Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

Awesome Lists | Featured Topics | Projects

https://github.com/senthilchandrasegaran/textplorer

Visual analytics application for qualitative text analysis
https://github.com/senthilchandrasegaran/textplorer

nlp text-visualization visual-analytics

Last synced: about 2 months ago
JSON representation

Visual analytics application for qualitative text analysis

Awesome Lists containing this project

README 

        
# Textplorer



Textplorer is a web-based visual analytics tool to help the qualitative analyst in the Grounded Theory Method.

Grounded Theory is a general method of developing theoretical constructs

inductively from data sources gathered as a part of a qualitative

research study.

It uses a "construct-oriented approach" where the analyst creates

categories based on patterns in the data.

These categories are further grouped into higher-level categories, and

relationships (especially causal) between categories are identified.

Finally a "core concept" is chosen among these categories, and based on

the relationships identified, a theory is formed.



Textplorer uses natural language processing (NLP) techniques along with

interactive text visualizations to help the user explore the text data,

identify concepts of interest, and establish relationships between these

concepts.



## Publication

Textplorer was developed as part of a paper presented at EuroVis 2017.

The full citation, link to the pdf, and a video demo are shown below.



Chandrasegaran, S., Badam, S.K., Kisselburgh, L., Elmqvist, N., and

Ramani, K. _Integrating Visual Analytics Support for Grounded Theory

Practice in Qualitative Text Analysis_. Computer Graphics Forum (Proc.

EuroVis), 36 (3), pp. 201–212, 2017.



[(**Download Paper**)](https://senthilchandrasegaran.github.io/pages/pubs/pdfs/gthelper.pdf)



[![Click to play video](./textplorer_video.png)](https://vimeo.com/194922904 "Click to play video")



## Installation Instructions

We use the Stanford Parts-of-Speech (POS) Tagger and the Stanford Named

Entity Recognition (NER) Tagger, which require a little setup in Java.

So before installing Textplorer, perform the following steps first.



### Install Dependences



1. Install JDK (v > 1.8), and add the path to the bin file (e.g.

  `C:/Program Files/Java/jdk1.8.0_101/bin` or `/usr/bin/java` to the environment variable `JAVAHOME` (for Windows), or to your `$PATH` variable (for Linux/OSX).

2. Download the [Stanford Named Entity Recognizer](http://nlp.stanford.edu/software/CRF-NER.html#Download)

  and extract its contents to a folder, say `$HOME/StanfordNER/`

3. Add `$HOME/StanfordNER` to the `CLASSPATH` environment variable (for

   windows) or to your `$PATH` variable if linux/OSX.

4. Download the [Stanford CoreNLP models](http://nlp.stanford.edu/software/stanford-english-corenlp-2018-10-05-models.jar)

  and extract the files. Copy the folder `nlp` from

  `stanford-english-corenlp-20YY-MM-DD/edu/stanford/` and place it in

  `$HOME/StanfordNER`.

5. Download the [Stanford POS Tagger](https://nlp.stanford.edu/software/stanford-postagger-2018-10-16.zip), extract the contents into a folder, say `$HOME/StanfordPOS`. Add this folder to your `$PATH` variable.

6. Make sure Node.js and Python are installed on your system

7. Install the [NLTK package](http://www.nltk.org/install.html) for

  Python.

8. Run python and the command line and type ``import nltk``, followed by

   ``nltk.download()``. This opens a download window titled "nltk

   downloader". Select the "Corpora" tab, and download the "wordnet_ic",

   and "stopwords" corpora.



### Install Textplorer

Textplrorer's server uses the [Node.js](https://nodejs.org/) runtime, so

it needs to be installed first, in order to install all related

libraries.



1. Download the source code

  [as a zip file](https://github.com/senthilchandrasegaran/textplorer/archive/master.zip)

  or clone the repository by typing the following command on the terminal:



   ```shell

   $ git clone https://github.com/senthilchandrasegaran/textplorer.git

   ```



2. On the Node.js Command Prompt (for Windows) or Terminal (for OS X), navigate to the main folder (the one that contains the file `textplorer.js`) and type in:



   ```shell

   $ npm install

   ```



This installs all required modules.



**NOTE:**

It is wise to update the path variables in the file

`public/pythonscripts/infoContent.py` to reflect the paths of the

Stanford NER and POS Taggers, instead of relying on the `$PATH` variable setting. Make sure you have the absolute path (paths starting with `~/` or `$HOME` will not work.)



## License

Released under [BSD license](https://opensource.org/licenses/BSD-3-Clause).

Copyright 2017 [Senthil Chandrasegaran](https://github.com/senthilchandrasegaran).