AutoMap is a text mining tool that enables the extraction of network data from texts. AutoMap can extract three types of information: content analytic (words and frequencies), semantic networks, and meta-networks.

AutoMap uses parts of speech tagging and proximity analysis to do computer-assisted Network Text Analysis (NTA). NTA encodes the links among words in a text and constructs a network of the linked words. 

AutoMap subsumes classical Content Analysis by analyzing the existence, frequencies, and covariance of terms and themes. 

AutoMap has been implemented in Java 1.5.0_07.

It can operate in both a front end with gui, and backend mode.

Main functionalities of AutoMap are:

• Extract, analyze and compare mental models of individuals and groups.
• Reveal structure of social and organizational systems from texts.

AutoMap also offers a variety of techniques for pre-processing Natural Language:

• Named-Entity Recognition
• Stemming (Porter, KStem)
• Collocation (Bigram) Detection
• Extraction routines for dates, events, parts of speech
• Deletion
• Thesaurus development and application
• Flexible ontology usage
• Parts of Speech Tagging

The employed algorithm for map analysis is based on Carley's approach to coding texts as cognitive maps and Danowski's approach for proximity analysis.

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