"Citation Analysis: UL Smith (1981)
URL: https://www.ideals.illinois.edu/bitstream/handle/2142/7190/?sequence=1

Citation analysis

Higher the citation counts, the higher the quality, significance, and impact of a document.  

University of Michigan - Ann Arbor

1. Context: 
	- On 3/20/2020, a paper titled, "Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial (Gautret et al.)" was published by International Journal of Antimicrobial Agents, freely accessible ScienceDirect. 
    - On 3/30/3030, an opinion article titled, "A Rush to Judgment? Rapid Reporting and Dissemination of Results and Its Consequences Regarding the Use of Hydroxychloroquine for COVID-19 (Alfred H.J. Kim)" was pubished by Annals of Internal Medicine, pointint out various flaws in Gautret et al.'s. 
    -  Since the publication, Gautret et al. has received criticisms not just by Alfred H.J. Kim et al. within the academic community. 
 2. A google.com search results of each paper
 - Searched on 5/10/2020
 - The searches were done separately by entering the full titles of the papers for respective search
    - The number of citation for Gautret et al.: 646
    - The number of the citations for Alfred H.J. Kim: 21
3. At the moment (5/10/2020), we have not analyzed within what contexts (positive, negative, or neutral) each paper was cited for, but the discrepancy between the number of citations is large.   
   

An example of Google.com search results to compare the number of citations between papers that contradict

@EBRheum: https://twitter.com/EBRheum/status/1244713254011707398

Tweet with a link to a journal article that criticizes inappropriate results from another paper on the use of Hydroxychloroquine & other implications related to rapid reporting

@CarlosdelRio7: https://twitter.com/CarlosdelRio7/status/1248081364215308292

Twitter url to @CarlosdelRio7 who advocates for the retraction of the paper on Hydroxychloroquine (Gautret et al.)

1. The number of negative citations is disproportionately larger than that of the positive ones, which are generally to point out incorrect results.
2. The citation counts include self-citations.

Common criticisms for citation count as a benchmark for scientific performance

Underlying assumption of citation counts as quality indicators

Since single citation count is not convictive enough as a benchmark for scientific performance, a further NLP sentiment analysis could be helpful. Sentiment analysis could identify the emotions (positive, negative, and neutral) within text data so that we can classify all the citations in both articles to figure out the actual opinions.

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