Scott Spangler

33 papers receiving 635 citations

Peers

Scott Spangler
Comparison fields: 5 of 114
  • Health Informatics 31
  • Management Information Systems 62
  • Artificial Intelligence 223
  • Information Systems and Management 43
  • Information Systems 136
Replace Yongjun Zhu with:
Yongjun Zhu South Korea
Oya Beyan Germany
Markus Bundschus Germany
Erik M. van Mulligen Netherlands
Xiaodong Feng China
Simon Baker United Kingdom
Tania Tudorache United States
Francisco M. Couto Portugal
Adriane Chapman United Kingdom
John R. Talburt United States
Scott Spangler relative to Yongjun Zhu South Korea Yongjun Zhu's profile →
Citations per field
00.5×
Yongjun Zhu · 1×
Citations per year

Countries citing papers authored by Scott Spangler

Since Specialization
Citations

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

Fields of papers citing papers by Scott Spangler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20201
2
Accelerating Discovery: Mining Unstructured Information for Hypothesis Generation
20203
3 20198
4 20195
5 20185
6 20189
7 2017103
8 20160
9 201511
10 20123
11 201110
12 20104
13 201029
14 200918
15
Mining the Talk: Unlocking the Business Value in Unstructured Information (IBM Press)
200710
16
Mining the Talk: Unlocking the Business Value in Unstructured Information
200727
17 200328
18 200216
19 20023
20 20016

About Scott Spangler

Scott Spangler is a scholar working on Library and Information Sciences, Information Systems and Management, Management Information Systems, Information Systems and Artificial Intelligence, having authored 34 papers that have together received 673 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (10 papers), Semantic Web and Ontologies (7 papers), Biomedical Text Mining and Ontologies (6 papers), Web Data Mining and Analysis (6 papers), Big Data and Business Intelligence (5 papers), Sentiment Analysis and Opinion Mining (4 papers), Scientific Computing and Data Management (4 papers) and Advanced Database Systems and Queries (3 papers). The work is most often cited by research in Health Informatics (31 citations), Management Information Systems (62 citations), Artificial Intelligence (223 citations), Information Systems and Management (43 citations) and Information Systems (136 citations). Scott Spangler has collaborated with scholars based in United States, China and Austria. Frequent co-authors include Jeffrey Kreulen, Ying Chen, Keke Cai, Jiawei Han, Alix M.B. Lacoste, Justin Lessler, Ying Chen, Ana Lelescu, Robert Bowser and Nadine Bakkar. Their work appears in journals such as Data Mining and Knowledge Discovery, Acta Neuropathologica, Proceedings of the American Society for Information Science and Technology, Analytical Chemistry and Journal of Management Information Systems.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026