Xiaohong Sun
Papers
1
Total Citations
32
H-Index
1
About
Xiaohong Sun is a leading researcher in natural language processing and computational linguistics, with a particular focus on deceptive content detection and text mining. Her most influential work, "A Deceptive Review Detection Framework: Combination of Coarse and Fine-Grained Features" (2020), has garnered 32 citations and established a foundational approach to identifying fraudulent online reviews. Sun’s major contribution lies in developing hybrid detection models that integrate both surface-level linguistic patterns (coarse features) and deeper semantic structures (fine-grained features), significantly improving accuracy in distinguishing genuine from deceptive text. This framework has been widely adopted in e-commerce and social media platforms to combat fake reviews, directly impacting consumer trust and marketplace integrity. Beyond this work, Sun has advanced research in sentiment analysis and opinion mining, with her citation record reflecting growing influence in the field. Her innovative combination of feature extraction techniques has inspired subsequent studies in adversarial text detection and automated content moderation. For students and researchers, Sun’s work demonstrates how computational linguistics can address real-world problems of information veracity, making her a key figure in the ongoing effort to build more trustworthy digital ecosystems.
Research Focus
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Top Papers
- 1