Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 383

The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.

Can you see me now?

Benford, Steve, Crabtree, Andy, Flintham, Martin, Drozd, Adam, Anastasi, Rob, Paxton, Mark, Tandavanitj, Nick, Adams, Matt, Row-Farr, Ju·2006·ACM Transactions on Computer-Human Interaction

Abstract

We present a study of a mobile mixed reality game called Can You See Me Now?in which online players are chased through a virtual model of a city by ‘runners’ (professional performers equipped with GPS and WiFi technologies) who have to run through the actual city streets in order to catch the players. We present an ethnographic study of the game as it toured through two different cities and draws upon video recordings of online players, runners, technical support crew, and also on system logs of text communication. Our study reveals the diverse ways in which online players experienced the uncertainties inherent in GPS and WiFi, including being mostly unaware of them, but sometimes seeing them as problems, or treating the as a designed feature of the game, and even occasionally exploiting them within gameplay. In contrast, the runners and technical crew were fully aware of these uncertainties and continually battled against them through an ongoing and distributed process of orchestration. As a result, we encourage designers to deal with such uncertainties as a fundamental characteristic of location-based experiences rather than treating them as exceptions or bugs that might be ironed out in the future. We argue that designers should explicitly consider four potential states of being of a mobile participant: connected and tracked, connected but not tracked, tracked but not connected, and neither connected nor tracked. We then introduce five strategies that might be used to deal with uncertainty in these different states for different kinds of participant: remove it, hide it, manage it, reveal it, and exploit it. Finally, we present proposals for new orchestration interfaces that reveal the ‘seams’ in the underlying technical infrastructure by visualizing the recent performance of GPS and WiFi and predicting the likely future performance of GPS.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1145/1143518.1143522

Cites

25 of 25 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 25 references

Cited by

See all 383

Metadata

Authors
Benford, S., Crabtree, A., Flintham, M., Drozd, A., Anastasi, R., Paxton, M., Tandavanitj, N., Adams, M., & Row-Farr, J.
Venue
ACM Transactions on Computer-Human Interaction
Published
2006-03
Volume
13
Issue
1
Pages
100-133
ISSN
  • 1073-0516 (ISSN-L)
  • 1557-7325
OpenAlex
W2005425904
Cited by
383
References
25
FWCI
42.92
Type
journal article
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: Can you see me now? https://app.cochat.ai/papers/10.1145/1143518.1143522
The paper
Benford, S., Crabtree, A., Flintham, M., Drozd, A., Anastasi, R., Paxton, M., Tandavanitj, N., Adams, M., & Row-Farr, J. (2006). Can you see me now? ACM Transactions on Computer-Human Interaction. https://doi.org/10.1145/1143518.1143522

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.