TopoText is a digital mapping and text analysis software prototype was built by remixing features of open-source tools. After inputting a text in plain text (.txt) format, TopoText matches all unambiguous place names with geographical coordinates and displays them on a map interface using the Stanford Named Entity Recognition (NER) Tagger. Matching is carried out using the Google Maps Platform and placed onto a Google Maps Engine basemap. Coordinated with the map are text analysis and concordance tools that display the context in which the place names occur and allow manipulation of the content for analysis. Manipulation of text is carried out by collocating place-name occurrences and words that appear around them using Wordle. Users can specify the number of words to collocate around a place name, and can categorize them according to part of speech with the embedded Stanford Part-of-Speech (POS) Tagger, which extracts nouns, verbs, adjectives, or adverbs. These collocations can be localized to the specific passage in which the place name appears, or generated across the entire text by counting the most frequent word collocations around a selected place name.
The target users for this tool are researchers conducting a geospatial analysis of a work and exploring topics that occur around specific place names in or across texts. No technical background is required for using TopoText, nor does it require a steep learning curve; it was purposely designed to provide a quick and easy entry point from which to conduct a spatial analysis that could help guide further spatial investigations. In addition, users can upload any type of plain text in English, French, German, or Spanish.
Please see the file called LICENSE.
Randa El Khatib, Julia El Zini, Mohamad Jaber, David Wrisley, Wassim El-Hajj, Shady Elbassuoni, Bilal Abi Farraj, Houda Nasser,Shadia Barada, and Yasmin Kadah.
If you need any further help or have any questions, please contact Randa El Khatib firstname.lastname@example.org.