Package: text2emotion 0.1.0

text2emotion: Real-Time Emoji Mapping for Emotional English Text

This package allows users to analyze text and classify emotions such as happiness, sadness, anger, fear, and neutrality. It combines text preprocessing, TF-IDF feature extraction, and Random Forest classification to predict emotions and map them to corresponding emojis for enhanced sentiment visualization.

Authors:Yusong Zhao [aut], Fangyi Wang [aut, cre], Zisheng Qu [aut]

text2emotion_0.1.0.tar.gz
text2emotion_0.1.0.zip(r-4.7)text2emotion_0.1.0.zip(r-4.6)text2emotion_0.1.0.zip(r-4.5)
text2emotion_0.1.0.tgz(r-4.6-any)text2emotion_0.1.0.tgz(r-4.5-any)
text2emotion_0.1.0.tar.gz(r-4.7-any)text2emotion_0.1.0.tar.gz(r-4.6-any)
text2emotion_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
text2emotion/json (API)

# Install 'text2emotion' in R:

install.packages('text2emotion', repos = c('https://hateprograming.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/hateprograming/text2emotion/issues

On CRAN:

3.18 score 3 stars 153 downloads 8 exports 94 dependencies

Last updated from:a307c75157. Checks:7 WARNING, 1 ERROR, 1 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	WARNING	218
source / vignettes	ERROR	273
linux-release-x86_64	WARNING	194
macos-release-arm64	WARNING	200
macos-oldrel-arm64	WARNING	226
windows-devel	WARNING	173
windows-release	WARNING	141
windows-oldrel	WARNING	137
wasm-release	OK	151

Exports:evaluate_rf_model handle_negation predict_emotion_with_emoji preprocess_text train_full_model train_rf_model train_tfidf_model tune_rf_model

Dependencies:caret class cli clock codetools cpp11 data.table diagram digest dplyr dtt e1071 english farver float foreach future future.apply generics ggplot2 globals glue gower gtable hardhat ipred isoband iterators KernSmooth labeling lattice lava lexicon lgr lifecycle listenv lubridate magrittr MASS Matrix MatrixExtra mgsub mlapi ModelMetrics nlme NLP nnet numDeriv parallelly pillar pkgconfig plyr pROC prodlim progressr proxy purrr qdapRegex R6 ranger RColorBrewer Rcpp RcppArmadillo RcppEigen recipes reshape2 RhpcBLASctl rlang rpart rsparse S7 scales shape slam sparsevctrs SQUAREM stringi stringr survival syuzhet text2vec textclean textshape tibble tidyr tidyselect timechange timeDate tzdb utf8 vctrs viridisLite withr zoo

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Evaluate a Random Forest Model on Test Data	evaluate_rf_model
Handle Negation in Token List	handle_negation
Predict Emotion with Emoji Representation	predict_emotion_with_emoji
Preprocess Text with Slang Handling	preprocess_text
Train a full model pipeline including text preprocessing, TF-IDF vectorization, random forest tuning, and training.	train_full_model
Train a Random Forest Model with TF-IDF Features	train_rf_model
Train a TF-IDF Model (for Training Phase)	train_tfidf_model
Tune Random Forest Model Hyperparameters	tune_rf_model