From Kardashian to Nye-Krauss: a dual impact index for marketing scientists


From Kardashian to Nye-Krauss: an index of marketing scientists’ social media presence & academic impact

Professors’ primary responsibility to their subject is to seek and to state the truth as they see it[1].

The goal of science and of universities is to both discover and disseminate knowledge (Bloomfield 2015, How to be a good professor). However, a topic for hot debate is whether individual scientists should do both or focus on either objective. Krauss[2] (2015) describes how public acclaim is often uncorrelated with scientific accomplishment and depends more on communication skills and personality traits. Nevertheless, he argues that the entire scientific community benefits when credible scientists gain a wider audience to promote science literacy, combat scientific nonsense, motivate young people, and steer public policy discussions toward sound decision making wherever they can. But how can we measure such impact?

Recently, a genome biologist (Hall 2014) proposed the Kardashian Index (K-Index), as a metric for “the discrepancy between a scientist’s social media profile and publication record[3]. Using Twitter followers and academic citations, Hall calls scientists with a K-index higher than 5 ‘science kardashians’; i.e. ‘scientists who are seen as leaders in their field simply because of their notoriety’. He notes these are mostly men, while most women in his field have an index below 1 and are “undervalued”.

Wouldn’t it be cool to extend this idea for marketing scientists? Yes, according to research assistant Ziad Choueiki and myself. While we like Hall’s methodology, we disagree with him on interpretation: instead of being ‘Kardashians’, scientists with a high number of followers may be the great science disseminators and communicators of our field. In the natural sciences, “Bill Nye The Science Guy” has much larger public than academic impact acclaim – effectively acting as an ambassador of science. In marketing, Gary Shirr offers marketing insights to 75K Twitter followers, while his Google Scholar citations stand at 135. Other publicly famous scientists – such as the late Carl Sagan or Lawrence Krauss, combine a large number of academic citations with a large public following. In marketing, Dan Ariely educates on (ir)rationality in decision making, while Jennifer Aaker shows how to use social media to drive social change. Thus, we propose the Nye-Krauss (NK) index of a marketing scientist social media presence and academic impact.

Compared to Hall’s (2014) convenience sample of 40 scientists, we set out to obtain a broader list of marketing scholars, combining lists of the top 100 cited professors (most of whom are not on Twitter) and the top 100 list[4] (Huffman 2015) of most tweeted marketing professors (most of whom do not have academic citations) with snowballing Twitter lists (e.g. EMAC followers) and references in our papers. We met several obstacles: many marketing scientists don’t have a Google Scholar profile (we instead summed citations for their top 20 papers on Scholarometer)) or tweet under another name (mea culpa, @romimarketer). We also realized ‘top 100 ‘ lists are outdated soon after they were posted, and found dozen of marketing professors with more Twitter followers than the final one in Huffman (2015). Still, we obtained data on more than 200 marketing professors, of which 88 have at least 200 Twitter followers (our threshold for inclusion in the analysis). As in genome biology, both distribution are skewed: only a few professors have more than 10K Twitter followers (Dan Ariely has 99K), and Google Scholar Citations vary between 8 and 60 K (the latter for David Aaker). We therefore follow Hall (2014) in taking the natural logarithms of both and then regressing ln(Followers) on ln(Citations) and a constant. This regression yields a constant estimate of 6.18 and a slope estimate of 0.14, with a (significant) R2 of .07 and a t-stat of 2.41 on the slope estimate. This regression line is shown as a solid line in the figure. Diving the actual number of twitter followers by the regression-expected number of Twitter followers yields the Nye-Krauss index for each marketing scientist, who are represented by the dots in the Figure. We also offer two classifications (thanks Ashwin Malshe!): K-means clustering (4 clusters in different colors) and Hall’s (2014) original threshold of an index of 5 and our additional threshold of 0.5.

What can we tell from the figure ?

First, the relation between Twitter followers and academic citations is positive and significant, in marketing just as in genome biology. That would warm a scientist’s heart. Second, we observe that the K-means clustering shows yields intuitive segments by itself, but especially combined with Hall’s (2014) Kardashian threshold. We propose the following classification:

Group 1: NK-index > 5: 11 scientists: “A+” Nye-Krauss scientists”: Hall’s (2014) Kardashian threshold of 5 would combine the rather different profiles of the 11 scientists above the top dotted line. On the top left side, our Nye label applies to Gary Schirr (index 77.09), Ashwin Malshe (30.87), Rhiannon MacDonnell (18.59), Christopher Lee (8.65) and Gino Van Ossel (5.11) each have less than 265 Google Scholar citations. On the top right side, our Krauss label applies to Dan Ariely (50.26), Jennifer Aaker (12.92), Kristof De Wulf (9.54), Gad Saad (9.51), Angela Hausman (6.92), David Bell (6.13) each have more than 1700 citations. Top Nye-Krauss scientists are mostly men, as in genome biology (Hall 2014), but 3 (27%) are women in our marketing scientist sample.

Group 2: 1 <NK-index < 5: 23 scientists:A” Nye-Krauss scientists” This group is very close to the “A+” group and again we see 2 segments of about equal size. First, “A“ Nye scientists have substantially more followers than citations. Many of them are young scientists with a research focus on social media, such as Markus Giesler (2.66) Dan Goldstein (2.64) and Behice Ece Ilhan (2.45). Instead, the Krauss-like segment mostly include senior professors such David Aaker (4.95), Pete Fader (4.20) John Deighton (3.35), Anindya Ghose (2.45), Sunil Gupta (2.32), Barbara Kahn (1.68), Jaideep Prabhu (1.66), Rob Kozinets (1.64), Geeta Menon (1.48), Nirmalya Kumar (1.55) and Rudy Moenaert (1.09). 26% of scientists in group 2 are women.

Group 3: 0.5 < NK-index < 1: 21 scientists: “Closing in”: these include Neil Bendle (0.95), Zeynep Arsel (0.93), Christine Moorman (0.90), Frank Goedertier (0.88), Bill Rand (0.82), June Cotte (0.78), Pierre Chandon (0.77), Angelina Close (0.71), Pinar Yildirim, (0.70), Aydin Aydinli (0.64), Uma Karmarkar (0.61), Myung Ja Kim (0.60), Stephen Vargo (0.59), Hope Jensen Shau (0.57), Claudia Townsend (0.55), Eric Bradlow (0.55) and Americus Reed II (0.52). These marketing professors have at most 600 more Twitter followers than citations, and are ‘closing in’ on the regression line by either adding more followers or adding more citations. We see more women (52%) than men in this segment

Segment 4: 0.10 < NK-index < 0.5: 33 scientists: “Get out there”: scoring low in the figure still means these scientists have more than 200 Twitter followers! The vast majority in this group are professors with fewer followers than citations. Hall would call them ‘undervalued’ and we agree, but as marketers we also believe they should make their value shine – and that we should all help them do so! These include Wendy Moe (0.37), Michaela Draganska (0.34), Cait Lamberton (0.29), Kristin Diehl (0.23), Peter Verhoef (0.19), Puneet Manchanda (PMA, 0.18), Venkat Ramaswamy (0.18), Nick Lee (0.13) and yours truly (0.42). A third (33%) of these scientists are women.

Of course, several caveats apply to our analysis. First, our metrics are imperfect: Google Scholar (or Web of Science) citations are but one measure of academic impact, while Twitter following may be less important than activities on other online platforms such LinkedIn, Facebook or Second, it is not the size of your following, it’s how you use it to form and sustain relationships and disseminate knowledge. Third, marketing scientists work on different topics, some of which may be much more intriguing to the general public than others.

What do you think about our interpretation & data? Please comment or email !

[1] American Association of University Professors,

[2] “Scientists as celebrities: Bad for science or good for society?” Bulletin of the Atomic Scientists January/February 2015 71: 26-32

[3] The metric compares your number of Twitter followers to the number you “deserve” based on your number of research citations. Hall (2014) takes a convenience sample of 40 scientists in his field that have considerable Twitter experience, and regresses the log of followers on the log of citations to come up with a formula for how many followers you should have (Fs). Dividing your actual Twitter followers (Fa) by Fs yields your Kardashian index.



6 thoughts on “From Kardashian to Nye-Krauss: a dual impact index for marketing scientists

  1. Really fun stuff, guys. One thing that would be worth looking at is the follower/following ratio on Twitter, since it’s potentially a more accurate indicator of acclaim and “ambassadorship,” since Twitter users with high numbers of similar followers/following are known to have achieved that through automation, rather than influence. But still great things to think about in terms of influence in our field.

    • thanks, Scott, that is a wonderful idea we will implement. others have suggested i look at other measures of social media presence such as Facebook likes and LinkedIn connections, or the Klout score as the composite metric for which each user chooses the media. Which one do you prefer?

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