Package 'TextMiningGUI'

Title: Text Mining GUI Interface
Description: Graphic interface for text analysis, implement a few methods such as biplots, correspondence analysis, co-occurrence, clustering, topic models, correlations and sentiments.
Authors: Conrado Reyes [aut, cre], Purificacion Galindo [tch]
Maintainer: Conrado Reyes <[email protected]>
License: GPL (>= 2)
Version: 0.3
Built: 2024-10-07 04:03:53 UTC
Source: https://github.com/c0reyes/textmininggui

Help Index

chistes

Description

Data from: https://github.com/liopic/chistes-nlp

jockes

Description

Data from: https://github.com/taivop/joke-dataset

TextMiningGUI

Description

Graphic interface for text analysis, implement a few methods such as biplots, correspondence analysis, co-occurrence, clustering, topic models, correlations and sentiments.

File Menu:

  • Can import files: csv, excel, json or RData.

  • Save project.

  • Set work directory.

Data Menu:

  • Converter Columns

  • Transform

  • Slice

  • View Data

  • View Lexical Table

  • View Clean Data

Analysis Menu:

  • Statistics

  • Most common words

  • Word Group

  • Word Cloud

  • Co-ocurrence

  • Cluster

  • Correlation

  • Correlation Between Two Groups

  • AFC

  • HJ-Biplot

  • Emotions & Sentiments

  • Topic Models

Usage

TextMiningGUI(seed = 0)

Arguments

seed

the seed of internal function.

References

  • Becue, M. B. (1992) El análisis estadístico de datos textuales. La lectura según los escolares de la enseñanza primaria.

  • Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988). The New S Language. Wadsworth & Brooks/Cole. (S version.)

  • Benzècri, J. P. (1973). L'Analyse des Donées: L'Analyse des correspondences. Paris: Dunod.

  • Blei, D. B., Ng, A. Y. N., Jordan, M. I. J. (2003) Latent Dirichlet Allocation.

  • Caballero, D. C. (2014) Grupos de Discusión y HJ-Biplot: Una Nueva Forma de Análisis Textual.

  • Caballero, D.C. (2011). El HJ-Biplot como Herramienta en el Análisis de Grupos de Discusión. Salamanca: Universidad de Salamanca.

  • Collins, M. J. C. (1996) A new Statistical Parser Based on Bigram Lexical Dependencies.

  • Diaz-Faes, A. D. (2013) HJ-Biplot como herramienta de inspección de matrices de datos bibliométricos.

  • Feinerer, I., Hornik, K. (2019). tm: Text Mining Package. R package version 0.7-7. https://CRAN.R-project.org/package=tm

  • Feinerer, I., Hornik, K., Meyer, D. (2008). Text Mining Infrastructure in R. Journal of Statistical Software 25(5): 1-54. http://www.jstatsoft.org/v25/i05/

  • Forgy, E. W. (1965). Cluster analysis of multivariate data: efficiency vs interpretability of classifications. Biometrics, 21, 768–769.

  • Gabriel, K. R. (1971). The biplot graphic display of matrices with application to principal component analysis. Biometrika 58, 3 , 453-467

  • Galindo, M. P. (1985). Contribuciones a la Representación Simultánea de Datos Multidimensionales. Tesis Doctoral. Salamanca: Universidad de Salamanca.

  • Galindo, P. (1986). Una alternativa de representación simultanea: HJ-Biplot. Qüestiió ,13-23.

  • Hartigan, J. A. and Wong, M. A. (1979). Algorithm AS 136: A K-means clustering algorithm. Applied Statistics, 28, 100–108. doi: 10.2307/2346830.

  • Jockers, ML. (2015). Syuzhet: Extract Sentiment and Plot Arcs from Text. https://github.com/mjockers/syuzhet

  • Kuhn, M., Jackson, S., Cimentada, J. (2020). corrr: Correlations in R. R package version 0.4.2. https://CRAN.R-project.org/package=corrr

  • Lloyd, S. P. (1957, 1982). Least squares quantization in PCM. Technical Note, Bell Laboratories. Published in 1982 in IEEE Transactions on Information Theory, 28, 128–137.

  • MacQueen, J. (1967). Some methods for classification and analysis of multivariate observations. In Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, eds L. M. Le Cam & J. Neyman, 1, pp. 281–297. Berkeley, CA: University of California Press.

  • Müller, K., Wickham, H. (2020). tibble: Simple Data Frames. R package version 3.0.1. https://CRAN.R-project.org/package=tibble

  • Nenadic, O., Greenacre, M. (2007) Correspondence Analysis in R, with two- and three-dimensional graphics: The ca package. Journal of Statistical Software 20(3):1-13.

  • Silge, J., Robinson, D. (2016). “tidytext: Text Mining and Analysis Using Tidy Data Principles in R. https://doi.org/10.21105/joss.00037

  • Osuna, Z. (2006). Contribuciones al Análisis de Datos Textuales.

  • Osuna, Z. O. (2004) Análisis estadístico de datos textuales. Aplicación al estudio de las declaraciones del Libertador Simón Bolívar

  • Robertson, S. R. (2004) Understanding Inverse Document Frequency: On theoretical arguments for IDF.

  • Vicente-Villardón, J. L. (2017). MultBiplotR: Multivariate Analysis using Biplots. R package version 0.1.0. http://biplot.dep.usal.es/multbiplot/multbiplot-in-r/

  • Ward, J. H., Jr. (1963), "Hierarchical Grouping to Optimize an Objective Function", Journal of the American Statistical Association, 58, 236–244.

  • Wickham, H. (2016) ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York.

  • Wickham, H., François, R., Henry, L., Müller, K. (2020). dplyr: A Grammar of Data Manipulation. R package version 0.8.5. https://CRAN.R-project.org/package=dplyr

  • Wickham, H., Lionel Henry, L. (2020). tidyr: Tidy Messy Data. R package version 1.0.2. https://CRAN.R-project.org/package=tidyr

  • NRC Word-Emotion Association Lexicon. (2010). http://saifmohammad.com/WebPages/NRC-Emotion-Lexicon.htm

  • ProgGUIinR: support package for «Programming Graphical User Interfaces in R». (2014). https://rdrr.io/cran/ProgGUIinR/

Examples

library(TextMiningGUI)
if(TextMiningGUI()){}