Dosam Hwang

2.6k citations
119 papers · 1.2k indexed · h-index 17

Impact in

Papers in

Dosam Hwang

106 papers receiving 1.1k citations

Peers

Dosam Hwang
Comparison fields: 5 of 103
  • Artificial Intelligence 550
  • Information Systems 334
  • Electronic, Optical and Magnetic Materials 183
  • Signal Processing 68
  • Statistical and Nonlinear Physics 78
Replace Abhijnan Chakraborty with:
Abhijnan Chakraborty India
Sotiris Ioannidis Greece
Fabrício Murai Japan
Yafei Dai China
Han Guo China
Gabriele Lenzini Luxembourg
Ivan Titov United Kingdom
Yong Ren China
Dosam Hwang relative to Abhijnan Chakraborty India Abhijnan Chakraborty's profile →
Citations per field
00.5×
Abhijnan Chakraborty · 1×
Citations per year

Countries citing papers authored by Dosam Hwang

Since Specialization
Citations

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

Fields of papers citing papers by Dosam Hwang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 202363
3 20233
4 20231
5 20211
6 202071
7 20184
8
Development of a Version-Compatible HL7 Parser
20180
9 20162
10
SOCIAL DATA VISUALIZATION SYSTEM FOR UNDERSTANDING DIFFUSION PATTERNS ON TWITTER: A CASE STUDY ON KOREAN ENTERPRISES
20146
11
Named Entity Corpus Construction using Wikipedia and DBpedia Ontology
20148
12 20120
13 20092
14 20062
15 20060
16 19997
17 19989
18
Magnetoresistance of CO / Cu / CO Spin Valve Sandwiches
19973
19 19926
20 199011

About Dosam Hwang

Dosam Hwang is a scholar working on Electronic, Optical and Magnetic Materials, Information Systems, Artificial Intelligence, Atomic and Molecular Physics, and Optics and Statistical and Nonlinear Physics, having authored 119 papers that have together received 1.2k indexed citations. Recurring topics across this work include Magnetic properties of thin films (37 papers), Magnetic Properties and Applications (25 papers), Advanced Text Analysis Techniques (16 papers), Topic Modeling (13 papers), Sentiment Analysis and Opinion Mining (12 papers), ZnO doping and properties (12 papers), Complex Network Analysis Techniques (11 papers) and Spam and Phishing Detection (10 papers). The work is most often cited by research in Artificial Intelligence (550 citations), Information Systems (334 citations), Electronic, Optical and Magnetic Materials (183 citations), Signal Processing (68 citations) and Statistical and Nonlinear Physics (78 citations). Dosam Hwang has collaborated with scholars based in South Korea, Poland and Vietnam. Frequent co-authors include Ngoc Thanh Nguyên, Huyen Trang Phan, Cuong Tran, Sang‐Suk Lee, Jason J. Jung, Jai E. Jung, Hamido Fujita, O‐Joun Lee, Van Nguyen and Gottfried Vossen. Their work appears in journals such as Journal of Magnetism and Magnetic Materials, IEEE Transactions on Magnetics, IEEE Access, Journal of Applied Physics and Journal of Intelligent & Fuzzy 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.

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