This folder contains a jupyter notebook for the calculation contained in the work-in-progress paper submitted to ISSI 2021
Yuanxi Fu+, Jasmine Yuan+, Jodi Schneider. “Using Citation Bias to Guide Better Sampling of Scientific Literature.” [work in progress paper] In Proceedings of the 18th International Conference on Scientometrics & Informetrics (ISSI2021), Virtual, July 2021. 419–424.
This folder contains Jasmine Yuan's work
This folder contains files for the iGraph to NetworkX code migration
March 18, 2021: made a new file called "networkx-main" for Jasmine to update every week with her code
This folder contains codes that simulates citation networks with varied degrees of bias.
network_generation_toy_model.py simulates a network where a paper X published in year Y has a pre-defined probability p (derived from the observed network) to cite a paper Z published in prior years. A random number is drawn, if the random number is smaller than or equal to to the probability p, we will assign a citation relationship from X to Z.
Data from: de Vries, Y. A., & Munafo, M. (2016). [Dataset] Citation bias and selective focus on positive findings in the literature on 5-HTTLPR, life stress, and depression. University of Bristol. Retrieved January 28, 2021, from http://doi.org/10.5523/BRIS.Z7JCONXFBMDR1JJ3T0W4K1HWN
This folder contains Zhonghe's work
This folder contains codes that are used to produce the work in the iSchool Research Showcase poster: Zhonghe Wan, Yuanxi Fu, Jodi Schneider. Using citation redistribution to estimate unbiased expected citation count from a biased citation network. Poster presented at the iSchool Research Showcase, University of Illinois at Urbana Champaign, October 27, 2021. http://hdl.handle.net/2142/112794