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The Topic Model Analyzer (TMA) is a simple tool for exploring and analyzing your real-world data with modern topic models. Using a modern, javascript-enabled web-browser (preferably not IE, yet...), navigate to http://geordi.cs.uiowa.edu/tma and begin using TMA on any reasonably sized dataset, or you can experiment with some of the example datasets. See below for documentation and installation instructions.
The overarching goals of TMA are:
- Allow both non-experts and researchers to easily explore text corpora using modern topic models
- Provide a common platform to exchange topic models applied to various datasets (ie by exchanging the TMA output URL for the online version or TMA database for the offline version)
- Obtain quantitative and qualitative results that can be used to compare topic models and create baselines for novel research
- Collectively produce a data warehouse of various topic models applied to a wide range of corpora (and use this information for meta-research)
TMA built upon Allison Chaney and Dave Blei's Topic Model Visualization Engine, which you can read about in their paper, Visualizing Topic Models.
Interested in contributing? Please join the TMA development group at https://groups.google.com/forum/?fromgroups#!forum/topic-model-analyzer-dev.
TMA is in its early stages, and the developers are currently looking to work with other interested parties in shaping TMA into a standard tool for the topic modeling community. The main idea is to have a common [online] tool that allows researchers to share topic models, easily produce reliable quantitative and qualitative results, and over time, create a warehouse of topic models applied to a vast array of datasets that can be used for meta-research and an overall deeper understanding of topic models. Join the TMA development group (listed above) and please post your suggestions or ideas to the group.
Feel free to take a look at the needed contributions page if you'd like to help but don't know what you'd like to work on.