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Redefining neuromarketing as an integrated science of influence

Overview of attention for article published in Frontiers in Human Neuroscience, February 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (94th percentile)

Mentioned by

news
1 news outlet
twitter
66 X users
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Citations

dimensions_citation
40 Dimensions

Readers on

mendeley
155 Mendeley
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Title
Redefining neuromarketing as an integrated science of influence
Published in
Frontiers in Human Neuroscience, February 2015
DOI 10.3389/fnhum.2014.01073
Pubmed ID
Authors

Hans C. Breiter, Martin Block, Anne J. Blood, Bobby Calder, Laura Chamberlain, Nick Lee, Sherri Livengood, Frank J. Mulhern, Kalyan Raman, Don Schultz, Daniel B. Stern, Vijay Viswanathan, Fengqing Zhang

Abstract

Multiple transformative forces target marketing, many of which derive from new technologies that allow us to sample thinking in real time (i.e., brain imaging), or to look at large aggregations of decisions (i.e., big data). There has been an inclination to refer to the intersection of these technologies with the general topic of marketing as "neuromarketing". There has not been a serious effort to frame neuromarketing, which is the goal of this paper. Neuromarketing can be compared to neuroeconomics, wherein neuroeconomics is generally focused on how individuals make "choices", and represent distributions of choices. Neuromarketing, in contrast, focuses on how a distribution of choices can be shifted or "influenced", which can occur at multiple "scales" of behavior (e.g., individual, group, or market/society). Given influence can affect choice through many cognitive modalities, and not just that of valuation of choice options, a science of influence also implies a need to develop a model of cognitive function integrating attention, memory, and reward/aversion function. The paper concludes with a brief description of three domains of neuromarketing application for studying influence, and their caveats.

X Demographics

X Demographics

The data shown below were collected from the profiles of 66 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 155 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Switzerland 1 <1%
Ecuador 1 <1%
Brazil 1 <1%
Canada 1 <1%
United States 1 <1%
Unknown 150 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 15%
Student > Ph. D. Student 18 12%
Student > Bachelor 14 9%
Professor 13 8%
Student > Doctoral Student 13 8%
Other 34 22%
Unknown 39 25%
Readers by discipline Count As %
Business, Management and Accounting 26 17%
Psychology 14 9%
Social Sciences 11 7%
Neuroscience 10 6%
Computer Science 9 6%
Other 39 25%
Unknown 46 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 64. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 February 2020.
All research outputs
#639,049
of 24,579,513 outputs
Outputs from Frontiers in Human Neuroscience
#288
of 7,513 outputs
Outputs of similar age
#8,894
of 367,679 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#11
of 182 outputs
Altmetric has tracked 24,579,513 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 367,679 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 182 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 94% of its contemporaries.