A5058670321- Misinformation and Its Impacts
- Spam and Phishing Detection
- Topic Modeling
- Complex Network Analysis Techniques
- Sentiment Analysis and Opinion Mining
- Hate Speech and Cyberbullying Detection
- Natural Language Processing Techniques
- Advanced Malware Detection Techniques
- Multimodal Machine Learning Applications
- Advanced Graph Neural Networks
- Privacy-Preserving Technologies in Data
- Anomaly Detection Techniques and Applications
- Ethics and Social Impacts of AI
- Domain Adaptation and Few-Shot Learning
- Adversarial Robustness in Machine Learning
- Network Security and Intrusion Detection
- Opinion Dynamics and Social Influence
- Recommender Systems and Techniques
- Traffic Prediction and Management Techniques
- Privacy, Security, and Data Protection
- Advanced Text Analysis Techniques
- Authorship Attribution and Profiling
- Supercapacitor Materials and Fabrication
- Media Influence and Politics
- Data Stream Mining Techniques
Emory University
2024-2025
Huazhong University of Science and Technology
2020-2025
Illinois Institute of Technology
2020-2024
Chongqing University of Posts and Telecommunications
2022-2024
China Agricultural University
2024
Ningbo Transportation Planning and Design Institute (China)
2024
Sanya University
2024
Hefei University of Technology
2023
South China University of Technology
2021
University of Southern California
2021
Social media for news consumption is a double-edged sword. On the one hand, its low cost, easy access, and rapid dissemination of information lead people to seek out consume from social media. other it enables wide spread \fake news", i.e., quality with intentionally false information. The extensive fake has potential extremely negative impacts on individuals society. Therefore, detection recently become an emerging research that attracting tremendous attention. Fake presents unique...
Social media has become a popular means for people to consume and share the news. At same time, however, it also enabled wide dissemination of fake news, that is, news with intentionally false information, causing significant negative effects on society. To mitigate this problem, research detection recently received lot attention. Despite several existing computational solutions lack comprehensive community-driven data sets one major roadblocks. Not only are scarce, they do not contain...
Social media for news consumption is a double-edged sword. On the one hand, its low cost, easy access, and rapid dissemination of information lead people to seek out consume from social media. other it enables wide spread "fake news", i.e., quality with intentionally false information. The extensive fake has potential extremely negative impacts on individuals society. Therefore, detection recently become an emerging research that attracting tremendous attention. Fake presents unique...
In recent years, to mitigate the problem of fake news, computational detection news has been studied, producing some promising early results. While important, however, we argue that a critical missing piece study be explainability such detection, i.e., why particular is detected as fake. this paper, therefore, explainable news. We develop sentence-comment co-attention sub-network exploit both contents and user comments jointly capture top-k check-worthy sentences for detection. conduct...
Social media is becoming popular for news consumption due to its fast dissemination, easy access, and low cost. However, it also enables the wide propagation of fake news, i.e., with intentionally false information. Detecting an important task, which not only ensures users receive authentic information but helps maintain a trustworthy ecosystem. The majority existing detection algorithms focus on finding clues from contents, are generally effective because often written mislead by mimicking...
Consuming news from social media is becoming increasingly popular nowadays. Social brings benefits to users due the inherent nature of fast dissemination, cheap cost, and easy access. However, quality considered lower than traditional outlets, resulting in large amounts fake news. Detecting becomes very important attracting increasing attention detrimental effects on individuals society. The performance detecting only content generally not satisfactory, it suggested incorporate user...
Social media has become one of the main channels for people to access and consume news, due rapidness low cost news dissemination on it. However, such properties social also make it a hotbed fake dissemination, bringing negative impacts both individuals society. Therefore, detecting crucial problem attracting tremendous research effort. Most existing methods detection are supervised, which require an extensive amount time labor build reliably annotated dataset. In search alternative, in this...
The increasing popularity and diversity of social media sites has encouraged more people to participate on multiple online networks enjoy their services. Each user may create a identity, which can includes profile, content, or network information, represent his her unique public figure in every network. Thus, fundamental question arises -- we link identities across networks? User identity linkage is an emerging task attracted attention recent years. Advancements could potentially impact...
The explosive growth of fake news and its erosion to democracy, justice, public trust increased the demand for detection. As an interdisciplinary topic, study encourages a concerted effort experts in computer information science, political journalism, social psychology, economics. A comprehensive framework systematically understand detect is necessary attract unite researchers related areas conduct research on news. This tutorial aims clearly present (1) research, challenges, directions; (2)...
The rapid growth of Location-based Social Networks (LBSNs) provides a vast amount check-in data, which facilitates the study point-of-interest (POI) recommendation. majority existing POI recommendation methods focus on four aspects, i.e., temporal patterns, geographical influence, social correlations and textual content indications. For example, user's visits to locations have patterns users are likely visit POIs near them. In real-world LBSNs such as Instagram, can upload photos associating...
Social media has become a popular means for people to consume news. Meanwhile, it also enables the wide dissemination of fake news, i.e., news with intentionally false information, which brings significant negative effects society. Thus, detection is attracting increasing attention. However, non-trivial task, requires multi-source information such as content, social context, and dynamic information. First, written fool people, makes difficult detect simply based on contents. In addition...
Consuming news from social media is becoming increasingly popular. Social appeals to users due its fast dissemination of information, low cost, and easy access. However, also enables the widespread fake news. Due detrimental societal effects news, detecting has attracted increasing attention. detection performance only using contents generally not satisfactory as written mimic true Thus, there a need for an in-depth understanding on relationship between user profiles In this paper, we study...
Emotion plays an important role in detecting fake news online. When leveraging emotional signals, the existing methods focus on exploiting emotions of contents that conveyed by publishers (i.e., publisher emotion). However, often evokes high-arousal or activating people, so comments aroused crowd social emotion) should not be ignored. Furthermore, it remains to explored whether there exists a relationship between emotion and dual emotion), how appears news. In this paper, we verify is...
Disinformation and fake news have posed detrimental effects on individuals society in recent years, attracting broad attention to detection. The majority of existing detection algorithms focus mining content and/or the surrounding exogenous context for discovering deceptive signals; while endogenous preference a user when he/she decides spread piece or not is ignored. confirmation bias theory has indicated that more likely it confirms his/her beliefs/preferences. Users' historical, social...
Consuming news from social media is becoming increasingly popular. However, also enables the wide dissemination of fake news. Because detrimental effects news, detection has attracted increasing attention. performance detecting only content generally limited as pieces are written to mimic true In real world, spread through propagation networks on media. The usually involve multi-levels. this paper, we study challenging problem investigating and exploiting hierarchical network for...
An infodemic is an overflow of information varying quality that surges across digital and physical environments during acute public health event. It leads to confusion, risk-taking, behaviors can harm lead erosion trust in authorities responses. Owing the global scale high stakes emergency, responding related pandemic particularly urgent. Building on diverse research disciplines expanding discipline infodemiology, more evidence-based interventions are needed design management tools implement...
The wide spread of fake news is increasingly threatening both individuals and society. Great efforts have been made for automatic detection on a single domain (e.g., politics). However, correlations exist commonly across multiple domains, thus it promising to simultaneously detect domains. Based our analysis, we pose two challenges in multi-domain detection: 1) shift, caused by the discrepancy among domains terms words, emotions, styles, etc. 2) labeling incompleteness, stemming from...
Abstract Misinformation such as fake news and rumors is a serious threat for information ecosystems public trust. The emergence of large language models (LLMs) has great potential to reshape the landscape combating misinformation. Generally, LLMs can be double‐edged sword in fight. On one hand, bring promising opportunities misinformation due their profound world knowledge strong reasoning abilities. Thus, emerging question is: we utilize combat misinformation? other critical challenge that...
The wide dissemination of fake news has affected our lives in many aspects, making detection important and attracting increasing attention. Existing approaches make substantial contributions this field by modeling from a single-modal or multi-modal perspective. However, these modal-based methods can result sub-optimal outcomes as they ignore reader behaviors consumption authenticity verification. For instance, haven't taken into consideration the component-by-component reading process:...
Abstract The creation, dissemination, and consumption of disinformation fabricated content on social media is a growing concern, especially with the ease access to such sources, lack awareness existence false information. In this article, we present an overview techniques explored date for combating various forms. We introduce different forms disinformation, discuss factors related spread elaborate inherent challenges in detecting show some approaches mitigating via education, research,...