Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Uniting the Tribes: Using Text for Marketing Insight
2019505 citationsJonah Berger, Ashlee Humphreys et al.Journal of Marketingprofile →
Automated Text Analysis for Consumer Research
2017438 citationsAshlee Humphreys, Rebecca Jen-Hui WangJournal of Consumer Researchprofile →
Peers — A (Enhanced Table)
Peers by citation overlap · career bar shows stage (early→late)
cites ·
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Countries citing papers authored by Ashlee Humphreys
Since
Specialization
Citations
This map shows the geographic impact of Ashlee Humphreys's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Ashlee Humphreys with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ashlee Humphreys more than expected).
Fields of papers citing papers by Ashlee Humphreys
This network shows the impact of papers produced by Ashlee Humphreys. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Ashlee Humphreys. The network helps show where Ashlee Humphreys may publish in the future.
Co-authorship network of co-authors of Ashlee Humphreys
This figure shows the co-authorship network connecting the top 25 collaborators of Ashlee Humphreys.
A scholar is included among the top collaborators of Ashlee Humphreys based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Ashlee Humphreys. Ashlee Humphreys is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Berger, Jonah, Grant Packard, Reihane Boghrati, et al.. (2022). Marketing insights from text analysis. Marketing Letters. 33(3). 365–377.23 indexed citations
Kronrod, Ann, Grant Packard, Sarah G. Moore, et al.. (2020). Where Consumer Behavior Meets Language: Applying Linguistic Methods to Consumer Research. ACR North American Advances.1 indexed citations
Berger, Jonah, Ashlee Humphreys, Stephan Ludwig, et al.. (2019). Uniting the Tribes: Using Text for Marketing Insight. Journal of Marketing. 84(1). 1–25.505 indexed citations breakdown →
Chaney, Damien, Karim Ben Slimane, & Ashlee Humphreys. (2015). Megamarketing expanded by neo-institutional theory. HAL (Le Centre pour la Communication Scientifique Directe).1 indexed citations
Smith, Andrew & Ashlee Humphreys. (2014). Professional Contests and the Emergence of Social Media As an Institutional Field. ACR North American Advances.1 indexed citations
Thyroff, Anastasia, Ashlee Humphreys, Emınegül Karababa, et al.. (2012). Market System Dynamics: the Value of and the Open Questions Associated With Studying Markets in Consumer Culture Theory. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 40. 1096–1097.4 indexed citations
Humphreys, Ashlee & Robert V. Kozinets. (2009). The Construction of Value in Attention Economies. ACR North American Advances.3 indexed citations
19.
Humphreys, Ashlee. (2008). Understanding Collaboration and Collective Production: New Insights on Consumer Co- Production.2 indexed citations
20.
Giesler, Markus & Ashlee Humphreys. (2007). Tensions Between Access and Ownership in the Media Marketplace. ACR North American Advances.1 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.