Xiaowen Ding

2.3k total citations · 1 hit paper
23 papers, 1.5k citations indexed

About

Xiaowen Ding is a scholar working on Cancer Research, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Xiaowen Ding has authored 23 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cancer Research, 7 papers in Molecular Biology and 5 papers in Artificial Intelligence. Recurrent topics in Xiaowen Ding's work include Breast Cancer Treatment Studies (5 papers), Sentiment Analysis and Opinion Mining (4 papers) and Advanced Text Analysis Techniques (3 papers). Xiaowen Ding is often cited by papers focused on Breast Cancer Treatment Studies (5 papers), Sentiment Analysis and Opinion Mining (4 papers) and Advanced Text Analysis Techniques (3 papers). Xiaowen Ding collaborates with scholars based in China and United States. Xiaowen Ding's co-authors include Bing Liu, Philip S. Yu, Bing Liu, Lei Zhang, John E. Hopcroft, Zhanpeng Fang, Jie Tang, Tiancheng Lou, Xingfei Zheng and Xin Wang and has published in prestigious journals such as Cancer Research, European Journal of Cancer and International Journal of Environmental Research and Public Health.

In The Last Decade

Xiaowen Ding

23 papers receiving 1.4k citations

Hit Papers

A holistic lexicon-based approach to opinion mining 2008 2026 2014 2020 2008 250 500 750

Peers

Xiaowen Ding
Comparison fields: 5 of 121
  • Artificial Intelligence 1.1k
  • Information Systems 326
  • Sociology and Political Science 173
  • Molecular Biology 150
  • Statistical and Nonlinear Physics 116
Replace Mário J. Silva with:
Mário J. Silva Portugal
Naoaki Okazaki Japan
Michael Welge United States
Qinke Peng China
Xuan Wang China
Ming Fan China
Giannis Tzimas Greece
Xi Niu United States
Wahab Khan Pakistan
Tiantian Qin China
Mário J. Silva Portugal View profile →
Citations per field, relative to Xiaowen Ding
Xiaowen Ding · 1×
Citations per year, relative to Xiaowen Ding
Xiaowen Ding · 1×

Countries citing papers authored by Xiaowen Ding

Since Specialization
Citations

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

Fields of papers citing papers by Xiaowen Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaowen Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaowen Ding. A scholar is included among the top collaborators of Xiaowen 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 Xiaowen Ding. Xiaowen 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
# Work Indexed citations
1 7
2 1
3 1
4 57
5 10
6 1
7 38
8 10
9 25
10 76
11 4
12 4
13 30
14 52
15 5
16 80
17
Resolving Object and Attribute Coreference in Opinion Mining
24
18 71
19
A holistic lexicon-based approach to opinion mining breakdown →
881
20 148

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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