Xiaodan Zhu

10.8k total citations · 5 hit papers
181 papers, 5.5k citations indexed

About

Xiaodan Zhu is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Molecular Biology. According to data from OpenAlex, Xiaodan Zhu has authored 181 papers receiving a total of 5.5k indexed citations (citations by other indexed papers that have themselves been cited), including 116 papers in Artificial Intelligence, 23 papers in Computer Vision and Pattern Recognition and 16 papers in Molecular Biology. Recurrent topics in Xiaodan Zhu's work include Topic Modeling (82 papers), Natural Language Processing Techniques (54 papers) and Sentiment Analysis and Opinion Mining (22 papers). Xiaodan Zhu is often cited by papers focused on Topic Modeling (82 papers), Natural Language Processing Techniques (54 papers) and Sentiment Analysis and Opinion Mining (22 papers). Xiaodan Zhu collaborates with scholars based in Canada, China and United States. Xiaodan Zhu's co-authors include Svetlana Kiritchenko, Saif M. Mohammad, Colin Cherry, Seyed Mohammad, Parinaz Sobhani, Joel Martin, Zhenming Liu, Zhen-Hua Ling, Diana Inkpen and Hongyu Guo and has published in prestigious journals such as Journal of Hazardous Materials, Physics Letters B and Journal of Chromatography A.

In The Last Decade

Xiaodan Zhu

164 papers receiving 5.2k citations

Hit Papers

5 papers align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Sentiment Analysis of Short Informal Texts

2014 588 citations Svetlana Kiritchenko, Xiaodan Zhu et al. Journal of Artificial Intelligence Research profile →
SemEval-2016 Task 6: Detecting Stance in Tweets

2016 488 citations Saif M. Mohammad, Svetlana Kiritchenko et al. NPARC profile →
NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews

2014 470 citations Svetlana Kiritchenko, Xiaodan Zhu et al. NPARC profile →
NRC-Canada: Building the State-of-the-Art in Sentiment Analysis of Tweets

2013 328 citations Saif M. Mohammad, Svetlana Kiritchenko et al. profile →
DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics

2018 309 citations Xukan Ran, Xiaodan Zhu et al. profile →

Peers

Countries citing papers authored by Xiaodan Zhu

Since Specialization

Citations

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

Fields of papers citing papers by Xiaodan Zhu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaodan Zhu

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaodan Zhu. A scholar is included among the top collaborators of Xiaodan Zhu 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 Xiaodan Zhu. Xiaodan Zhu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

#	Work	Indexed citations
1	Economic Policy Uncertainty and Digital Finance Development: Evidence From 30 Regions in China 2025 ·International Journal of Finance & Economics ·Chengdong Wang, (unknown), (unknown), Xiaodan Zhu	0
2	Targeted generative data augmentation for automatic metastases detection from free-text radiology reports 2025 ·Frontiers in Artificial Intelligence ·(unknown), Xiaodan Zhu, (unknown), Amber L. Simpson, Richard Kinh Gian	2
3	Early detection, clinicopathological subtyping, and prognosis prediction for endometrial cancer patients using fragmentomics liquid biopsy assay 2025 ·ESMO Open ·Qing Rao, Hui Zhou, Wen-Kai Weng, Yazhou He, (unknown), Pingping He, Wanxiangfu Tang, (unknown), Xiaodan Zhu, Dan Zhu, (unknown), Xue Wu, (unknown), Zhixiong Lin, Bingnan Zhang	1
4	Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs 2024 ·TUbilio (Technical University of Darmstadt) ·(unknown), (unknown), (unknown), Xiaodan Zhu, Iryna Gurevych	1
5	Fine-Tuning Language Models with Differential Privacy through Adaptive Noise Allocation 2024 ·Xianzhi Li, (unknown), Zhiqiang Ma, Xiaomo Liu, Xiaodan Zhu	1
6	HGOT: Hierarchical Graph of Thoughts for Retrieval-Augmented In-Context Learning in Factuality Evaluation 2024 ·(unknown), Stephen H. Thomas, Xiaodan Zhu	2
7	Misinformation with Legal Consequences (MisLC): A New Task Towards Harnessing Societal Harm of Misinformation 2024 ·(unknown), (unknown), (unknown), (unknown), Xiaodan Zhu	0
8	A Simple and Effective Framework for Strict Zero-Shot Hierarchical Classification 2023 ·(unknown), Lei Chen, Xiaodan Zhu	5
9	Spatial Justice and Residents’ Policy Acceptance: Evidence from Construction Land Reduction in Shanghai, China 2023 ·Land ·Keqiang Wang, (unknown), Hongmei Liu, (unknown), (unknown), Xiaodan Zhu	8
10	Effectiveness of Data Augmentation for Parameter Efficient Tuning with Limited Data 2023 ·NPARC ·(unknown), Hongyu Guo, Xiaodan Zhu	1
11	Dispersive solid‐phase extraction combined with dispersive liquid‐liquid microextraction for simultaneous determination of seven succinate dehydrogenase inhibitor fungicides in watermelon by ultra high performance liquid chromatography with tandem mass spectrometry 2019 ·Journal of Separation Science ·Junxue Wu, (unknown), Chunhong Jia, Xinghai Li, Xiaodan Zhu, Ercheng Zhao	16
12	DeepDecision: A Mobile Deep Learning Framework for Edge Video Analytics breakdown → 2018 ·Xukan Ran, (unknown), Xiaodan Zhu, Zhenming Liu, Jiasi Chen	309
13	A Dataset for Multi-Target Stance Detection 2017 ·Parinaz Sobhani, Diana Inkpen, Xiaodan Zhu	87
14	SemEval-2016 Task 6: Detecting Stance in Tweets breakdown → 2016 ·NPARC ·Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, Colin Cherry	488
15	Residue behavior and dietary intake risk assessment of three fungicides in tomatoes (Lycopersicon esculentum Mill.) under greenhouse conditions 2016 ·Regulatory Toxicology and Pharmacology ·Xiaodan Zhu, Chunhong Jia, (unknown), Wei Zhang, Pingzhong Yu, Min He, Li Chen, Ercheng Zhao	21
16	A Dataset for Detecting Stance in Tweets. 2016 ·Language Resources and Evaluation ·Saif M. Mohammad, Svetlana Kiritchenko, Parinaz Sobhani, Xiaodan Zhu, Colin Cherry	47
17	Residue behavior and dietary intake risk assessment of kresoxim-methyl and procymidone in strawberry under greenhouse conditions 2015 ·(unknown), Xiaodan Zhu, Zuntao Zheng, Chunhong Jia, (unknown), Min He	2
18	Sentiment Analysis of Short Informal Texts breakdown → 2014 ·Journal of Artificial Intelligence Research ·Svetlana Kiritchenko, Xiaodan Zhu, Seyed Mohammad	588
19	Sentiment Analysis of Social Media Texts 2014 ·Empirical Methods in Natural Language Processing ·Saif M. Mohammad, Xiaodan Zhu	0
20	A Critical Reassessment of Evaluation Baselines for Speech Summarization 2008 ·Meeting of the Association for Computational Linguistics ·Gerald Penn, Xiaodan Zhu	48

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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