The open-source LightSide platform, including the machine-learning and feature-extraction core as well as the researcher's workbench UI, has been and continues to be funded in part through Carnegie Mellon University, in particular by grants from the National Science Foundation and the Office of Naval Research. See the full acknowledgements and grant details below!

We make the LightSide research platform freely available for research and education. In exchange, we ask that you provide us with basic information about who you are and how you're making use of LightSide's capabilities.




Contact me about updates and improvements to LightSide!
(we will not give your email address to others)

How are you using LightSide?

Feb 2019: note for Mac users: to run, click on LightSide.command, not LightSide.app

The Cutting Edge

The most recent version of LightSide is always available - this "snapshot" release is where we preview new features, built from the latest version of the source code that passed our unit tests. Software is now maintained in Github -- please do not use the old Bitbucket site to report issues! See the changelog for details about changes in the codebase. Older changes can be examined in the obsolete Bitbucket repository: old commit history. Please do submit bug reports and feature requests, when opportunities present themselves!

For Chinese processing, use Version 2.3.4zh, November 2018
Feb 2019: note for Mac users: to run, click on LightSide.command, not LightSide.app

Support

How can you get help with LightSide? How can you learn more?

  1. Read the manual! In addition to diving in to the particulars of the tool, the manual gives a great overview of the general workflow.
  2. Join the community of LightSide workbench users - ask questions and explore best practices with your fellow researchers.
  3. Report issues and check out the source code in our Github public repository (plus the library of plugins)

Acknowledgements

LightSide has a long and storied history, which includes contributions from Moonyoung Kang, Sourish Chaudhuri, Yi-Chia Wang, Mahesh Joshi, Eric Rosé, Martin Van Velsen, and Carolyn Penstein Rosé. The open-source LightSide platform, including the machine learning and feature extraction core as well as the GUI research workbench, has been and continues to be funded in part by grants from the National Science Foundation and the Office of Naval Research including:

  • ONR N000141110221 (PI Rosé) Towards Optimization of Macrocognitive Processes: Automating Analysis of the Emergence of Leadership in Ad Hoc Teams
  • NSF IIS-0968485 (PI Kraut) Conversational Dynamics in Online Support Groups
  • NSF DRL-0835426 (PI Rosé) Dynamic Support for Virtual Math Teams
  • NSF SBE 0836012 (PI Koedinger) Pittsburgh Sciences of Learning Center
  • NSF HCC-0803482 (PI Fussell) HCC Medium: Dynamic Support for Computer-Mediated Intercultural Communication
  • ONR N000141010277 (PI Stahl) Theories and Models of Group Cognition
  • NSF REESE/REC 0723580 (PI Rosé) Exploring Adaptive Support for Virtual Math Teams
  • ONR N000140811033 (PI Rosé) TFLex project extension: Expanding the Accessibility and Impact of Language Technologies for Supporting Education

The LightSide research platform is licensed under the GPLv3. We make use of several open-source packages, including Weka, LibLinear, Apache Commons Math, RiverLayout, the Stanford POS Tagger, Trove, and icons courtesy of FamFamFam.

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