The DOI matches its Crossref record; 12 of the 12 references it cites were found in a registry or an index.
Input-agreement
Abstract
Since its introduction at CHI 2004, the ESP Game has inspired many similar games that share the goal of gathering data from players. This paper introduces a new mechanism for collecting labeled data using "games with a purpose." In this mechanism, players are provided with either the same or a different object, and asked to describe that object to each other. Based on each other's descriptions, players must decide whether they have the same object or not. We explain why this new mechanism is superior for input data with certain characteristics, introduce an enjoyable new game called "TagATune" that collects tags for music clips via this mechanism, and present findings on the data that is collected by this game.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Citations
Cites
Labeling images with a computer game
von Ahn, L., & Dabbish, L. (2004) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/985692.985733 · Cited by 2,234
Designing games with a purpose
von Ahn, L., & Dabbish, L. (2008) · Communications of the ACM · doi:10.1145/1378704.1378719 · Cited by 1,186
von Ahn, L. (2006) · Computer · doi:10.1109/mc.2006.196 · Cited by 968
Social Tagging and Music Information Retrieval
Lamere, P. (2008) · Journal of New Music Research · doi:10.1080/09298210802479284 · Cited by 280
Games with a Purpose for the Semantic Web
Siorpaes, K., & Hepp, M. F. (2008) · IEEE Intelligent Systems · doi:10.1109/mis.2008.45 · Cited by 215
Tagatune: A Game For Music And Sound Annotation.
Law, E., von Ahn, L., Dannenberg, R. B., & Crawford, M. (2007) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1415567 · Cited by 195
Self-citationHacker, S., & von Ahn, L. (2009) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1518882 · Cited by 142
A Web-Based Game for Collecting Music Metadata
Mandel, M., & Ellis, D. P. W. (2008) · Journal of New Music Research · doi:10.1080/09298210802479300 · Cited by 129
Moodswings: A Collaborative Game For Music Mood Label Collection.
Kim, Y. E., Schmidt, E. M., & Emelle, L. (2008) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1416585 · Cited by 106
A Game-Based Approach For Collecting Semantic Annotations Of Music.
Turnbull, D., Liu, R., Barrington, L., & Lanckriet, G. R. G. (2007) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1416463 · Cited by 98
Cited by
Sorted by citations
WaveNet: a generative model for raw audio
Oord, A. V. D., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., & Kavukcuoglu, K. (2016) · arXiv · doi:10.48550/arxiv.1609.03499 · Cited by 4,911
“• the MagnaTagATune dataset (Law & Von Ahn, 2009), which consists of about 200 hours of music audio.”
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
Kong, Q., Cao, Y., Iqbal, T., Wang, Y., Wang, W., & Plumbley, M. D. (2020) · IEEE/ACM Transactions on Audio, Speech, and Language Processing · doi:10.1109/taslp.2020.3030497 · Cited by 1,235
Power to the People: The Role of Humans in Interactive Machine Learning
Amershi, S., Cakmak, M., Knox, W. B., & Kulesza, T. (2014) · AI Magazine · doi:10.1609/aimag.v35i4.2513 · Cited by 1,084
Bertin-Mahieux, T., Ellis, D. P. W., Whitman, B., & Lamere, P. (2011) · Columbia University · doi:10.7916/d8nz8j07 · Cited by 944
Quinn, A. J., & Bederson, B. B. (2011) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979148 · Cited by 837
Metadata
- Authors
- Law, E., & von Ahn, L.
- Affiliations
- Carnegie Mellon University (US)
- Carnegie Mellon University, Pittsburgh, PA, USA
- ORCID
- Law, Edith
- Venue
- Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
- Publisher
- ACM
- Published
- 2009-04-04
- Pages
- 1197-1206
- OpenAlex
- W2067329295
- Semantic Scholar
- 72dd231084d2fee5c31343b395ae372b68389ba9
- Cited by
- 248
- References
- 12
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 3 · 2023: 5 · 2022: 5 · 2021: 2 · 2020: 6 · 2019: 12 · 2018: 9 · 2017: 14 · 2016: 18 · 2015: 19 · 2014: 29 · 2013: 37 · 2012: 32
- FWCI
- 30.05
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- ACM SIGCHI Conference on Human Factors in Computing Systems (CHI) (publishedVersion)
- Funders
- Heinz Endowments
- Intel Corporation
- Microsoft Research
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Mobile Crowdsensing and Crowdsourcing
- Social Sciences › Psychology › Developmental and Educational Psychology › Educational Games and Gamification
- Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
- Keywords
- games with a purpose, crowdsourcing, music tagging, object identification, collaborative games
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: Input-agreement. https://app.cochat.ai/papers/10.1145/1518701.1518881
- The paper
- Law, E., & von Ahn, L. (2009). Input-agreement. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems. https://doi.org/10.1145/1518701.1518881
