Tim O’Reilly

10.3k citations
44 papers · 2.2k indexed · 2 hit papers · h-index 11

Impact in

Papers in

Tim O’Reilly

39 papers receiving 1.9k citations

Hit Papers

What is Web 2.0 2009 · 543 citations
5430+6+12Years since publication250500750

Peers

Tim O’Reilly
Comparison fields: 5 of 127
  • Communication 550
  • Computer Science Applications 367
  • Information Systems and Management 184
  • Information Systems 593
  • Human-Computer Interaction 104
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Citations per year

Countries citing papers authored by Tim O’Reilly

Since Specialization
Citations

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

Fields of papers citing papers by Tim O’Reilly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tim O’Reilly. 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 Tim O’Reilly. The network helps show where Tim O’Reilly may publish in the future.

Co-authors

The 19 scholars most cited alongside Tim O’Reilly, 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 Tim O’Reilly Line = papers co-authored together Tim O’Reilly links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
What Is Web 2.0: Design Patterns and Business Models for the Next Generation of Software
Hit paper breakdown →
2007954
2
What is Web 2.0
Hit paper breakdown →
2009543
3 2011287
4 1999150
5
Exploring expect
199449
6
The Twitter Book
200934
7 199629
8 201929
9
X Toolkit Intrinsics Programming Manual
199026
10 202413
11
X Window System User's Guide
199012
12
Unix Power Tools
199310
13
X Toolkit intrinsics programming manual: second edition for X11, release 4
19908
14 20237
15 20156
16 19905
17 19975
18
Motif Reference Manual B: for OSF/Motif Release 1.2
19934
19
Unix power tools, third edition
20024
20 20114

About Tim O’Reilly

Tim O’Reilly is a scholar working on Information Systems, Computer Networks and Communications, Strategy and Management, Management Information Systems and Marketing, having authored 44 papers that have together received 2.2k indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (6 papers), Digital Platforms and Economics (3 papers), Blockchain Technology Applications and Security (2 papers), Scientific Computing and Data Management (2 papers), FinTech, Crowdfunding, Digital Finance (2 papers), Web and Library Services (2 papers), Mobile and Web Applications (1 paper) and Sharing Economy and Platforms (1 paper). The work is most often cited by research in Communication (550 citations), Computer Science Applications (367 citations), Information Systems and Management (184 citations), Information Systems (593 citations) and Human-Computer Interaction (104 citations). Tim O’Reilly has collaborated with scholars based in United Kingdom and United States. Frequent co-authors include Don Libes, Alison McMillan, Kelvin Leong, Mariana Mazzucato, Andrew P. Moore, Kevin A. Fall, Dale Dougherty, Mike Loukides, Josh Ryan‐Collins and Paula Ferguson. Their work appears in journals such as Communications of the ACM, Nature, IEEE Software, Information Economics and Policy and Oxford Review of Economic Policy.

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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