The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Getting our head in the clouds: toward evaluation studies of tagclouds
Abstract
Tagclouds are visual presentations of a set of words, typically a set of "tags" selected by some rationale, in which attributes of the text such as size, weight, or color are used to represent features, such as frequency, of the associated terms. This note describes two studies to evaluate the effectiveness of differently constructed tagclouds for the various tasks they can be used to support, including searching, browsing, impression formation and recognition. Based on these studies, we propose a paradigm for evaluating tagclouds and ultimately guidelines for tagcloud construction.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
MRC psycholinguistic database: Machine-usable dictionary, version 2.00
Wilson, M. (1988) · Behavior Research Methods, Instruments, & Computers · doi:10.3758/bf03202594 · Cited by 1,174
HT06, tagging paper, taxonomy, Flickr, academic article, to read
Marlow, C., Naaman, M., Boyd, D., & Davis, M. (2006) · Proceedings of the seventeenth conference on Hypertext and hypermedia · doi:10.1145/1149941.1149949 · Cited by 877
The Structure of Collaborative Tagging Systems
Golder, S. A., & Huberman, B. A. (2005) · arXiv (Cornell University) · doi:10.48550/arxiv.cs/0508082 · Cited by 828
Improving Tag-Clouds as Visual Information Retrieval Interfaces
Hassan‐Montero, Y., & Herrero-Solana, V. (2024) · arXiv (Cornell University) · doi:10.48550/arxiv.2401.04947 · Cited by 313
Dogear: Social bookmarking in the enterprise
Millen, D. R., Feinberg, J., & Kerr, B. (2006) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1124772.1124792 · Cited by 298
Self-citationLibrary 2.0 Theory: Web 2.0 and Its Implications for Libraries
Maness, J. M. (2006) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · Cited by 111
Cited by
Word Cloud Explorer: Text Analytics Based on Word Clouds
Heimerl, F., Lohmann, S., Lange, S., & Ertl, T. (2014) · 2014 47th Hawaii International Conference on System Sciences · doi:10.1109/hicss.2014.231 · Cited by 548
A Survey of Traffic Data Visualization
Chen, W., Guo, F., & Wang, F.-Y. (2015) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2436897 · Cited by 294
VEST, J. R., & KASH, B. A. (2016) · The Milbank Quarterly · doi:10.1111/1468-0009.12180 · Cited by 80
RevMiner: an extractive interface for navigating reviews on a smartphone
Huang, J., Etzioni, O., Zettlemoyer, L., Clark, K., & Lee, C. (2012) · Proceedings of the 25th annual ACM symposium on User interface software and technology · doi:10.1145/2380116.2380120 · Cited by 37
Dense and influential core promotion of daily viral information spread in political echo chambers
Asatani, K., Yamano, H., Sakaki, T., & Sakata, I. (2021) · Scientific Reports · doi:10.1038/s41598-021-86750-w · Cited by 18
Metadata
- Authors
- Rivadeneira, A. W., Gruen, D. M., Muller, M. J., & Millen, D. R.
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2007-04-29
- Pages
- 995-998
- OpenAlex
- W2108105891
- Cited by
- 340
- References
- 6
- FWCI
- 27.10
- Type
- conference paper
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Getting our head in the clouds: toward evaluation studies of tagclouds. https://app.cochat.ai/papers/10.1145/1240624.1240775
- The paper
- Rivadeneira, A. W., Gruen, D. M., Muller, M. J., & Millen, D. R. (2007). Getting our head in the clouds: toward evaluation studies of tagclouds. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/1240624.1240775
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
