Kate Ehrlich

4.7k citations
70 papers · 3.1k · 1 hit paper · h-index 27

Impact in

Papers in

Kate Ehrlich

68 papers receiving 2.7k citations

Kate Ehrlich's Hit Papers

Empirical Studies of Programming Knowledge 1984 · 618 citations
6180+14+28Years since publication200400600

Peers

Kate Ehrlich
Comparison fields: 5 of 113
  • Computer Science Applications 838
  • Software 299
  • Information Systems 1.3k
  • Communication 382
  • Developmental and Educational Psychology 609
Replace Erkki Sutinen with:
Erkki Sutinen Finland
Andrew Begel United States
Marian Petre United Kingdom
Andrés Monroy‐Hernández United States
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Robert D. Macredie United Kingdom
W. Lewis Johnson United States
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Citations per field
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Citations per year

Countries citing papers authored by Kate Ehrlich

Since Specialization
Citations

This map shows the geographic impact of Kate Ehrlich'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 Kate Ehrlich with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kate Ehrlich more than expected).

Fields of papers citing papers by Kate Ehrlich

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kate Ehrlich. 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 Kate Ehrlich. The network helps show where Kate Ehrlich may publish in the future.

Co-authors

The 25 scholars most cited alongside Kate Ehrlich, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kate Ehrlich Line = papers co-authored together Kate Ehrlich links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 70 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Empirical Studies of Programming Knowledge
Hit paper breakdown →
1984618
2 1983221
3 1983180
4 1982161
5 1995159
6 1980108
7 2007106
8 1984103
9 1989102
10 201093
11
An empirical investigation of the tacit plan knowledge in programming
198486
12
Knowledge and processes in the comprehension of computer programs.
198879
13 201274
14 200964
15 200761
16 200857
17 199948
18 200847
19 200846
20 201246

About Kate Ehrlich

Kate Ehrlich is a scholar working on Information Systems, Computer Science Applications, Communication, Artificial Intelligence and Social Psychology, having authored 70 papers that have together received 3.1k indexed citations. Recurring topics across this work include Software Engineering Techniques and Practices (17 papers), Knowledge Management and Sharing (16 papers), Software Engineering Research (13 papers), Team Dynamics and Performance (12 papers), Open Source Software Innovations (11 papers), Expert finding and Q&A systems (8 papers), Usability and User Interface Design (7 papers) and Digital Marketing and Social Media (6 papers). The work is most often cited by research in Computer Science Applications (838 citations), Software (299 citations), Information Systems (1.3k citations), Communication (382 citations) and Developmental and Educational Psychology (609 citations). Kate Ehrlich has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Elliot Soloway, N. Sadat Shami, Keith Rayner, Jeffrey Bonar, P. N. Johnson‐Laird, David A. Maltz, Ching‐Yung Lin, Marcelo Cataldo, Inga Carboni and Klarissa Chang. Their work appears in journals such as interactions, Memory & Cognition, ACM Transactions on Information Systems, Human Resource Management and Proceedings of the IEEE.

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.

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