What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- The Internet
Suhang Wang focuses on Social media, Fake news, Information retrieval, Internet privacy and Artificial intelligence.
His Social media research incorporates themes from Variety, Multimedia and Network embedding.
He has researched Fake news in several fields, including Exploit, Learning to rank and News media.
The study incorporates disciplines such as Perspective, Categorization, Data pre-processing and Big data in addition to Information retrieval.
His Perspective study combines topics in areas such as Similarity and Feature selection.
The Artificial intelligence study combines topics in areas such as Natural language processing and Pattern recognition.
His most cited work include:
- Fake News Detection on Social Media: A Data Mining Perspective (840 citations)
- Feature Selection: A Data Perspective (627 citations)
- What Your Images Reveal: Exploiting Visual Contents for Point-of-Interest Recommendation (145 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Artificial intelligence, Social media, Machine learning, Theoretical computer science and Fake news.
Artificial intelligence is often connected to Pattern recognition in his work.
His Social media research is multidisciplinary, incorporating perspectives in Data science, Information retrieval, User profile and Internet privacy.
Internet privacy and Information seeking are commonly linked in his work.
His work investigates the relationship between Theoretical computer science and topics such as Link that intersect with problems in Network embedding.
His Fake news study frequently draws connections between related disciplines such as Feature.
He most often published in these fields:
- Artificial intelligence (35.38%)
- Social media (24.62%)
- Machine learning (20.77%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (35.38%)
- Machine learning (20.77%)
- Graph neural networks (9.23%)
In recent papers he was focusing on the following fields of study:
Suhang Wang mainly investigates Artificial intelligence, Machine learning, Graph neural networks, Fake news and Theoretical computer science.
The various areas that he examines in his Machine learning study include Node, Embedding and Image.
Suhang Wang regularly ties together related areas like Social media in his Fake news studies.
Suhang Wang focuses mostly in the field of Social media, narrowing it down to topics relating to Attack model and, in certain cases, Threat model.
His studies in Theoretical computer science integrate themes in fields like Semi-supervised learning and Feature learning.
Suhang Wang has included themes like Disinformation and Misinformation in his Internet privacy study.
Between 2019 and 2021, his most popular works were:
- FakeNewsNet: A Data Repository with News Content, Social Context, and Spatiotemporal Information for Studying Fake News on Social Media (42 citations)
- Transferring Robustness for Graph Neural Network Against Poisoning Attacks (37 citations)
- Graph Structure Learning for Robust Graph Neural Networks (27 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- The Internet
His main research concerns Fake news, Graph neural networks, Theoretical computer science, Social media and Misinformation.
His research on Fake news concerns the broader Internet privacy.
Suhang Wang connects Internet privacy with Information repository in his research.
His research in Graph neural networks intersects with topics in Adversarial system, Embedding and Knowledge transfer.
His biological study spans a wide range of topics, including Feature learning and Robustness.
His studies link Feature with Social media.
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