Ding Ding

452 citations
19 papers · 240 · 1 hit paper · h-index 7

Impact in

    • Artificial Intelligence in Healthcare and Education
  • Finance top 10%
    • Banking stability, regulation, efficiency
    • Financial Markets and Investment Strategies

Papers in

Ding Ding

16 papers receiving 230 citations

Ding Ding's Hit Papers

Generative AI: A systematic review using topic modelling techniques 2024 · 84 citations
840+1Years since publication255075

Peers

Ding Ding
Comparison fields: 5 of 69
  • Health Informatics 21
  • Finance 47
  • Economics and Econometrics 70
  • General Economics, Econometrics and Finance 18
  • Safety Research 16
Replace Hyungjin Ko with:
Hyungjin Ko South Korea
Christian Hugo Hoffmann Switzerland
Francesco Corea Italy
Eric Nielsen United States
Olubukola Omolara Adebiyi United States
K. Valerie Carl Germany
Kapil Vhatkar India
Omar Fares Canada
Benjamin Samson Ayinla United States
Nikolaus Lipusch Germany
Ding Ding relative to Hyungjin Ko South Korea Hyungjin Ko's profile →
Citations per field
00.5×2.7×
Hyungjin Ko · 1×
Citations per year

Countries citing papers authored by Ding Ding

Since Specialization
Citations

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

Fields of papers citing papers by Ding Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Ding Ding, 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 Ding Ding Line = papers co-authored together Ding Ding links everyone, so they are left out of the graph.

All Works

19 of 19 papers shown
#Work
1
Generative AI: A systematic review using topic modelling techniques
Hit paper breakdown →
202484
2 202052
3 201723
4 202322
5 202213
6 201211
7 202310
8 20126
9 20244
10 20224
11 20143
12 20242
13 20202
14 20252
15 20231
16 20231
17 20260
18 20250
19 20190

About Ding Ding

Ding Ding is a scholar working on Finance, Economics and Econometrics, Information Systems, General Economics, Econometrics and Finance and Health Informatics, having authored 19 papers that have together received 240 indexed citations. Recurring topics across this work include Global Financial Crisis and Policies (4 papers), Blockchain Technology Applications and Security (3 papers), Artificial Intelligence in Healthcare and Education (3 papers), Complex Systems and Time Series Analysis (3 papers), Computational and Text Analysis Methods (2 papers), FinTech, Crowdfunding, Digital Finance (2 papers), Global trade and economics (2 papers) and Aesthetic Perception and Analysis (2 papers). The work is most often cited by research in Health Informatics (21 citations), Finance (47 citations), Economics and Econometrics (70 citations), General Economics, Econometrics and Finance (18 citations) and Safety Research (16 citations). Ding Ding has collaborated with scholars based in Singapore, United States and China. Frequent co-authors include Chong Guan, Bosheng Ding, Priyanka Gupta, Wenting Liu, Calvin M. L. Chan, Libo Yin, Liyan Han, Yothin Jinjarak, Yannick Timmer and Yinghui Yu. Their work appears in journals such as Journal of Enterprise Information Management, Electronic Markets, Quantitative Finance, The North American Journal of Economics and Finance and Financial Innovation.

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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