Text and Data Mining (TDM): Tools and APIs

Open-source text analysis software for examining word frequency and where and how words occur in texts.

A web-scraping tool that enables you to extract data from websites using Python.

Tutorial from The Programming Historian.

List of tools and tutorials with brief descriptions

Elsevier's developer portal provides API based access to data available in Elsevier products, such as Scopus and ScienceDirect.

An open-source visualization tool for exploring graphs and networks

SPSS is a software platform offers advanced statistical analysis, a vast library of machine learning algorithms, text analysis, open source extensibility, integration with big data and seamless deployment into applications.

Open-source Java-based tools that can be used for document classification, clustering, topic modeling, and other natural language processing.

A platform for building Python programs to work with human language data. Provides easy-to-use interfaces to over 50 corpora and lexical resources, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning.

Free, open-source tool for exploring, cleaning, and transforming data.

Open source statistical software that enables data manipulation, calculation, and graphical display.

A large collection of tools, with reviews and recommendations. Browse or do a keyword search and narrow with filters.

Simple web-based text analysis tool that generates statistics about your text by analyzing word groups, keyword density, the prominence of a word or expression, and word count.

Interactive software for cleaning historical corpora, especially for dealing with spelling variation in Early Modern English texts.

Web-based tool for text reading, basic quantitative analysis, and visualization. Allows you to upload your own text or collection of texts and visualize patterns in a variety of ways. You can also work with existing collections of texts (Shakespeare, Austen).

Extract information from a collection of text documents and uncover the themes and concepts that are concealed in them. SAS Text Miner enables you to combine quantitative variables with unstructured text and thereby incorporate text mining with other traditional data mining techniques.

WordStat for Stata was created to allow Stata 13 and Stata 16 users running under Windows, to apply text analytics techniques on any string variables stored in a Stata data file.