TOOLS
Overview
This page lists the tools provided by LADAL. To access a tool, simply click on the 
badge or on the linked name of the tool, and the tool (an interactive Jupyter notebook) will launch, allowing you to perform the task.
Concordancing
The Concordancing Tool allows you to create Keyword-in-Context displays of words or phrases in a single text or collection of texts and to download the resulting table. This will allow you to examine how your chosen words or phrases are used across the texts you provide.
Collocations
The Collocation Tool calculates various association measures (collocation statistics) based on textual input and allows you to download the resulting table. These association measures allow you to examine which words are statistically more likely to occur near to each other in your texts.
Keywords
The Keyword Tool calculates various keyness measures describing how words are over or under-represented in the texts you provide, compared to your chosen reference text corpus.
Part-of-speech Tagging
The Pos-tagging Tool allows you to computationally add part-of-speech tags to texts or collections of texts in more than 60 languages and download the resulting pos-tagged texts. This can be used, for example, to identify only the nouns used in your collection of text, or to disambiguate when a word of interest can be used as both a noun and verb.
Corpus Text Cleaning
The Corpus-cleaning Tool allows you to remove and replace words, tags, and other elements from the text data that you upload (of course you can then download the cleaned texts too). This allows you to quickly remove some repetitive structures that might otherwise impact on the analysis of your texts.
Network Analysis
The Network-Analysis Tool allows you to generate and download network graphs based on your data. Instead of a collection of texts, you will need to provide structured data describing the edges and their weights in your network of interest.
Topic Modelling
The Topic-Model Tool allows you to generate your own custom topic models using unsupervised and supervised LDA and download the results in an MS Excel spreadsheet. Topic modelling can allow ‘distant reading’ approaches to examine the contents of a large number of texts without needing to exhaustively read all of them.
Sentiment Analysis
The Sentiment-Analysis Tool allows you to perform a sentiment analysis on your texts and download the results in an MS Excel spreadsheet. This tool uses a word level sentiment scoring approach to estimate whether your texts are more ‘positive’ (“This sandwich is great!”), or ‘negative’ (“The worst sandwich I’ve ever been served”). This can also be used to examine eight basic emotional associations of the words in your texts.
Reporting Errors
If something’s amiss or if a tool isn’t cooperating, don’t hesitate to contact Martin at m.schweinberger@uq.edu.au. We’ll do our best to investigate and resolve the issue as quickly as we can. Thanks for bringing it to our attention!