Editing Text mining (section)

=== Software applications ===
Text mining methods and software is also being researched and developed by major firms, including [[IBM]] and [[Microsoft]], to further automate the mining and analysis processes, and by different firms working in the area of search and indexing in general as a way to improve their results. Within the public sector, much effort has been concentrated on creating software for tracking and monitoring [[Information Awareness Office|terrorist activities]].<ref>[http://yatsko.zohosites.com/texor-a-chat-mining-program.html] {{webarchive|url=https://web.archive.org/web/20131004224652/http://yatsko.zohosites.com/texor-a-chat-mining-program.html|date=October 4, 2013}}</ref> For study purposes, [[Weka (machine learning)|Weka software]] is one of the most popular options in the scientific world, acting as an excellent entry point for beginners. For Python programmers, there is an excellent toolkit called [[Natural Language Toolkit|NLTK]] for more general purposes. For more advanced programmers, there's also the [[Gensim]] library, which focuses on word embedding-based text representations.