Lane Harrison

1.7k citations
70 papers · 1.1k indexed · h-index 17

Lane Harrison

62 papers receiving 1.0k citations

Peers

Lane Harrison
Comparison fields: 5 of 113
  • Computer Vision and Pattern Recognition 623
  • Chemical Health and Safety 17
  • Human-Computer Interaction 126
  • Cognitive Neuroscience 187
  • Computer Science Applications 50
Replace Alvitta Ottley with:
Alvitta Ottley United States
Danielle Albers Szafir United States
Caroline Ziemkiewicz United States
Ioannis Arapakis Spain
Anastasia Bezerianos France
Marko Tkalčič Slovenia
Younah Kang South Korea
Fanny Chevalier Canada
Vidya Setlur United States
Lane Harrison relative to Alvitta Ottley United States Alvitta Ottley's profile →
Citations per field
00.5×2.9×
Alvitta Ottley · 1×
Citations per year

Countries citing papers authored by Lane Harrison

Since Specialization
Citations

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

Fields of papers citing papers by Lane Harrison

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Lane Harrison, 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 Lane Harrison Line = papers co-authored together Lane Harrison links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20245
2 20246
3 20240
4 20243
5 20245
6 20237
7 20230
8 202312
9 20231
10 20228
11 20227
12 202023
13 20205
14 20209
15 20186
16 20170
17 201569
18
The role of emotion in visualization
20136
19 20127
20 20108

About Lane Harrison

Lane Harrison is a scholar working on Computer Vision and Pattern Recognition, Computer Science Applications, General Decision Sciences, Experimental and Cognitive Psychology and Statistical and Nonlinear Physics, having authored 70 papers that have together received 1.1k indexed citations. Recurring topics across this work include Data Visualization and Analytics (47 papers), Complex Network Analysis Techniques (11 papers), Advanced Text Analysis Techniques (9 papers), Visual perception and processing mechanisms (7 papers), Mobile Crowdsensing and Crowdsourcing (6 papers), Multimedia Communication and Technology (6 papers), Aesthetic Perception and Analysis (5 papers) and Visual and Cognitive Learning Processes (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (623 citations), Chemical Health and Safety (17 citations), Human-Computer Interaction (126 citations), Cognitive Neuroscience (187 citations) and Computer Science Applications (50 citations). Lane Harrison has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Remco Chang, Steven Franconeri, Fumeng Yang, Evan M. Peck, Aidong Lu, Katharina Reinecke, Beste F. Yuksel, Daniel Afergan, Alvitta Ottley and Paul K. J. Han. Their work appears in journals such as IEEE Transactions on Visualization and Computer Graphics, Computer Graphics Forum, Journal of Imaging Science and Technology, International Journal of Human-Computer Interaction and Information Visualization.

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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