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The Sci-hub Effect: Sci-hub downloads lead to more article citations (2006.14979v2)

Published 26 Jun 2020 in cs.DL, cs.IR, and stat.AP

Abstract: Citations are often used as a metric of the impact of scientific publications. Here, we examine how the number of downloads from Sci-hub as well as various characteristics of publications and their authors predicts future citations. Using data from 12 leading journals in economics, consumer research, neuroscience, and multidisciplinary research, we found that articles downloaded from Sci-hub were cited 1.72 times more than papers not downloaded from Sci-hub and that the number of downloads from Sci-hub was a robust predictor of future citations. Among other characteristics of publications, the number of figures in a manuscript consistently predicts its future citations. The results suggest that limited access to publications may limit some scientific research from achieving its full impact.

Citations (4)

Summary

  • The paper demonstrates that Sci-hub downloads yield a 1.72 times increase in citations, supporting open-access impact.
  • The analysis uses OLS, robust regression, and instrumental variable methods on data from 12 top journals.
  • The study also finds that articles with more visual data, such as figures, attract higher citation counts.

The Sci-hub Effect: Analyzing the Impact on Citations

The paper "The Sci-hub Effect: Sci-hub downloads lead to more article citations" investigates the influence of Sci-hub downloads on the citation frequency of academic papers. This paper has been conducted using empirical data extracted from 12 prominent journals across various domains such as economics, neuroscience, and multidisciplinary research. The central thesis posits that articles accessed via Sci-hub garner more citations than those that are not, suggesting that the open-access nature of Sci-hub potentially amplifies a paper's scientific impact by broadening its accessibility.

Methodology and Data

The research leverages data spanning from September 2015 to February 2016, capturing both articles downloaded from Sci-hub and those that were not, thus creating experimental and control groups. A multifaceted analysis using Ordinary Least Squares (OLS), robust regression, and instrumental variable techniques allows for a comprehensive understanding of a paper's citation dynamics. The paper integrates various other influences such as the impact factor of journals, the H-index of authors, and figures and tables used in papers.

Findings

The numerical analysis reveals that papers downloaded from Sci-hub are cited approximately 1.72 times more than those not accessed through Sci-hub. This assertion is corroborated across several models, indicating a strong and consistent association between Sci-hub downloads and increased citation counts. Additionally, the paper finds that articles featuring a higher number of figures tend to receive more citations, highlighting the role of visual data presentation in facilitating scholarly engagement and referencing.

The statistical robustness is assured through a variety of assessments, including heteroscedasticity corrections and sensitivity analyses, which consistently support the main claim. Notably, the research identifies that variables such as the number of authors, the H-index of the primary author, and the use of figures significantly predict citation rates. The linear and non-linear modeling further substantiate these associations, providing compelling evidence for Sci-hub's impact on citation frequency.

Implications

These findings have several implications for the academic community and policy-makers. First, they suggest that Sci-hub, by removing access barriers, democratizes the dissemination of scientific knowledge, potentially leveling the playing field for researchers in less resource-rich institutions. This insight challenges the traditional subscription-based journal model, suggesting that open-access platforms could play a vital role in future academic publishing paradigms.

Second, the result that graphical content enhances citation rates prompts a reconsideration of how research findings are presented. For authors, this may mean integrating more comprehensive visual data representation to increase visibility and impact.

Future Directions

The paper opens pathways for further research into how different open-access methodologies might influence citation patterns across other scientific disciplines. Additionally, exploring the interaction between visual presentation and article length, or varying impacts across regional publications, could yield further insights into the mechanics of research dissemination.

In conclusion, this paper offers valuable empirical evidence on the citation impact of open-access platforms, particularly Sci-hub, and suggests substantial implications for how scientific findings are shared and recognized globally. It prompts a re-evaluation of academic publishing practices and highlights the significance of factors like data visuals in academic communication.

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