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Article
Computer Science, Artificial Intelligence
Xiaonan Gao et al.
Summary: Identifying experts in a specific research field is important in academia and industry. Existing methods rely on text mining and are time-consuming and imprecise. This study proposes a new expert finding model, TOSA, which can identify representative authors in a specific research topic directly from a heterogeneous academic network without text data processing.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Sarmistha Sarna Gomasta et al.
Summary: Online Social Networks (OSNs) are crucial for viral promoting applications and education. Identifying influential users in OSNs is a research problem, with less attention paid to temporal factors. We propose a temporal activity-biased weight model and an algorithm to list the most influential users. Experimental results demonstrate the effectiveness of our approach compared to the baseline method.
APPLIED INTELLIGENCE
(2022)
Article
Mathematics, Applied
Fulian Yin et al.
Summary: The study introduces a multiple-related susceptible-forwarding-immunized model to investigate the impact of users' repeated forwarding behaviors on the dynamics of topic propagation. Data fitting using real data shows that user behavior influences information dissemination, and sensitivity analyses offer strategies for effective dissemination.
APPLIED MATHEMATICS LETTERS
(2022)
Article
Mathematics, Interdisciplinary Applications
Fuzhong Nian et al.
Summary: This research examines information dissemination on Weibo, a Twitter-like service in China, to gain insights into the trend of network propagation. It also investigates core users on the internet, which is crucial for controlling network public opinion.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Multidisciplinary
Baojun Fu et al.
Summary: This paper analyzes the impact of node interactions in dynamic social networks on information dissemination and proposes a two-stage influence maximization solution algorithm based on node degree and effective links.
Article
Computer Science, Information Systems
Guixun Luo et al.
Summary: User interaction plays a vital role in network public opinion formation, but the physical phenomena of individual interaction are difficult to describe and explain mathematically. By studying micro individuals and their interaction process, we found that friends with higher preference have a higher frequency of interaction compared to friends with lower preference. We established a mathematical model to describe user interaction behavior and analyzed its distribution and time characteristics through theoretical analysis, simulation experiments, and empirical analysis of Weibo data.
INFORMATION SCIENCES
(2022)
Article
Mathematics, Interdisciplinary Applications
Yan Wang et al.
Summary: This article addresses the importance of identifying influential nodes in a network and proposes a new centrality measure and a heuristic algorithm for filtering propagators. Experimental results show that the new centrality measure is more accurate and effective, while the heuristic algorithm improves both spread speed and infection scale.
CHAOS SOLITONS & FRACTALS
(2022)
Article
Physics, Multidisciplinary
Hailu Yang et al.
Summary: Community detection in semantic social networks is a crucial issue in online social network analysis. We propose a Gaming-based Topic Influence Percolation model (GTIP) for semantic overlapping community detection. Compared with conventional and representative methods, GTIP achieves better performance in synthetic and real networks.
Article
Business
Zaoli Yang et al.
Summary: This study utilized various techniques to analyze content related to intellectual property on Weibo and WeChat in China, identifying 16 topics associated with IP, most of which showed high levels of positive sentiment. The development trends of sentiment and topics are easily affected by abnormal events, leading to noticeable fluctuations.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2022)
Article
Business
Sulemana Bankuoru Egala et al.
Summary: This study explores the impact of source credibility and content reliability on users' perception of the quality of health-related information on social media during the COVID-19 pandemic. The results indicate that content reliability significantly influences users' perceived quality, while source credibility does not have an impact. This study has important theoretical and practical implications for users' choice and consumption of health-related information on social media platforms.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2022)
Article
Computer Science, Artificial Intelligence
Roy Ka-Wei Lee et al.
Summary: Identifying influential users in online social networks is crucial, and the proposed MPHAT model extends existing models to determine influential users across multiple OSNs, outperforming in platform prediction and link recommendation tasks. The model demonstrates the ability to learn topics effectively while addressing platform preferences.
IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
(2021)
Article
Computer Science, Information Systems
Lien-Fa Lin et al.
Summary: Researchers focus on influential nodes in social networks for information dissemination, proposing a new algorithm to minimize the total cost for users to receive information.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Artificial Intelligence
Wentao Ye et al.
Summary: The identification of vital users on the Sina Weibo network is crucial. This study proposed an end-to-end computational model based on a deep graph neural network, incorporating a simplified graph attention mechanism to integrate information from both follower and followee networks, achieving high detection accuracy while maintaining low computational cost.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Yanan Wang et al.
Summary: Online social networks have changed the way people exchange information, and user mobility affects information diffusion. A new information diffusion model is established, and theoretical analysis and experimental validation show the model is reliable.
INFORMATION SCIENCES
(2021)
Article
Computer Science, Information Systems
Qiuyan Shang et al.
Summary: The identification of important nodes in complex networks is a rapidly growing field, with various proposed measures needing to comprehensively consider both global and local information as well as static and dynamic data. A new gravity model with effective distance has been introduced to address this, showing effectiveness through simulation on different real networks.
INFORMATION SCIENCES
(2021)
Article
Physics, Multidisciplinary
Pei Li et al.
Summary: This study introduces a duplicate forwarding model to characterize the diffusion process in social networks and theoretically analyze the user influence in the independent cascade model. After obtaining user influence ranking, a Spearman-like correlation coefficient is proposed to measure the correlation between rankings, showing that the analysis results from the duplicate forwarding model achieve better accuracy in estimating user influence ranking compared to traditional methods.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Zou Xiaomei et al.
Summary: This study proposes a collaborative microblog sentiment analysis approach based on personalized sentiment analysis methods and utilizing social context information, which can effectively improve the performance of microblog sentiment classification.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Jiameng Gao et al.
Summary: This paper proposes a hybrid microblog recommendation approach based on a deep neural network, incorporating user interest tags and topics, describing candidate microblogs with features and utilizing collaborative filtering to obtain recommended microblogs. Experimental results demonstrate that the proposed method significantly outperforms existing methods.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Pengli Lu et al.
Journal of Shanghai Jiaotong University (Science)
(2021)
Article
Construction & Building Technology
Nidal Nasser et al.
Summary: This paper introduces a framework that categorizes and processes tweets using N-gram and machine learning techniques to identify COVID-19 positive patients.
SUSTAINABLE CITIES AND SOCIETY
(2021)
Article
Multidisciplinary Sciences
Yun-Bei Zhuang et al.
Summary: Online social networks have heterogeneous nature, with influencers playing significant roles in various aspects. This paper introduces a multi-dimensional social influence measurement approach, utilizing structure-based, information-based, and action-based factors to assess users' influence. Experimental results demonstrate the effectiveness of the proposed framework in evaluating users' influence on both topic-level and global-level within social networks.
Article
Information Science & Library Science
Pianpian Wang et al.
Summary: This study investigates how retweeting behavior increases attention to specific issues on the largest Chinese microblogging website, showing that verified users and social media publics have different patterns of retweets and that amplification of different types of issues exhibit systematically different temporalities. The findings provide insights into the possibilities and limitations of grassroots empowerment through social media in China.
TELEMATICS AND INFORMATICS
(2021)
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Computer Science, Artificial Intelligence
Ahmad Zareie et al.
KNOWLEDGE-BASED SYSTEMS
(2020)
Article
Physics, Multidisciplinary
Nouran Ayman R. Abd Al-Azim et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2020)
Article
Physics, Multidisciplinary
Sanjay Kumar et al.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2020)
Article
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En-Yu Yu et al.
KNOWLEDGE-BASED SYSTEMS
(2020)
Review
Computer Science, Artificial Intelligence
Giridhar Maji et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2020)
Proceedings Paper
Computer Science, Information Systems
Hongbo Bo et al.
WWW'20: COMPANION PROCEEDINGS OF THE WEB CONFERENCE 2020
(2020)
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Zhongying Zhao et al.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2019)
Proceedings Paper
Computer Science, Theory & Methods
Lin Jiangpeng et al.
2019 INTERNATIONAL CONFERENCE ON CYBER-ENABLED DISTRIBUTED COMPUTING AND KNOWLEDGE DISCOVERY (CYBERC)
(2019)
Review
Computer Science, Artificial Intelligence
Ifeyinwa Angela Ajah et al.
BIG DATA AND COGNITIVE COMPUTING
(2019)
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Alpaslan Burak Eliacik et al.
EXPERT SYSTEMS WITH APPLICATIONS
(2018)
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Computer Science, Artificial Intelligence
Zeynep Zengin Alp et al.
KNOWLEDGE-BASED SYSTEMS
(2018)
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Siwar Jendoubi et al.
KNOWLEDGE-BASED SYSTEMS
(2017)
Article
Computer Science, Information Systems
Zhao Jianqiang et al.
Article
Multidisciplinary Sciences
Jian-Xiong Zhang et al.
SCIENTIFIC REPORTS
(2016)
