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Using Coreference Resolution to Mitigate Measurement Error in Text Analysis

Farhan Iqbal & Michael D. Pfarrer

Organizational Research Methods2025https://doi.org/10.1177/10944281251334777article
AJG 4ABDC A*
Weight
0.37

Abstract

Content analysis has enabled organizational scholars to study constructs and relationships that were previously unattainable at scale. One particular area of focus has been on sentiment analysis, which scholars have implemented to examine myriad relationships pertinent to organizational research. This article addresses certain limitations in sentiment analysis. More specifically, we bring attention to the challenge of accurately attributing sentiment in text that mentions multiple firms. Whereas traditional methods often result in measurement error due to misattributing text to firms, we offer coreference resolution—a natural language processing technique that identifies and links expressions referring to the same entity—as a solution to this problem. Across two studies, we demonstrate the potential of this approach to reduce measurement error and enhance the veracity of text analyses. We conclude by offering avenues for theoretical and empirical advances in organizational research.

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https://doi.org/https://doi.org/10.1177/10944281251334777

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@article{farhan2025,
  title        = {{Using Coreference Resolution to Mitigate Measurement Error in Text Analysis}},
  author       = {Farhan Iqbal & Michael D. Pfarrer},
  journal      = {Organizational Research Methods},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1177/10944281251334777},
}

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Using Coreference Resolution to Mitigate Measurement Error in Text Analysis

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Evidence weight

0.37

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.16 × 0.4 = 0.06
M · momentum0.53 × 0.15 = 0.08
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.