Online or downloadable tools that are free, free to students, or have generous trial periods without tight usage constraints, watermarks, or other spoilers. Bias toward tools that can be run online or installed on a personal computer without needing an institutional server.
Software for Data Mining, Analytics, Data Science, and Knowledge Discovery - lists software for social network analysis, text analysis, text mining, audio and video mining, web scraping, visualisation, and data cleaning.
Discover research tools for studying text - specific lists of tools for Wikipedia scraping and analysis, social media analysis, tools that are a good introduction to text analysis, sentiment analysis, web scraping, and Voyant tools.
Text Mining and Visualization: Case Studies Using Open-Source Tools provides an introduction to text mining using some of the most popular and powerful open-source tools: KNIME, RapidMiner, Weka, R, and Python. Each chapter presents a case study that you can follow as part of a step-by-step, reproducible example. All the examples are available on a supplementary website. The book shows you how to exploit your text data, offering successful application examples and blueprints for you to tackle your text mining tasks and benefit from open and freely available tools.