Loading [MathJax]/extensions/MathMenu.js
Yazhou Chen - IEEE Xplore Author Profile
Subscribe
ADVANCED SEARCH

Author details

< Back

Yazhou Chen

Also published under: Ya-zhou Chen, Ya-Zhou Chen

Publications
26
Citations
203
Publications by Year
20092025
Co-Authors:
Show All Co-Authors (40)
Image of author Yazhou Chen

Yazhou Chen

Also published under: Ya-zhou Chen, Ya-Zhou Chen

Affiliation

National Key Laboratory of Electromagnetic Environment Effects
Army Engineering University of PLA
Shijiazhuang, China

Publication Topics

Biography

Yazhou Chen (Member, IEEE) received the B.Eng., M.Eng., and Ph.D. degrees from Shijiazhuang Mechanical Engineering College, Shijiazhuang, China, in 1996, 1999, and 2002, respectively.,He is currently working as a Professor and the Director of the Key Laboratory on Electromagnetic Environment Effects, Shijiazhuang Mechanical Engineering College. His research areas of interests are EMC and lightning protection.(Based on document published on 20 June 2022).
Publications
26
Citations
203
Publications by Year
20092025
Co-Authors:
Show All Co-Authors (40)
Author's Published Works

Showing 1-25 of 27 results

  • Sort

Filter Results

Show

Sort By

Results

“Can You Play Anything Else?” Understanding Play Style Flexibility in League of Legends

Emily Chen;Alexander Bisberg;Emilio Ferrara

2024 IEEE Conference on Games (CoG)
Year: 2024 | Conference Paper |
Cited by: Papers (1)
This study investigates the concept of flexibility within League of Legends, a popular online multiplayer game, focusing on the relationship between user adaptability and team success. Utilizing a dataset encompassing players of varying skill levels and play styles, we calculate two measures of flexibility for each player: overall flexibility and temporal flexibility. Our findings suggest that the...Show More

“Can You Play Anything Else?” Understanding Play Style Flexibility in League of Legends

Emily Chen;Alexander Bisberg;Emilio Ferrara

Year: 2024 | Conference Paper |

Zero-Shot Meta-Learning for Small-Scale Data From Human Subjects

Julie Jiang;Kristina Lerman;Emilio Ferrara

2023 IEEE 11th International Conference on Healthcare Informatics (ICHI)
Year: 2023 | Conference Paper |
While developments in machine learning led to impressive performance gains on big data, many human subjects data are, in actuality, small and sparsely labeled. Existing methods applied to such data often do not easily generalize to out-of-sample subjects. Instead, models must make predictions on test data that may be drawn from a different distribution, a problem known as zero-shot learning. To ad...Show More

Zero-Shot Meta-Learning for Small-Scale Data From Human Subjects

Julie Jiang;Kristina Lerman;Emilio Ferrara

Year: 2023 | Conference Paper |

Tensor Embedding: A Supervised Framework for Human Behavioral Data Mining and Prediction

Homa Hosseinmardi;Amir Ghasemian;Kristina Lerman;Shrikanth Narayanan;Emilio Ferrara

2023 IEEE 11th International Conference on Healthcare Informatics (ICHI)
Year: 2023 | Conference Paper |
Cited by: Papers (1)
Today’s densely instrumented world offers tremendous opportunities for continuous acquisition and analysis of multimodal sensor data, providing temporal characterization of individual behaviors. Is it possible to efficiently couple such rich sensor data with predictive modeling techniques to provide contextual and insightful assessments of individual behavior? Such data is noisy, incomplete, and c...Show More

Tensor Embedding: A Supervised Framework for Human Behavioral Data Mining and Prediction

Homa Hosseinmardi;Amir Ghasemian;Kristina Lerman;Shrikanth Narayanan;Emilio Ferrara

Year: 2023 | Conference Paper |

GCN-WP – Semi-Supervised Graph Convolutional Networks for Win Prediction in Esports

Alexander J. Bisberg;Emilio Ferrara

2022 IEEE Conference on Games (CoG)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Win prediction is crucial to understanding skill modeling, teamwork and matchmaking in esports. In this paper we propose GCN-WP, a semi-supervised win prediction model for esports based on graph convolutional networks. This model learns the structure of an esports league over the course of a season (1 year) and makes predictions on another similar league. This model integrates over 30 features abo...Show More

GCN-WP – Semi-Supervised Graph Convolutional Networks for Win Prediction in Esports

Alexander J. Bisberg;Emilio Ferrara

Year: 2022 | Conference Paper |

Pictures as a Form of Protest: A Survey and Analysis of Images Posted During the Stop Asian Hate Movement on Twitter

Oliver Melbourne Allen;Emily Chen;Emilio Ferrara

2021 IEEE 18th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
Year: 2021 | Conference Paper |
Modern protests are not limited to on-the-ground operations, and the ease and speed at which users can upload images to social media platforms has enabled protests to manifest online. Previous analysis of protest imagery from social media sites categorized these images into groups including texts, screenshots, memes, and artwork. However, large-scale manual annotation to identify different types o...Show More

Pictures as a Form of Protest: A Survey and Analysis of Images Posted During the Stop Asian Hate Movement on Twitter

Oliver Melbourne Allen;Emily Chen;Emilio Ferrara

Year: 2021 | Conference Paper |

Mitigating the Bias of Heterogeneous Human Behavior in Affective Computing

Shen Yan;Hsien-Te Kao;Kristina Lerman;Shrikanth Narayanan;Emilio Ferrara

2021 9th International Conference on Affective Computing and Intelligent Interaction (ACII)
Year: 2021 | Conference Paper |
Cited by: Papers (4)
Affective computing is broadly applied to decision making systems ranging from mental health assessment to employability evaluation. The heterogeneity of human behavioral data poses challenges for both model validity and fairness. The limited access to sensitive attributes (e,g., race, gender) in real-world settings makes it more difficult to mitigate the unfairness of the model outcomes. In this ...Show More

Mitigating the Bias of Heterogeneous Human Behavior in Affective Computing

Shen Yan;Hsien-Te Kao;Kristina Lerman;Shrikanth Narayanan;Emilio Ferrara

Year: 2021 | Conference Paper |

The Influence of Social Ties on Performance in Team-Based Online Games

Yilei Zeng;Anna Sapienza;Emilio Ferrara

IEEE Transactions on Games
Year: 2021 | Volume: 13, Issue: 4 | Journal Article |
Cited by: Papers (6)
Social ties are the invisible glue that keeps together human ecosystems. Despite the massive amount of research studying the role of social ties in communities (groups, teams, etc.) and society at large, little attention has been devoted to study their interplay with other human behavioral dynamics. Of particular interest is the influence that social ties have on human performance in collaborative...Show More

The Influence of Social Ties on Performance in Team-Based Online Games

Yilei Zeng;Anna Sapienza;Emilio Ferrara

Year: 2021 | Volume: 13, Issue: 4 | Journal Article |

Individualized Context-Aware Tensor Factorization for Online Games Predictions

Julie Jiang;Kristina Lerman;Emilio Ferrara

2020 International Conference on Data Mining Workshops (ICDMW)
Year: 2020 | Conference Paper |
Cited by: Papers (1)
Individual behavior and decisions are substantially influenced by their contexts, such as location, environment, and time. Changes along these dimensions can be readily observed in Multiplayer Online Battle Arena games (MOBA), where players face different in-game settings for each match and are subject to frequent game patches. Existing methods utilizing contextual information generalize the effec...Show More

Individualized Context-Aware Tensor Factorization for Online Games Predictions

Julie Jiang;Kristina Lerman;Emilio Ferrara

Year: 2020 | Conference Paper |

Charting the Landscape of Online Cryptocurrency Manipulation

Leonardo Nizzoli;Serena Tardelli;Marco Avvenuti;Stefano Cresci;Maurizio Tesconi;Emilio Ferrara

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (72)
Cryptocurrencies represent one of the most attractive markets for financial speculation. As a consequence, they have attracted unprecedented attention on social media. Besides genuine discussions and legitimate investment initiatives, several deceptive activities have flourished. In this work, we chart the online cryptocurrency landscape across multiple platforms. To reach our goal, we collected a...Show More

Charting the Landscape of Online Cryptocurrency Manipulation

Leonardo Nizzoli;Serena Tardelli;Marco Avvenuti;Stefano Cresci;Maurizio Tesconi;Emilio Ferrara

Year: 2020 | Volume: 8 | Journal Article |

Effects of Network Structure on Subjective Preference Diversity

Anne Lin;Andreés Abeliuk;Emilio Ferrara

2019 IEEE International Conference on Big Data (Big Data)
Year: 2019 | Conference Paper |
Different social media environments enable different levels of community connectedness, which in turn affects the information that a user is exposed to. In this study, we create an agent-based model to investigate how the different levels of connectedness as well as network structure affects a group's diversity of opinions. In the model, agents are tasked with “liking” or “disliking” a set of obje...Show More

Effects of Network Structure on Subjective Preference Diversity

Anne Lin;Andreés Abeliuk;Emilio Ferrara

Year: 2019 | Conference Paper |

Estimating Individualized Daily Self-Reported Affect with Wearable Sensors

Shen Yan;Homa Hosseinmardi;Hsien-Te Kao;Shrikanth Narayanan;Kristina Lerman;Emilio Ferrara

2019 IEEE International Conference on Healthcare Informatics (ICHI)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Wearable sensors (smart watches, health/fitness trackers, etc.) are experiencing an explosion in popularity. Their pervasiveness allows for effective data collections to quantify human behavior in natural settings, enriching traditional behavioral science research opportunities. In this paper, we focus on the problem of affect estimation from sensor-generated data, whereas ground truth is availabl...Show More

Estimating Individualized Daily Self-Reported Affect with Wearable Sensors

Shen Yan;Homa Hosseinmardi;Hsien-Te Kao;Shrikanth Narayanan;Kristina Lerman;Emilio Ferrara

Year: 2019 | Conference Paper |

Personality and Behavior in Role-based Online Games

Zhao Wang;Anna Sapienza;Aron Culotta;Emilio Ferrara

2019 IEEE Conference on Games (CoG)
Year: 2019 | Conference Paper |
Cited by: Papers (9)
Both offline and online human behaviors are affected by personality. Of special interests are online games, where players have to impersonate specific roles and their behaviors are extensively tracked by the game. In this paper, we propose to study the relationship between players' personality and game behavior in League of Legends (LoL), one of the most popular Multiplayer Online Battle Arena (MO...Show More

Personality and Behavior in Role-based Online Games

Zhao Wang;Anna Sapienza;Aron Culotta;Emilio Ferrara

Year: 2019 | Conference Paper |

SoReC: A Social-Relation Based Centrality Measure in Mobile Social Networks

Bowen Li;Zhenxiang Gao;Xu Shan;Weihua Zhou;Emilio Ferrara

2019 26th International Conference on Telecommunications (ICT)
Year: 2019 | Conference Paper |
Cited by: Papers (2)
Mobile Social Networks (MSNs) have been evolving and enabling various fields in recent years. Recent advances in mobile edge computing, caching, and device-to-device communications, can have significant impacts on 5G systems. In those settings, identifying central users is crucial. It can provide important insights into designing and deploying diverse services and applications. However, it is chal...Show More

SoReC: A Social-Relation Based Centrality Measure in Mobile Social Networks

Bowen Li;Zhenxiang Gao;Xu Shan;Weihua Zhou;Emilio Ferrara

Year: 2019 | Conference Paper |

Discovering Latent Psychological Structures from Self-Report Assessments of Hospital Workers

Hsien-Te Kao;Homa Hosseinmardi;Shen Yan;Michelle Hasan;Shrikanth Narayanan;Kristina Lerman;Emilio Ferrara

2018 5th International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC)
Year: 2018 | Conference Paper |
Cited by: Papers (4)
Hospitals are high-stress environments where workers face a high risk of occupational burnout due to a mix of imbalanced schedules, understaffing, and emotional stress. In this paper, we propose a computational framework to infer the latent psychological makeup and traits of hospital workers. We apply machine learning models to psychometric data obtained from a suite of psychological survey instru...Show More

Discovering Latent Psychological Structures from Self-Report Assessments of Hospital Workers

Hsien-Te Kao;Homa Hosseinmardi;Shen Yan;Michelle Hasan;Shrikanth Narayanan;Kristina Lerman;Emilio Ferrara

Year: 2018 | Conference Paper |

Capturing Edge Attributes via Network Embedding

Palash Goyal;Homa Hosseinmardi;Emilio Ferrara;Aram Galstyan

IEEE Transactions on Computational Social Systems
Year: 2018 | Volume: 5, Issue: 4 | Journal Article |
Cited by: Papers (23)
Network embedding, which aims to learn low-dimensional representations of nodes, has been used for various graph related tasks including visualization, link prediction, and node classification. Most existing embedding methods rely solely on network structure. However, in practice, we often have auxiliary information about the nodes and/or their interactions, e.g., the content of scientific papers ...Show More

Capturing Edge Attributes via Network Embedding

Palash Goyal;Homa Hosseinmardi;Emilio Ferrara;Aram Galstyan

Year: 2018 | Volume: 5, Issue: 4 | Journal Article |

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Adam Badawy;Emilio Ferrara;Kristina Lerman

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Year: 2018 | Conference Paper |
Cited by: Papers (170)
Until recently, social media was seen to promote democratic discourse on social and political issues. However, this powerful communication platform has come under scrutiny for allowing hostile actors to exploit online discussions in an attempt to manipulate public opinion. A case in point is the ongoing U.S. Congress investigation of Russian interference in the 2016 U.S. election campaign, with Ru...Show More

Analyzing the Digital Traces of Political Manipulation: The 2016 Russian Interference Twitter Campaign

Adam Badawy;Emilio Ferrara;Kristina Lerman

Year: 2018 | Conference Paper |

Social Bots for Online Public Health Interventions

Ashok Deb;Anuja Majmundar;Sungyong Seo;Akira Matsui;Rajat Tandon;Shen Yan;Jon-Patrick Allem;Emilio Ferrara

2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Year: 2018 | Conference Paper |
Cited by: Papers (6)
According to the Center for Disease Control and Prevention, hundreds of thousands initiate smoking each year, and millions live with smoking-related diseases in the United States. Many tobacco users discuss their opinions, habits and preferences on social media. This work conceptualizes a framework for targeted health interventions to inform tobacco users about the consequences of tobacco use. We ...Show More

Social Bots for Online Public Health Interventions

Ashok Deb;Anuja Majmundar;Sungyong Seo;Akira Matsui;Rajat Tandon;Shen Yan;Jon-Patrick Allem;Emilio Ferrara

Year: 2018 | Conference Paper |

Performance Dynamics and Success in Online Games

Anna Sapienza;Hao Peng;Emilio Ferrara

2017 IEEE International Conference on Data Mining Workshops (ICDMW)
Year: 2017 | Conference Paper |
Cited by: Papers (6)
Online data provide a way to monitor how users behave in social systems like social networks and online games, and understand which features turn an ordinary individual into a successful one. Here, we propose to study individual performance and success in Multiplayer Online Battle Arena (MOBA) games. Our purpose is to identify those behaviors and playing styles that are characteristic of players w...Show More

Performance Dynamics and Success in Online Games

Anna Sapienza;Hao Peng;Emilio Ferrara

Year: 2017 | Conference Paper |

Early Warnings of Cyber Threats in Online Discussions

Anna Sapienza;Alessandro Bessi;Saranya Damodaran;Paulo Shakarian;Kristina Lerman;Emilio Ferrara

2017 IEEE International Conference on Data Mining Workshops (ICDMW)
Year: 2017 | Conference Paper |
Cited by: Papers (64)
We introduce a system for automatically generating warnings of imminent or current cyber-threats. Our system leverages the communication of malicious actors on the darkweb, as well as activity of cyber security experts on social media platforms like Twitter. In a time period between September, 2016 and January, 2017, our method generated 661 alerts of which about 84% were relevant to current or im...Show More

Early Warnings of Cyber Threats in Online Discussions

Anna Sapienza;Alessandro Bessi;Saranya Damodaran;Paulo Shakarian;Kristina Lerman;Emilio Ferrara

Year: 2017 | Conference Paper |

The DARPA Twitter Bot Challenge

V.S. Subrahmanian;Amos Azaria;Skylar Durst;Vadim Kagan;Aram Galstyan;Kristina Lerman;Linhong Zhu;Emilio Ferrara;Alessandro Flammini;Filippo Menczer

Computer
Year: 2016 | Volume: 49, Issue: 6 | Magazine Article |
Cited by: Papers (268)
From politicians and nation states to terrorist groups, numerous organizations reportedly conduct explicit campaigns to influence opinions on social media, posing a risk to freedom of expression. Thus, there is a need to identify and eliminate "influence bots" - realistic, automated identities that illicitly shape discussions on sites like Twitter and Facebook - before they get too influential.Show More

The DARPA Twitter Bot Challenge

V.S. Subrahmanian;Amos Azaria;Skylar Durst;Vadim Kagan;Aram Galstyan;Kristina Lerman;Linhong Zhu;Emilio Ferrara;Alessandro Flammini;Filippo Menczer

Year: 2016 | Volume: 49, Issue: 6 | Magazine Article |

Trust Networks: Topology, Dynamics, and Measurements

Santa Agreste;Pasquale De Meo;Emilio Ferrara;Sebastiano Piccolo;Alessandro Provetti

IEEE Internet Computing
Year: 2015 | Volume: 19, Issue: 6 | Magazine Article |
Cited by: Papers (32)
Thanks to the availability of user profiles and records of activity, online social network analysis can discover complex individual and social behavior patterns. The emergence of trust between users of online services is one of the most important phenomena, but it's also hard to detect in records of users' interactions, and even harder to replicate by abstract, generative models. Here, the authors...Show More

Trust Networks: Topology, Dynamics, and Measurements

Santa Agreste;Pasquale De Meo;Emilio Ferrara;Sebastiano Piccolo;Alessandro Provetti

Year: 2015 | Volume: 19, Issue: 6 | Magazine Article |

Parallel Clustering of High-Dimensional Social Media Data Streams

Xiaoming Gao;Emilio Ferrara;Judy Qiu

2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing
Year: 2015 | Conference Paper |
Cited by: Papers (11)
We introduce Cloud DIKW (Data, Information, Knowledge, Wisdom) as an analysis environment supporting scientific discovery through integrated parallel batch and streaming processing, and apply it to one representative domain application: social media data stream clustering. In this context, recent work demonstrated that high-quality clusters can be generated by representing the data points using hi...Show More

Parallel Clustering of High-Dimensional Social Media Data Streams

Xiaoming Gao;Emilio Ferrara;Judy Qiu

Year: 2015 | Conference Paper |

Analysis of a Heterogeneous Social Network of Humans and Cultural Objects

Santa Agreste;Pasquale De Meo;Emilio Ferrara;Sebastiano Piccolo;Alessandro Provetti

IEEE Transactions on Systems, Man, and Cybernetics: Systems
Year: 2015 | Volume: 45, Issue: 4 | Journal Article |
Cited by: Papers (27)
Modern online social platforms allow their members to be involved in a broad range of activities including getting friends, joining groups, posting, and commenting resources. In this paper, we investigate whether a correlation emerges across the different activities a user can take part in. For our analysis, we focused on aNobii, a social platform with a world-wide user base of book readers, who p...Show More

Analysis of a Heterogeneous Social Network of Humans and Cultural Objects

Santa Agreste;Pasquale De Meo;Emilio Ferrara;Sebastiano Piccolo;Alessandro Provetti

Year: 2015 | Volume: 45, Issue: 4 | Journal Article |

Trust and Compactness in Social Network Groups

Pasquale De Meo;Emilio Ferrara;Domenico Rosaci;Giuseppe M. L. Sarné

IEEE Transactions on Cybernetics
Year: 2015 | Volume: 45, Issue: 2 | Journal Article |
Cited by: Papers (66)
Understanding the dynamics behind group formation and evolution in social networks is considered an instrumental milestone to better describe how individuals gather and form communities, how they enjoy and share the platform contents, how they are driven by their preferences/tastes, and how their behaviors are influenced by peers. In this context, the notion of compactness of a social group is par...Show More

Trust and Compactness in Social Network Groups

Pasquale De Meo;Emilio Ferrara;Domenico Rosaci;Giuseppe M. L. Sarné

Year: 2015 | Volume: 45, Issue: 2 | Journal Article |

Clustering memes in social media

Emilio Ferrara;Mohsen JafariAsbagh;Onur Varol;Vahed Qazvinian;Filippo Menczer;Alessandro Flammini

2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2013)
Year: 2013 | Conference Paper |
The increasing pervasiveness of social media creates new opportunities to study human social behavior, while challenging our capability to analyze their massive data streams. One of the emerging tasks is to distinguish between different kinds of activities, for example engineered misinformation campaigns versus spontaneous communication. Such detection problems require a formal definition of meme,...Show More

Clustering memes in social media

Emilio Ferrara;Mohsen JafariAsbagh;Onur Varol;Vahed Qazvinian;Filippo Menczer;Alessandro Flammini

Year: 2013 | Conference Paper |

IEEE Account

Purchase Details

Profile Information

Need Help?

A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity.
© Copyright 2025 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.