Text Mining

An intermediate-level freeware corpus analysis toolkit for concordancing and text analysis. Includes plotting, clustering, collocating, and visualizations.

Google Books Ngram Viewer is a beginner text mining tool that displays frequencies of phrases in a corpus of published books over a customizable time frame.

The HTRC is a tool for beginner to intermediate text mining. It enables computations analysis of nearly 3 million texts in the HathiTrust Digital Library as well as texts uploaded by the user.

MALLET (Machine Learning for Language Toolkit) is a tool for intermediate to advanced text mining. It is a command line tool for natural language processing, document classification, clustering, topic modeling and information extraction.

Orange in an intermediate to advanced open source machine learning and data visualization program. Orange is a visual programming package that does not require coding, but can provide Python integrations.

Python is a general-purpose programming language that can be used for text mining. Common packages for text analysis include: Scrapy, BeautifulSoup, NLTK, Scattertext, SpaCy, TextBlob.

R is a scripting language for statistical computing and graphics that can do a variety of tasks, including text mining. Popular packages for analyzing text include: rvest, quanteda, koRpus, spacyr, tidytext, tokenizer, text2vec, ida, STM, topicmodels, SentimentAnalysis, and cleanNLP.

SameDiff is a a tool for beginner text mining. It is a web-based tool for comparing two texts. It generates lists of common words and distinct words. It also uses cosine similarity algorithm to rate the similarity of the documents.

Voyant is a tool for beginner to intermediate text mining. It is a web-based and allows basic text mining of texts uploaded by the user or users can put in a URL and text mine an entire webpage.

Online environment for social media data ingestion, pre-processing, and analysis. Currently only available for Reddit and YouTube data.

A beginner tool for tracking Google search trends by keyword, time, and location.