greysun / context

constructing network data from text data

ConText: Network Construction from Texts

ConText supports a) the construction of network data from natural language text data, a process also known as relation extraction and b) the joint analysis of text data and network data.

A new version of ConText running with Java 8 will be published soon.

Contributors:

PI: Jana Diesner [email protected]

• Amirhossein Aleyasen [email protected]
• Chieh-Li Chin [email protected]
• Shubhanshu Mishra [email protected]
• Kiumars Soltani [email protected]
• Liang Tao [email protected]
• Ming Jiang [email protected]
• Harathi Korrapati [email protected]
• Nikolaus Nova Parulian [email protected]
• Lan Jiang [email protected]
• Siva Ratna Kumari Narisetti

License:

ConText Application Executable Files

The ConText application executable files (e.g. ConText-1.*.dmg, ConText-1.*-x64.exe, ConText-1.*-x86.exe, ConText.jar, and ConText.zip) are licensed under GNU General Public License version 3.0 or later license.

The executable files include the following:

• The application code, packaged into a set of JAR files, plus any other application resources (data files, native libraries)
• A private copy of the Java and JavaFX Runtimes, to be used by this application only
• A native launcher for the application
• Metadata, such as icons

Copyright (c) 2019 University of Illinois Board of Trustees, All rights reserved. Other copyright statements provided below.

Developed at the iSchool @ UIUC, by Dr. Jana Diesner, Amirhossein Aleyasen, Chieh-Li Chin, Shubhanshu Mishra, Kiumars Soltani, Liang Tao, Ming Jiang, Harathi Korrapati, Nikolaus Nova Parulian, and Lan Jiang.

U of I Codes

The following files are released under GNU General Public License version 2.0 or later license:

• All files in directory "build"
• All files in directory “installer”
• All files in directory "logo"
• All files in directory "src"
• .classpath, .project, build.fxbuild, build.xml, mainfest.mf, and train_model.sh

Copyright (c) 2019 University of Illinois Board of Trustees, All rights reserved.

Developed at the iSchool @ UIUC, by Dr. Jana Diesner, Amirhossein Aleyasen, Chieh-Li Chin, Shubhanshu Mishra, Kiumars Soltani, Liang Tao, Ming Jiang, Harathi Korrapati, Nikolaus Nova Parulian, and Lan Jiang.

Dependencies

The following dependencies are required for the application, and should be used under their licenses.

Apache License 2.0:

• Apache: Commons BeanUtils (http://commons.apache.org/proper/commons-beanutils), Commons Codec (http://commons.apache.org/proper/commons-codec/), Commons Collections (http://commons.apache.org/proper/commons-collections), Commons Digester (http://commons.apache.org/proper/commons-digester), Commons IO (http://commons.apache.org/proper/commons-io), Commons JEXL (http://commons.apache.org/proper/commons-jexl), Commons Lang (http://commons.apache.org/proper/commons-lang), Commons Logging (http://commons.apache.org/proper/commons-logging), POI (http://poi.apache.org)

• Apache License 2.0

• Joda-Time:

• http://www.joda.org/joda-time/

• Apache License 2.0

• Jollyday:

• http://jollyday.sourceforge.net/

• Apache License 2.0

• JSONIC:

• http://en.sourceforge.jp/projects/jsonic/

• Apache License 2.0

• language-detection:

• http://code.google.com/p/language-detection/

• Apache License 2.0

• OpenCSV:

• http://opencsv.sourceforge.net/

• Apache license 2.0

• Copyright 2007,2010 Kyle Miller.

• Sentiment Word Clusters

• https://github.com/napsternxg/SentimentWordClusters

• Apache License 2.0

GNU License:

• Gephi Toolkit

• http://gephi.org/toolkit/

• GNU General Public License v3.0

• jXLS:

• http://jxls.sourceforge.net

• GNU Lesser General Public License v3.0

• MALLET

• http://mallet.cs.umass.edu

• GNU General Public License v3.0

• McCallum, Andrew Kachites. "MALLET: A Machine Learning for Language Toolkit." http://mallet.cs.umass.edu. 2002.

• Stanford CoreNLP:

• http://nlp.stanford.edu/software/corenlp.shtml

• GNU General Public License (v3 or later)

• Manning, Christopher D., Surdeanu, Mihai, Bauer, John, Finkel, Jenny, Bethard, Steven J., and McClosky, David. 2014. The Stanford CoreNLP Natural Language Processing Toolkit. In Proceedings of 52nd Annual Meeting of the Association for Computational Linguistics: System Demonstrations, pp. 55-60. [pdf] [bib]

• Stanford Named Entity Recognizer (NER)

• http://nlp.stanford.edu/software/CRF-NER.shtml

• GNU General Public License (v2 or later)

• Note: We are using the following files in the data/Classifiers folder: english.all.3class.distsim.crf.ser.gz, english.all.3class.distsim.prop, english.conll.4class.distsim.crf.ser.gz, english.conll.4class.distsim.prop, english.muc.7class.distsim.crf.ser.gz, english.muc.7class.distsim.prop, ner-eng-ie.crf-3-all2008-distsim.ser.gz, ner-eng-ie.crf-3-all2008.ser.gz, ner-eng-ie.crf-4-conll-distsim.ser.gz, ner-eng-ie.crf-4-conll.ser.gz

• Stanford Parser:

• http://nlp.stanford.edu/software/lex-parser.shtml

• GNU General Public License (v2 or later)

• Note: We've removed the following models from stanford-parser-3.4.1-models.jar: arabicFactored.ser.gz, chineseFactored.ser.gz, chinesePCFG.ser.gz, englishRNN.ser.gz, frenchFactored.ser.gz, germanFactored.ser.gz, germanPCFG.ser.gz, wsjRNN.ser.gz

• Dan Klein and Christopher D. Manning. 2003. Accurate Unlexicalized Parsing. Proceedings of the 41st Meeting of the Association for Computational Linguistics, pp. 423-430.

• Dan Klein and Christopher D. Manning. 2003. Fast Exact Inference with a Factored Model for Natural Language Parsing. In Advances in Neural Information Processing Systems 15 (NIPS 2002), Cambridge, MA: MIT Press, pp. 3-10.

• Marie-Catherine de Marneffe, Bill MacCartney and Christopher D. Manning. 2006. Generating Typed Dependency Parses from Phrase Structure Parses. In LREC 2006.

• Stanford POS Tagger:

• http://nlp.stanford.edu/software/tagger.shtml

• GNU General Public License (v2 or later)

• Kristina Toutanova, Dan Klein, Christopher Manning, and Yoram Singer. 2003. Feature-Rich Part-of-Speech Tagging with a Cyclic Dependency Network. In Proceedings of HLT-NAACL 2003, pp. 252-259.

• Subjectivity Lexicon:

• http://mpqa.cs.pitt.edu/lexicons/subj_lexicon/

• GNU General Public License v3.0

• Theresa Wilson, Janyce Wiebe, and Paul Hoffmann (2005). Recognizing Contextual Polarity in Phrase-Level Sentiment Analysis. Proceedings of HLT/EMNLP-2005.

• Trove:

• http://trove.starlight-systems.com/license

• GNU Lesser General Public License (LGPL) 2.1 or later

• XOM:

• http://www.xom.nu/

• GNU Lesser General Public License (LGPL) 2.1

Other Licenses:

• D3.js:

• http://d3js.org/

• 3-Clause BSD License

• Copyright (c) 2010-2015, Michael Bostock

• MonologFX:

• https://github.com/hecklerm/MonologFX

• MIT License

• SecondString:

• http://secondstring.sourceforge.net/

• University of Illinois/NCSA Open Source License

Citing ConText:

While not a condition of use, the developers would appreciate if you acknowledge its use with the following citations:

Diesner, J. (2014). ConText: Software for the Integrated Analysis of Text Data and Network Data. Paper presented at the Social and Semantic Networks in Communication Research. Preconference at Conference of International Communication Association (ICA), Seattle, WA.

Diesner, J., Aleyasen, A., Chin, C., Mishra, S., Soltani, K., Tao, L., Jiang, M., Korrapati, H., Parulian, N., & Jiang, L. (2019). ConText: Network Construction from Texts [Software]. Available from http://context.ischool.illinois.edu/