Xiao Ding

2.3k citations
49 papers · 1.1k indexed · 2 hit papers · h-index 16
Topics
Topic Modeling (24 papers)Natural Language Processing Techniques (18 papers)Stock Market Forecasting Methods (5 papers)
Partner nations
ChinaSingaporeSweden

In The Last Decade

Xiao Ding

44 papers receiving 1.1k citations

Hit Papers

Deep learning for event-driven stock prediction201520262018202220152024100200300

Peers

Xiao Ding
Comparison fields: 5 of 114
  • Artificial Intelligence 516
  • Management Science and Operations Research 504
  • Finance 219
  • Economics and Econometrics 212
  • Electrical and Electronic Engineering 171
Replace Lai Xu with:
Lai Xu United States
Rui Mao Singapore
Paul D. Feigin Israel
Yuanzhu Chen Canada
Joseph D. Petruccelli United States
Kiyoaki Shirai Japan
Hakan Gündüz Türkiye
Ling He China
Yingheng Wang China
Khaled H. Alyoubi Saudi Arabia
Xiao Ding relative to Lai Xu United States Lai Xu's profile →
Citations per field
00.5×5.6×
Lai Xu · 1×
Citations per year

Countries citing papers authored by Xiao Ding

Since Specialization
Citations

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

Fields of papers citing papers by Xiao Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiao Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Xiao Ding. A scholar is included among the top collaborators of Xiao Ding based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xiao Ding. Xiao Ding is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 2
3 0
4 0
5 2
6 3
7 2
8 3
9 4
10 17
11 61
12 5
13 24
14
Generating Reasonable and Diversified Story Ending Using Sequence to Sequence Model with Adversarial Training
17
15
Knowledge-Driven Event Embedding for Stock Prediction
63
16
Deep learning for event-driven stock predictionbreakdown →
344
17 1
18 160
19 2
20
Building Chinese Event Type Paradigm Based on Trigger Clustering
2

About Xiao Ding

Xiao Ding is a scholar working on Artificial Intelligence, Management Science and Operations Research and Biological Psychiatry, having authored 49 papers that have together received 1.1k indexed citations. Recurring topics across this work include Topic Modeling (24 papers), Natural Language Processing Techniques (18 papers) and Stock Market Forecasting Methods (5 papers). The work is most often cited by research in Management Science and Operations Research (504 citations), Finance (219 citations) and Artificial Intelligence (516 citations). Xiao Ding has collaborated with scholars based in China, Singapore and Sweden. Frequent co-authors include Junwen Duan, Ting Liu, Yue Zhang, Ting Liu, Yue Zhang, Ting Liu, Bing Qin, Zhongyang Li, Li Du and Yue Zhang. Their work appears in journals such as IEEE Access, Neuropharmacology and IEEE Transactions on Knowledge and Data Engineering.

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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