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. 2022 Jun 6;377(1852):20200409.
doi: 10.1098/rstb.2020.0409. Epub 2022 Apr 18.

The apportionment of citations: a scientometric analysis of Lewontin 1972

Affiliations

The apportionment of citations: a scientometric analysis of Lewontin 1972

Jedidiah Carlson et al. Philos Trans R Soc Lond B Biol Sci. .

Abstract

'The apportionment of human diversity' (1972) is the most highly cited research article published by geneticist Richard Lewontin in his career. This study's primary result-that most genetic diversity in humans can be accounted for by within-population differences, not between-population differences-along with Lewontin's outspoken, politically charged interpretations thereof, has become foundational to the scientific and cultural discourse pertaining to human genetic variation. The article has an unusual bibliometric trajectory in that it is much more salient in the bibliographic record today compared to the first 20 years after its publication. Here, we highlight four factors that may have played a role in shaping the paper's fame: (i) citations in influential publications across several disciplines; (ii) Lewontin's own popular books and media appearances; (iii) the renaissance of population genetics research of the early 1990s; and (iv) the serendipitous collision of scientific progress, influential books and papers, and heated controversies around the year 1994. We conclude with an analysis of Twitter data to characterize the communities and conversations that continue to keep this study at the centre of discussions about race and genetics, prompting new challenges for scientists who have inherited Lewontin's legacy. This article is part of the theme issue 'Celebrating 50 years since Lewontin's apportionment of human diversity'.

Keywords: Lewontin's fallacy; Twitter; bibliometrics; citations; human diversity; population genetics.

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Conflict of interest statement

We declare we have no competing interests.

Figures

Figure 1.
Figure 1.
Bibliometric summary of Lewontin 1972. (a) Cumulative distribution of citations over time; (b) histogram of citations per year; (c) histogram of 2nd-degree citations (i.e. among citing articles in a given year, the total number of citations they have received to date) over time. Contributions from the most highly influential papers (articles that went on to receive greater than 1000 citations, according to Semantic Scholar) that cited Lewontin 1972 are indicated in coloured bar segments.
Figure 2.
Figure 2.
Breakdown of citation patterns for Lewontin 1972 according to the inferred research domain of the citing articles. (a) Total number of citing articles in a given year, stratified by research domain; (b) fraction of citing articles published in a given 5-year period within each of the four research domains.
Figure 3.
Figure 3.
(a) Co-citation frequencies over time for the 15 papers most commonly referenced alongside Lewontin 1972. Data prior to 1995 are not shown due to much lower overall citations of Lewontin 1972. (b) Citation trajectories of landmark population genetics papers (each published before 1980) that were among the most common co-citations of Lewontin 1972. (c) The citation trajectory of Lewontin 1972 compared to topically similar papers published by Nei and Roychoudhury [22,23] that reported similar results.
Figure 4.
Figure 4.
Summarizing nine months of Twitter data for tweets referencing ‘Lewontin’. (a) Timeline of tweets and retweets in our dataset. Each original tweet is shown as a point along the x-axis. For tweets that were retweeted, the retweet trajectories are indicated by linked line segments growing along the y-axis as the number of retweets increases over time. The size of each point indicates the number of followers of the corresponding user. (b) Wordcloud representing the 200 most frequent words found among the 2507 tweets collected (including retweets).
Figure 5.
Figure 5.
Twitter audience segmentation analysis for users indirectly referencing Lewontin 1972. Each unique user that tweeted about that paper is represented by a vertical stack of 12 coloured bars that represent the user's estimated membership probability in each of the 12 inferred audience sectors. The top 30 keywords, hashtags or emoji associated with each audience sector are shown in the legend. Audience sectors inferred to correspond to academic communities are indicated with a formula image emoji at the beginning of the list of associated keywords.
Figure 6.
Figure 6.
Timeline summarizing the relevant events, publications, citations and co-citations surrounding and involving the bibliographic history of Lewontin 1972, up to 2005.

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References

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