Tun Lu

2.2k citations
124 papers · 1.3k · 1 hit paper · h-index 20

Impact in

Papers in

    • Recommender Systems and Techniques 35
    • Service-Oriented Architecture and Web Services 11
    • Expert finding and Q&A systems 8
    • Topic Modeling 12
    • Advanced Graph Neural Networks 10

Tun Lu

112 papers receiving 1.3k citations

Tun Lu's Hit Papers

Cross-modal Ambiguity Learning for Multimodal Fake News Detection 2022 · 166 citations
1660+1+2Years since publication50100150

Peers

Tun Lu
Comparison fields: 5 of 146
  • Information Systems 609
  • Human-Computer Interaction 129
  • Computer Science Applications 90
  • Artificial Intelligence 496
  • Communication 83
Replace Ning Gu with:
Ning Gu China
Deirdre K. Mulligan United States
Denis Parra Chile
Eelco Herder Germany
Nithya Sambasivan United States
Longqi Yang United States
Amos Azaria Israel
Costas Vassilakis Greece
Ignacio Aedo Spain
Yoram Bachrach United Kingdom
Tun Lu relative to Ning Gu China Ning Gu's profile →
Citations per field
00.5×1.7×
Ning Gu · 1×
Citations per year

Countries citing papers authored by Tun Lu

Since Specialization
Citations

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

Fields of papers citing papers by Tun Lu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 124 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Cross-modal Ambiguity Learning for Multimodal Fake News Detection
Hit paper breakdown →
2022166
2 201479
3 201667
4 201550
5 201643
6 201436
7 201536
8 201735
9 201135
10 201632
11 202125
12 202025
13 201123
14 201623
15 201722
16 202121
17 202221
18 201120
19 201420
20 201120

About Tun Lu

Tun Lu is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Human-Computer Interaction and Communication, having authored 124 papers that have together received 1.3k indexed citations. Recurring topics across this work include Recommender Systems and Techniques (35 papers), Topic Modeling (12 papers), Service-Oriented Architecture and Web Services (11 papers), Advanced Graph Neural Networks (10 papers), Complex Network Analysis Techniques (9 papers), Usability and User Interface Design (9 papers), Caching and Content Delivery (9 papers) and Expert finding and Q&A systems (8 papers). The work is most often cited by research in Information Systems (609 citations), Human-Computer Interaction (129 citations), Computer Science Applications (90 citations), Artificial Intelligence (496 citations) and Communication (83 citations). Tun Lu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Ning Gu, Dongsheng Li, Peng Zhang, Li Shang, Qin Lv, Hansu Gu, Xianghua Ding, Dongsheng Li, Jie Sui and Yixuan Chen. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, ACM Transactions on the Web, Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Knowledge-Based Systems and International Journal of Human-Computer Interaction.

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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