Xiaolong Zheng
Biographic Data
| ID | 4681988 |
|---|---|
| NAME | Xiaolong Zheng |
| GIVEN NAMES | Xiaolong |
| FAMILY NAME | Zheng |
| SIGNATURE | ZHENG X |
| AFFILIATIONS | Chinese Academy of Sciences |
| ORCID | 0000-0001-7950-6773 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Evaluating the collective effects of vertical and ground greening on microclimate and energy consumption in a high-density building array
Graph Representation Learning of Multilayer Spatial–Temporal Networks for Stock Predictions
Accurate stock market prediction is crucial for investors seeking significant profits. With increased economic activity, various interrelations between listed companies have become important for accurate predictions. These relations can be represented as complex financial networks, aiding the development of effective graph neural network (GNN) prediction methods. However, current GNN-based methods for stock prediction typically rely on a single s…
CGNN
With the rise and prevalence of social bots, their negative impacts on society are gradually recognized, prompting research attention to effective detection and countermeasures. Recently, graph neural networks (GNNs) have flourished and have been applied to social bot detection research, improving the performance of detection methods effectively. However, existing GNN-based social bot detection methods often fail to account for the heterogeneous …
Sora for Computational Social Systems
Welcome to the second issue of IEEE Transactions on Computational Social Systems (TCSS) of 2024. This issue showcases an impressive array of 104 regular papers alongside our Special Issue on Big Data and Computational Social Intelligence for Guaranteed Financial Security, highlighting cutting-edge research aimed at harnessing big data and computational techniques to fortify financial security amidst the digital finance evolution. With a focus on …
Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors
By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.–China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literatur…
Towards Human–Machine Recognition Alignment
The multimodality nature of web data has necessitated complex multimodal information retrieval for a wide range of web applications. Deep neural networks (DNNs) have been widely employed to extract semantic features from raw samples to improve retrieval accuracy. In addition, hashing is widely used to improve computational and storage efficiency. As such, deep hashing frameworks have been applied for multimodal retrieval tasks. However, there is …
Hashing Fake
The wide application of deep neural networks (DNNs) has significantly improved the performance of hashing models on multimodal retrieval issues. DNN-based deep models can automatically learn semantic features from raw data to make human-level decisions. However, the superior generalization leads to potential privacy leakage risks. Strong DNN-based retrieval models enable malicious crawlers to search for nontag private information based on semanti…
Game Starts at GameStop
In January 2021, the users of subreddit r/wallstreetbets (WSB) triggered an unprecedented short squeeze by driving up GameStop’s stock price to an unimaginable high point. During the event, a large number of users participated in the discussion about GameStop and coordinated trading behavior on r/WSB to push the stock price higher. In this article, we investigate the characteristics of the collective behaviors and social dynamics from the evoluti…
Evaluation and Spatial–Temporal Difference Analysis of Urban Water Resource Utilization Efficiency Based on Two-Stage DEA Model
In the present study, a two-stage data envelopment analysis (DEA) model and spatial econometric method were employed to evaluate and analyze the utilization efficiency of urban water resources and spatial–temporal differences in cities of China. The traditional DEA model was enhanced by adopting the Shannon entropy in the first stage. After selecting variables based on the previous step and the Bayes information criterion (BIC), redundant variabl…
Donald J. Trump’s Presidency in Cyberspace
In the past few years, with the rapid growth of digital technologies, Facebook, Twitter, and other social media platforms have become the digital oligarchies, which have the enormous capabilities to potentially control what is discussed in cyberspace. In the digital oligarchy era, social perception and social influence in different complex social systems have evolved quickly. In this article, we conducted large-scale empirical studies on social p…
Portrayal of electronic cigarettes on YouTube
The vast majority of information on YouTube about e-cigarettes promoted their use and depicted the use of e-cigarettes as socially acceptable. It is critical to develop appropriate health campaigns to inform e-cigarette consumers of potential harms associated with e-cigarette use
No prominent works on this page.
Portrayal of electronic cigarettes on YouTube
The vast majority of information on YouTube about e-cigarettes promoted their use and depicted the use of e-cigarettes as socially acceptable. It is critical to develop appropriate health campaigns to inform e-cigarette consumers of potential harms associated with e-cigarette use
Donald J. Trump’s Presidency in Cyberspace
In the past few years, with the rapid growth of digital technologies, Facebook, Twitter, and other social media platforms have become the digital oligarchies, which have the enormous capabilities to potentially control what is discussed in cyberspace. In the digital oligarchy era, social perception and social influence in different complex social systems have evolved quickly. In this article, we conducted large-scale empirical studies on social p…
Game Starts at GameStop
In January 2021, the users of subreddit r/wallstreetbets (WSB) triggered an unprecedented short squeeze by driving up GameStop’s stock price to an unimaginable high point. During the event, a large number of users participated in the discussion about GameStop and coordinated trading behavior on r/WSB to push the stock price higher. In this article, we investigate the characteristics of the collective behaviors and social dynamics from the evoluti…
Evaluation and Spatial–Temporal Difference Analysis of Urban Water Resource Utilization Efficiency Based on Two-Stage DEA Model
In the present study, a two-stage data envelopment analysis (DEA) model and spatial econometric method were employed to evaluate and analyze the utilization efficiency of urban water resources and spatial–temporal differences in cities of China. The traditional DEA model was enhanced by adopting the Shannon entropy in the first stage. After selecting variables based on the previous step and the Bayes information criterion (BIC), redundant variabl…
Analyzing the Stock Volatility Spillovers in Chinese Financial and Economic Sectors
By regarding the Chinese financial and economic sectors as a system, this article studies the stock volatility spillover in the system and explores its effects on the overall performance of the macroeconomy in China. The recent outbreak of COVID-19, U.S.–China trade friction, and three historical financial turbulences are involved to distinguish the changes in the spillover in these distinct crises, which has seldom been unveiled in the literatur…
Towards Human–Machine Recognition Alignment
The multimodality nature of web data has necessitated complex multimodal information retrieval for a wide range of web applications. Deep neural networks (DNNs) have been widely employed to extract semantic features from raw samples to improve retrieval accuracy. In addition, hashing is widely used to improve computational and storage efficiency. As such, deep hashing frameworks have been applied for multimodal retrieval tasks. However, there is …
Hashing Fake
The wide application of deep neural networks (DNNs) has significantly improved the performance of hashing models on multimodal retrieval issues. DNN-based deep models can automatically learn semantic features from raw data to make human-level decisions. However, the superior generalization leads to potential privacy leakage risks. Strong DNN-based retrieval models enable malicious crawlers to search for nontag private information based on semanti…
CGNN
With the rise and prevalence of social bots, their negative impacts on society are gradually recognized, prompting research attention to effective detection and countermeasures. Recently, graph neural networks (GNNs) have flourished and have been applied to social bot detection research, improving the performance of detection methods effectively. However, existing GNN-based social bot detection methods often fail to account for the heterogeneous …
Sora for Computational Social Systems
Welcome to the second issue of IEEE Transactions on Computational Social Systems (TCSS) of 2024. This issue showcases an impressive array of 104 regular papers alongside our Special Issue on Big Data and Computational Social Intelligence for Guaranteed Financial Security, highlighting cutting-edge research aimed at harnessing big data and computational techniques to fortify financial security amidst the digital finance evolution. With a focus on …
Graph Representation Learning of Multilayer Spatial–Temporal Networks for Stock Predictions
Accurate stock market prediction is crucial for investors seeking significant profits. With increased economic activity, various interrelations between listed companies have become important for accurate predictions. These relations can be represented as complex financial networks, aiding the development of effective graph neural network (GNN) prediction methods. However, current GNN-based methods for stock prediction typically rely on a single s…
Evaluating the collective effects of vertical and ground greening on microclimate and energy consumption in a high-density building array
Computer Science (9 works) · Artificial Intelligence (6 works) · World Wide Web (4 works) · Geography (3 works) · Psychology (3 works) · Social media (3 works) · Advanced Malware Detection Techniques (2 works) · Adversarial Robustness in Machine Learning (2 works) · China (2 works) · Computer security (2 works)