Learning to Predict Citation-Based Impact Measures

@article{Weihs2017LearningTP,
  title={Learning to Predict Citation-Based Impact Measures},
  author={Luca Weihs and Oren Etzioni},
  journal={2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL)},
  year={2017},
  pages={1-10}
}
Citations implicitly encode a community's judgment of a paper's importance and thus provide a unique signal by which to study scientific impact. Efforts in understanding and refining this signal are reflected in the probabilistic modeling of citation networks and the proliferation of citation-based impact measures such as Hirsch's h-index. While these efforts focus on understanding the past and present, they leave open the question of whether scientific impact can be predicted into the future… CONTINUE READING

Figures, Tables, and Topics from this paper.

Citations

Publications citing this paper.
SHOWING 1-10 OF 14 CITATIONS

Predicting authors’ citation counts and h-indices with a neural network

VIEW 12 EXCERPTS
CITES RESULTS & METHODS
HIGHLY INFLUENCED

Predicting Long-Term Scientific Impact Based on Multi-Field Feature Extraction

VIEW 9 EXCERPTS
CITES BACKGROUND & METHODS
HIGHLY INFLUENCED

CiteTracked: A Longitudinal Dataset of Peer Reviews and Citations

VIEW 1 EXCERPT
CITES BACKGROUND

References

Publications referenced by this paper.
SHOWING 1-10 OF 28 REFERENCES

Future impact: Predicting scientific success

VIEW 4 EXCERPTS
HIGHLY INFLUENTIAL

A general theory of bibliometric and other cumulative advantage processes

  • Derek De Solla Price
  • Journal of the American Society for Information Science 27,
  • 1976
VIEW 5 EXCERPTS
HIGHLY INFLUENTIAL

An index to quantify an individual's scientific output

VIEW 3 EXCERPTS
HIGHLY INFLUENTIAL

Early prediction of scholar popularity

VIEW 1 EXCERPT

Predicting citation counts of papers

  • Junpeng Chen, Chunxia Zhang
  • Computer Science
  • 2015 IEEE 14th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)
  • 2015
VIEW 1 EXCERPT