Linjing Wu

542 citations
54 papers · 321 indexed · h-index 10

Impact in

Papers in

Linjing Wu

49 papers receiving 311 citations

Peers

Linjing Wu
Comparison fields: 5 of 88
  • Computer Science Applications 57
  • Human-Computer Interaction 42
  • Developmental and Educational Psychology 63
  • Health Informatics 4
  • Artificial Intelligence 86
Replace Huili Chen with:
Huili Chen United States
Dirk Börner Netherlands
Bosede Iyiade Edwards Malaysia
Rui Pedro Lopes Portugal
Yuh-Ming Cheng Taiwan
Nesra Yannier United States
Anne M. Sinatra United States
Chun-Chia Hsu Taiwan
Heidy Maldonado United States
Miguel Á. García-Ruiz Mexico
Linjing Wu relative to Huili Chen United States Huili Chen's profile →
Citations per field
00.5×
Huili Chen · 1×
Citations per year

Countries citing papers authored by Linjing Wu

Since Specialization
Citations

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

Fields of papers citing papers by Linjing Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
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4 20250
5 20251
6 20241
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8 20247
9 20241
10 202316
11 20234
12 202310
13 202219
14 20229
15 20221
16 20211
17 20213
18 201937
19 20191
20 20191

About Linjing Wu

Linjing Wu is a scholar working on Computer Science Applications, Human-Computer Interaction, Developmental and Educational Psychology, Health Informatics and Artificial Intelligence, having authored 54 papers that have together received 321 indexed citations. Recurring topics across this work include Online and Blended Learning (9 papers), Innovative Teaching and Learning Methods (9 papers), Online Learning and Analytics (8 papers), Virtual Reality Applications and Impacts (6 papers), Topic Modeling (4 papers), Augmented Reality Applications (4 papers), Electrocatalysts for Energy Conversion (3 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Computer Science Applications (57 citations), Human-Computer Interaction (42 citations), Developmental and Educational Psychology (63 citations), Health Informatics (4 citations) and Artificial Intelligence (86 citations). Linjing Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Qingtang Liu, Si Zhang, Ke Zhu, Wei Zhou, Kui Xie, Wanlei Zhou, Taotao Long, Xiang Liu, Xiangchun Shen and Ding Yuan. Their work appears in journals such as British Journal of Educational Technology, Education and Information Technologies, International Journal of Hydrogen Energy, Journal of Educational Computing Research and Scientific Reports.

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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