imst", "ukrainian-iu", "upper_sorbian-ufal", "urdu-udtb", "uyghur-udt", "vietnamese-vtb", "wolof-wtb"
stop_words	the stopwords data

Source

Jan Wijffels (2020) udpipe: Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing with the 'UDPipe' 'NLP' Toolkit

Examples

df_ pre <- twitter_preprocess(df_tweets, ud_lang = "spanish", stop_words)

BeaJJ/ComTxt documentation built on Dec. 17, 2021, 10:46 a.m.