Workshop: Optimizing (Socio-)linguistic Analysis: Language Variation Suite Toolkit

Time: 04/12/18 1:30pm EST – 3:00pm EST

Venue: Woodburn Hall, 200 (SSRC Grand Hall)

Remote Access: https://iu.zoom.us/j/415931246

In the format of hands-on session, this workshop will introduce participants to the Language Variation Suite (LVS), a user-friendly interactive web application built in R. LVS provides access to advanced statistical methods and visualization techniques, such as mixed-effects modeling, conditional and random tree analyses, cluster analysis. These advanced methods enable researchers to handle imbalanced data, measure individual and group variation, estimate significance, and rank variables according to their significance.

Workshop files:

1. Categorical data csv – Use of R in New York (Labov 1966)
2. Continuous data csv – Intervocalic /d/ (Díaz-Campos et al. 2016)
3. Language Variation Suite
4. Slides

 

Advertisements

R Introduction: SPH Workshop

This workshop covers R basics from learning about RStudio architecture to creating your own graphs with ggplot.

Material:

1. Slides  Introduction
2. CSV file – Movie_metadata.csv (IU BOX)
3. R script – intro.r (IU BOX)
4. R script – plotting.r   (IU BOX)

Workshop: Data Visualization for Corpus Linguistics via Shiny Framework

“The purpose of visualization is insight, not pictures”
(Ben Schneidermen, 1999)

Information visualization affords new opportunities for corpus linguistics. In addition to interpretable data synthesis (Keim et al., 2006), visualization allows researchers to unveil linguistic patterns through data exploration and discovery. Until recently, the full integration of visual analytics into corpus tools was not feasible. For example, web-based corpora (e.g., COCA and BNC) were limited to pre-defined text collections and functionalities, whereas software applications were mainly built for a specific purpose (e.g., AntConc – concordances, TigerSearch – syntactic query). The recent development of Shiny web framework makes it possible to integrate visualization tools into the corpus analysis. Shiny is a reactive system allowing for interactive data analysis and visualization. Built with R, Shiny web framework also provides access to advanced text mining and quantitative algorithms, thus advancing corpus linguistics studies. In this workshop, you will learn the fundamentals of reactive web framework and visual analytics for corpus analysis.

Workshop Materials:

• Zip File – download
• Slides – slideshare
• R and RStudio Instruction – slideshare

Additional Sources:

• Interactive Text Mining Tool for Corpus Linguistics
• Interactive Statistical Tool
• CNS plugin and play Shiny project (under development) – github

 

Venue: Corpora2017 Conference at Saint Petersburg Russia, June 27-30, 2017

Acknowledgment: this workshop is partially sponsored by Cyberinfrastructure for Network Science Center

Materials for Rbootcamp Day 1

Slides: https://www.slideshare.net/obscrivn/rbootcamp-day-1

CSV file: http://cl.indiana.edu/~obscrivn/docs/movie_metadata.csv

txt file: http://cl.indiana.edu/~obscrivn/docs/NY_Times_1996-10-18.txt

pdf file: http://cl.indiana.edu/~obscrivn/docs/C12-3020.pdf

Shiny Web Application – Workshop

“The impact of data scientists’ work depends on how well others can understand their insights to take further actions” (blog)

In this workshop, I will introduce you to the concept of Declarative Reactive Web Frameworks, allowing for interactive user-friendly data visualization and data analytics, particularly Shiny. Shiny is an R package that creates interactive applications for data visualization.

You will learn some Shiny basics: how to build your reactive app and deploy it to the server.

Workshop materials:

1. R installation Instructions – slides
2. CSV file –  download
3. Workshop Slides – slides
4. Shiny Workshop Files: zip file
5. Video of the workshop: youtube

Credits: Some ideas are based on the great tutorial by Dean Attali.

Seminar on ITMS and LVS: Quantitative Methods and Text Mining

The main objective of this workshop is to introduce researchers to user-friendly analytical tools. ITMS and LVS are two web-based tools for visualization and quantitative analysis.  In contrast to existing software programs (e.g., SAS, SPSS, and Tableau), these two applications are built in R and require no installation or programming skills.

This hands-on workshop will provide an overview of available statistical and text-mining techniques in these tools. You will learn how to import csv, text and pdf files, create plots, and run statistical analysis, including conditional trees and random forest tests. You will also learn about natural language pre-processing techniques, such as stopwords removal and stemming. Finally, you will be able to perform topic modeling and cluster analysis.

Part 1: Quantitative Methods – Language Variation Suite LVS slides

Part 2: Text Mining Methods – Interactive Text Mining Suite ITMS slides

Workshop exercice materials:

• sample of categorical data csv file – link
• sample of continuous data csv file – link

Language Variation Suite – v.2 release

Language Variation Suite has been released with more customizable features for language variation analysis.

New features include:

1. Plot Customization – titles, labels, colors

2. Redesigned user-friendly interface

3. Random Slope 

4. Tuning parameters for cluster analysis

5. Customized url link: www.languagevariationsuite.com
6. R code snippets

Do not hesitate to contact if you have any issues or if you like to request new features.

LVS team

Interactive Text Mining Suite – Version 2 Release

ITMS – Interactive Text Mining Suite ITMS is a web application for text analysis. This application offers the computational and statistical power of R and the Shiny web application interactivity.

The new release includes the following features:

• Import Zotero rdf files, Google Book API, json and xml
• Dynamic preprocessing  steps
• Stemming in multiple languages
• Tuning parameters for cluster classification
• Word cloud comparison
• Word cloud customization
• Metadata extraction

Contributors: Jefferson Davis, Irina Trapido and Jay Lee

As always, please do not hesitate to contact if you have any issues or to request new features!

NWAV45 Workshop – Language Variation Suite

Our workshop Optimizing Language Variation Analysis: Language Variation Suite is held on 11/03/16 at Simon Fraser University, Vancouver, Canada!

“Mastery of quantitative methods is increasingly becoming a vital component of linguistic training” (Johnson 2008:1)

“The science of analytical reasoning facilitated by visual interactive interfaces” (Thomas et al. 2005)

Workshop files:

1. Categorical data csv – Use of R in New York (Labov 1966)
2. Continuous data csv – Intervocalic /d/ (Díaz-Campos et al. 2016)
3. Language Variation Suite
4. Handouts
5. Slides

Please come and learn how to perform advanced statistical methods with a user-friendly interactive toolkit for (socio)linguistic analysis. Do not hesitate to contact us if you have any questions and suggestions (obscrivn AT indiana DOT edu)

Olga, Manuel and Rafael

Stepwise Regressions in Language Variation Suite – LVS

LVS provides three types of model comparison (LRT, AIC, and BIC) using the package MASS. The stepwise regression uses both directions (step up and step down) and selects the best model (best predictors).

All three criteria assess model fit.  LRT is based on log likelihood ratio (k = qchisq(1-p, df=1), where for p=0.05, k = 3.84). For more information on AIC ( Akaike Information Criterion ) and BIC (Bayesian information criterion) – see  http://www.jmp.com/support/help/Likelihood_AICc_and_BIC.shtml.

Steps to perform stepwise regression in LVS:

1. Upload csv or excel file – Panel DATA 
2. Go to Panel INFERENTIAL STATISTICS – tab MODELING
3. Select your regression model (dependent and independent factors), type of regression (see tab REGRESSION) and click RUN regression.
4. Go to STEPWISE REGRESSION tab and click RUN stepwise model.
5. Return to Modeling and Regression and update your selection with the best fitted model.

As always, your feedback and suggestions are greatly appreciated! (LVS Team)