AutoMap 1.2 : extract, analyze, represent, and compare mental models from texts

AutoMapl.2 is a network text analysis tool that extracts, analyzes, represents, and compares mental models from texts. Network text analysis is a specific text analysis method that encodes links between words in a text and builds a network of the linked words. Computational analysis of networks pulled out of textual data is a growing area of research for the following reasons: The large and still growing number of electronically available texts requires the investigation of appropriate methods and tools to analyze large scale collections of texts effectively and efficiently. Today's communication theories are oriented towards complex, large-scale systems, and therefore require methods that provide multi-level access to the meaning of textual data. AutoMap helps users to analyze textual data according to the current requirements. 005.1 C28R 04-100 ; * This work was supported in part by the National Science Foundation under grants: No. ITR/IMIIS-0081219, NSF 0201706 doctoral dissertation award, and NSF IGERT 9972762 in CASOS. Additional support was provided by CASOS and ISRI at Carnegie Mellon University. The views and conclusions contained in this document are those of die authors and should not be interpreted as representing the official policies, either expressed or implied, of the National Science Foundation, or the U.S. government.

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