Metadata
Title
Termite: Visualization Techniques for Assessing Textual Topic Models
Category
general
UUID
6235fb17bf764d9cadd4501eaa584a4c
Source URL
https://idl.uw.edu/papers/termite
Parent URL
https://idl.uw.edu/papers
Crawl Time
2026-03-11T03:13:50+00:00
Rendered Raw Markdown

Termite: Visualization Techniques for Assessing Textual Topic Models

Source: https://idl.uw.edu/papers/termite Parent: https://idl.uw.edu/papers

Termite: Visualization Techniques for Assessing Textual Topic Models

Jason Chuang, Christopher D. Manning, Jeffrey Heer. Proc. Advanced Visual Interfaces, 2012

Jason Chuang, Christopher D. Manning, Jeffrey Heer

Proc. Advanced Visual Interfaces, 2012

The Termite system. A tabular view (left) displays term-topic distributions for an LDA topic model. A bar chart (right) shows the marginal probability of each term.

Materials

PDF | Website | Software

Abstract

Topic models aid analysis of text corpora by identifying latent topics based on co-occurring words. Real-world deployments of topic models, however, often require intensive expert verification and model refinement. In this paper we present Termite, a visual analysis tool for assessing topic model quality. Termite uses a tabular layout to promote comparison of terms both within and across latent topics. We contribute a novel saliency measure for selecting relevant terms and a seriation algorithm that both reveals clustering structure and promotes the legibility of related terms. In a series of examples, we demonstrate how Termite allows analysts to identify coherent and significant themes.

BibTeX

@inproceedings{2012-termite,
  title = {Termite: Visualization Techniques for  Assessing Textual Topic Models},
  author = {Chuang, Jason AND Manning, Christopher AND Heer, Jeffrey},
  booktitle = {Proc. Advanced Visual Interfaces},
  year = {2012},
  url = {https://idl.uw.edu/papers/termite},
  doi = {10.1145/2254556.2254572}
}

{"status":200,"statusText":"","headers":{},"body":"[\n {\n \"fullName\": \"Proc. ACM Human Factors in Computing Systems (CHI)\",\n \"nickname\": \"CHI\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics (Proc. VIS)\",\n \"nickname\": \"VIS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Computer Graphics Forum (Proc. EuroVis)\",\n \"nickname\": \"EuroVis\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. EuroVis Short Papers\",\n \"nickname\": \"EuroVis-Short\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. IEEE VIS Short Papers\",\n \"nickname\": \"VIS-Short\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM User Interface Software & Technology (UIST)\",\n \"nickname\": \"UIST\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM Computer-Supported Cooperative Work (CSCW)\",\n \"nickname\": \"CSCW\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM Intelligent User Interfaces\",\n \"nickname\": \"IUI\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"ACM Trans. on Computer-Human Interaction\",\n \"nickname\": \"ACM TOCHI\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Advanced Visual Interfaces\",\n \"nickname\": \"AVI\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Conference on Innovative Data Systems Research (CIDR)\",\n \"nickname\": \"CIDR\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Very Large Database Endowment (PVLDB)\",\n \"nickname\": \"PVLDB\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Empirical Methods in Natural Language Processing\",\n \"nickname\": \"EMNLP\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. NAACL-HLT\",\n \"nickname\": \"NAACL-HLT\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. International Conference on Weblogs and Social Media (ICWSM)\",\n \"nickname\": \"ICWSM\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics (Proc. InfoVis)\",\n \"nickname\": \"InfoVis\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Beautiful Data\",\n \"nickname\": \"Beautiful Data\",\n \"venueType\": \"book\"\n },\n {\n \"fullName\": \"Information Visualization Journal\",\n \"nickname\": \"IV Journal\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. IEEE Visual Analytics Science & Technology (VAST)\",\n \"nickname\": \"VAST\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Cortex\",\n \"nickname\": \"Cortex\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Hawaii International Conference on Systems Sciences (HICSS)\",\n \"nickname\": \"HICSS\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. IEEE Information Visualization (InfoVis)\",\n \"nickname\": \"InfoVis (Pre-TVCG)\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Ubiquitous Computing\",\n \"nickname\": \"UbiComp\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. WEBKDD Workshop\",\n \"nickname\": \"WEBKDD\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"ACM Trans. on Information Systems\",\n \"nickname\": \"ACM TOIS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Communications of the ACM\",\n \"nickname\": \"CACM\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Workshop on Social Network Mining & Analysis, ACM KDD\",\n \"nickname\": \"SNAKDD\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. Social Visualization Workshop, ACM CHI\",\n \"nickname\": \"CHI Social Vis\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. AVI Workshop on Invisible & Transparent Interfaces\",\n \"nickname\": \"AVI ITI\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. Color Imaging Conference\",\n \"nickname\": \"Color Imaging Conf.\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. Workshop on Applications for Topic Models, NIPS\",\n \"nickname\": \"NIPS Topic Model Ws\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Proc. Mining Software Repositories\",\n \"nickname\": \"MSR\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Journal of Animal Ecology\",\n \"nickname\": \"J Anim Eco\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"J Am Med Inform Assoc\",\n \"nickname\": \"JAMIA\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. International Conference on Machine Learning (ICML)\",\n \"nickname\": \"ICML\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Computer Graphics and Applications\",\n \"nickname\": \"CG&A\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. IEEE Biological Data Visualization (BioVis)\",\n \"nickname\": \"BioVis\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Poetics\",\n \"nickname\": \"Poetics\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. ACM Web Search and Data Mining (WSDM)\",\n \"nickname\": \"WSDM\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. User Modeling and User-Adapted Interaction (UMUAI)\",\n \"nickname\": \"UMUAI\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Workshop on Eye Tracking and Visualization (ETVIS)\",\n \"nickname\": \"ETVIS\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"Trends in Ecology & Evolution\",\n \"nickname\": \"TREE\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"PLOS ONE\",\n \"nickname\": \"PLOS ONE\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. ACM SIGMOD Human-in-the-Loop Data Analysis (HILDA)\",\n \"nickname\": \"HILDA\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics (Proc. VAST)\",\n \"nickname\": \"VAST-TVCG\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Workshop on Dealing with Cognitive Biases in Visualisations (DECISIVe), IEEE VIS\",\n \"nickname\": \"DECISIVe\",\n \"venueType\": \"workshop\"\n },\n {\n \"fullName\": \"arXiv\",\n \"nickname\": \"arXiv\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"The Journal of Open Source Software\",\n \"nickname\": \"JOSS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proceedings of the National Academy of Sciences\",\n \"nickname\": \"PNAS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. Association for Computational Linguistics (ACL)\",\n \"nickname\": \"ACL\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Distill\",\n \"nickname\": \"Distill\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Harvard Data Science Review\",\n \"nickname\": \"HDSR\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Organizational Behavior and Human Decision Processes\",\n \"nickname\": \"OBHDP\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"EPJ Data Science\",\n \"nickname\": \"EPJ-DS\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. IEEE Symposium on Visual Languages and Human Centric Computing (VL/HCC)\",\n \"nickname\": \"VL/HCC\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Proc. ACM Management of Data (SIGMOD)\",\n \"nickname\": \"SIGMOD\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Companion of ACM Management of Data (SIGMOD)\",\n \"nickname\": \"SIGMOD-Demo\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"IEEE Trans. Visualization & Comp. Graphics\",\n \"nickname\": \"TVCG\",\n \"venueType\": \"journal\"\n },\n {\n \"fullName\": \"Proc. ACM Creativity & Cognition\",\n \"nickname\": \"C&C\",\n \"venueType\": \"conference\"\n },\n {\n \"fullName\": \"Workshop on Intelligent and Interactive Writing Assistants (In2Writing)\",\n \"nickname\": \"In2Writing\",\n \"venueType\": \"workshop\"\n }\n]\n"} {"status":200,"statusText":"","headers":{},"body":"{\n \"title\": \"Termite: Visualization Techniques for Assessing Textual Topic Models\",\n \"year\": 2012,\n \"start_page\": null,\n \"end_page\": null,\n \"volume\": null,\n \"issue\": null,\n \"editors\": \"\",\n \"publisher\": \"\",\n \"location\": \"\",\n \"pdf\": \"https://idl.cs.washington.edu/files/2012-Termite-AVI.pdf\",\n \"abstract\": \"Topic models aid analysis of text corpora by identifying latent topics based on co-occurring words. Real-world deployments of topic models, however, often require intensive expert verification and model refinement. In this paper we present Termite, a visual analysis tool for assessing topic model quality. Termite uses a tabular layout to promote comparison of terms both within and across latent topics. We contribute a novel saliency measure for selecting relevant terms and a seriation algorithm that both reveals clustering structure and promotes the legibility of related terms. In a series of examples, we demonstrate how Termite allows analysts to identify coherent and significant themes.\",\n \"thumbnail\": \"images/thumbs/termite.png\",\n \"figure\": \"images/figures/termite.png\",\n \"caption\": \"The Termite system. A tabular view (left) displays term-topic distributions for an LDA topic model. A bar chart (right) shows the marginal probability of each term.\",\n \"web_name\": \"termite\",\n \"visible\": true,\n \"mod_date\": \"2012-04-03\",\n \"note\": \"\",\n \"pub_date\": \"2012-04-03\",\n \"venue\": \"AVI\",\n \"authors\": [\n {\n \"first_name\": \"Jason\",\n \"last_name\": \"Chuang\",\n \"url\": \"http://jason.chuang.info\"\n },\n {\n \"first_name\": \"Christopher\",\n \"last_name\": \"Manning\",\n \"display_name\": \"Christopher D. Manning\"\n },\n {\n \"first_name\": \"Jeffrey\",\n \"last_name\": \"Heer\",\n \"url\": \"http://homes.cs.washington.edu/~jheer/\"\n }\n ],\n \"materials\": [\n {\n \"name\": \"Website\",\n \"link\": \"http://termite.stanford.edu/\"\n },\n {\n \"name\": \"Software\",\n \"link\": \"http://github.com/StanfordHCI/termite\"\n }\n ],\n \"tags\": [],\n \"doi\": \"10.1145/2254556.2254572\"\n}"}

{ __sveltekit_17copn9 = { base: new URL("..", location).pathname.slice(0, -1), assets: "/uwdata.github.io" }; const element = document.currentScript.parentElement; const data = [null,null]; Promise.all([ import("../_app/immutable/entry/start.CZdZnu7S.js"), import("../_app/immutable/entry/app.qRA-U4ZQ.js") ]).then(([kit, app]) => { kit.start(app, element, { node_ids: [0, 7], data, form: null, error: null }); }); }