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.
This map shows the geographic impact of Jean Scholtz'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 Jean Scholtz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jean Scholtz more than expected).
This network shows the impact of papers produced by Jean Scholtz. 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 Jean Scholtz. The network helps show where Jean Scholtz may publish in the future.
Co-authorship network of co-authors of Jean Scholtz
This figure shows the co-authorship network connecting the top 25 collaborators of Jean Scholtz.
A scholar is included among the top collaborators of Jean Scholtz 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 Jean Scholtz. Jean Scholtz is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Scholtz, Jean & Mark Whiting. (2009). User-Centered Evaluation of Technosocial Predictive Analytics. National Conference on Artificial Intelligence. 126–129.3 indexed citations
3.
Goel, Ashok K., Emile L. Morse, Anita Raja, Jean Scholtz, & John Stasko. (2009). Computational explanations for report generation in intelligence analysis. 37–47.1 indexed citations
4.
Plaisant, Catherine, Georges Grinstein, Jean Scholtz, et al.. (2008). Evaluating Visual Analytics: The 2007 Visual Analytics Science and Technology Symposium Contest | NIST. IEEE Computer Graphics and Applications.4 indexed citations
5.
Stanton, Brian, Brian Antonishek, & Jean Scholtz. (2007). Development of an Evaluation Method for Acceptable Usability.1 indexed citations
Scholtz, Jean, et al.. (2003). The Common Industry Format: A Way for Vendors and Customers to Talk About Software Usability.4 indexed citations
9.
Crosby, Martha E., Jean Scholtz, & Susan Wiedenbeck. (2002). The Roles Beacons Play in Comprehension for Novice and Expert Programmers.. PPIG. 5.55 indexed citations
10.
Scholtz, Jean & JEFF JOHNSON. (2002). Identification technologies. ACM SIGCHI Bulletin. 2002(July-Aug). 9–9.2 indexed citations
11.
Scholtz, Jean & John Thomas. (2000). Proceedings on the 2000 conference on Universal Usability.33 indexed citations
Mills, Kevin L., Jean Scholtz, & Karen Sollins. (2000). Workshop on Smart Spaces. IEEE Personal Communications.6 indexed citations
15.
Scholtz, Jean. (1999). The IUSR Project: Industry Usability Report.1 indexed citations
16.
Scholtz, Jean, Jim Spohrer, & Curtis R. Cook. (1993). Empirical Studies of Programmers: Fifth Workshop. Greenwood Publishing Group Inc. eBooks.46 indexed citations
17.
Cook, Curtis R., Jean Scholtz, & Jim Spohrer. (1993). Empirical studies of programmers : fifth workshop : papers presented at the Fifth Workshop on Empirical Studies of Programmers, December 3-5, 1993, Palo Alto, CA.1 indexed citations
Scholtz, Jean & Susan Wiedenbeck. (1990). Learning to program in another language. International Conference on Human-Computer Interaction. 925–930.6 indexed citations
20.
Wiedenbeck, Susan & Jean Scholtz. (1989). Beacons: a knowledge structure in program comprehension. International Conference on Human-Computer Interaction. 82–87.8 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.