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Cited by 36

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Citing for high impact

Shi, Xiaolin, Leskovec, Jure, McFarland, Daniel A.·2010·Proceedings of the 10th annual joint conference on Digital libraries
DOI 10.1145/1816123.1816131
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Abstract

The question of citation behavior has always intrigued scientists from various disciplines. While general citation patterns have been widely studied in the literature we develop the notion of citation projection graphs by investigating the citations among the publications that a given paper cites. We investigate how patterns of citations vary between various scientific disciplines and how such patterns reflect the scientific impact of the paper. We find that idiosyncratic citation patterns are characteristic for low impact papers; while narrow, discipline-focused citation patterns are common for medium impact papers. Our results show that crossing-community, or bridging citation patters are high risk and high reward since such patterns are characteristic for both low and high impact papers. Last, we observe that recently citation networks are trending toward more bridging and interdisciplinary forms.

Overview

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Crossref · 10.1145/1816123.1816131

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

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This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

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Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Show all 1 references

Research works printed but not linked: 23

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Metadata

Authors
Shi, X., Leskovec, J., & McFarland, D. A.
Affiliations
Stanford University, Stanford, CA, USA
Venue
Proceedings of the 10th annual joint conference on Digital libraries
Publisher
ACM
Published
2010-06-21
Pages
49-58
DOI
10.1145/1816123.1816131
Cited by
36
References
1
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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.

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