Mee Young Cha
Korea Advanced Institute of Science and Technology · Social Sciences
About the Lab
Professor Mee Young Cha's research lab focuses on understanding information diffusion, user influence, and content propagation in online social networks and user-generated content platforms. The lab investigates how information—especially rumors and viral content—spreads across social media, with an emphasis on structural, linguistic, and temporal features that shape online influence and virality. Using large-scale real-world data from platforms like Twitter, YouTube, and IPTV systems, the lab combines empirical analysis with statistical modeling to uncover patterns in user behavior and network dynamics. The research also explores the implications for viral marketing, content recommendation, and network resilience.
Research Overview
Research Output Trend
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Selected Papers
15Directed links in social media could represent anything from intimate friendships to common interests, or even a passion for breaking news or celebrity gossip. Such directed links determine the flow of information and hence indicate a user's influence on others — a concept that is crucial in sociology and viral marketing. In this paper, using a large amount of data collected from Twitter, we present an in-depth comparison of three measures of influence: indegree, retweets, and mentions. Based on
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Online social networking sites like MySpace, Facebook, and Flickr have become a popular way to share and disseminate content. Their massive popularity has led to viral marketing techniques that attempt to spread content, products, and ideas on these sites. However, there is little data publicly available on viral propagation in the real world and few studies have characterized how information spreads over current online social networks.
User generated content (UGC), now with millions of video producers and consumers, is reshaping the way people watch video and TV. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and generating new business opportunities. Compared to traditional video-on-demand (VoD) systems, UGC services allow users to request videos from a potentially unlimited selection in an asynchronous fashion. To better understand the impact of UGC s
This study determines the major difference between rumors and non-rumors and explores rumor classification performance levels over varying time windows-from the first three days to nearly two months. A comprehensive set of user, structural, linguistic, and temporal features was examined and their relative strength was compared from near-complete date of Twitter. Our contribution is at providing deep insight into the cumulative spreading patterns of rumors over time as well as at tracking the pre
For half a century, television has been a dominant and pervasive mass media, driving many technological advances. Despite its widespread usage and importance to emerging applications, the ingrained TV viewing habits are not completely understood. This was primarily due to the difficulty of instrumenting monitoring devices at individual homes at a large scale. The recent boom of Internet TV (IPTV) has enabled us to monitor the user behavior and network usage of an entire network. Such analysis ca
Information propagation in online social networks like Twitter is unique in that word-of-mouth propagation and traditional media sources coexist. We collect a large amount of data from Twitter to compare the relative roles different types of users play in information flow. Using empirical data on the spread of news about major international headlines as well as minor topics, we investigate the relative roles of three types of information spreaders: 1) mass media sources like BBC; 2) grassroots,
Online social networking sites like MySpace and Flickr have become a popular way to share and disseminate content. Their massive popularity has led to the viral marketing of content, products, and political campaigns on the sites themselves. Despite the excitement, the precise mechanisms by which information is exchanged over these networks are not well understood.In this paper, we investigate social cascades, or how information disseminates through social links in online social networks. Using
Abstract—In recent years, Telcos worldwide have deployed IPTV networks to offer cable TV-like services over the IP backbones. Such walled garden IPTV networks are provisioned to guarantee the quality of service, fast channel switching, and user experience expected by TV viewers. A common key design element of these networks is the use of IP multicast within a single network domain to broadcast several hundreds of TV channels to millions of receivers. However, as the amount of content and channel
The COVID-19 pandemic has been damaging to the lives of people all around the world. Accompanied by the pandemic is an infodemic, an abundant and uncontrolled spread of potentially harmful misinformation. The infodemic may severely change the pandemic's course by interfering with public health interventions such as wearing masks, social distancing, and vaccination. In particular, the impact of the infodemic on vaccination is critical because it holds the key to reverting to pre-pandemic normalcy
One might think that, compared to traditional media, social media sites allow people to choose more freely what to read and what to share, especially for politically oriented news. However, reading and sharing habits originate from deeply ingrained behaviors that might be hard to change. To test the extent to which this is true, we propose a Political News Sharing (PoNS) model that holistically captures four key aspects of social psychology: gratification , selective exposure , socialization , a
BACKGROUND: Chatbots have become a promising tool to support public health initiatives. Despite their potential, little research has examined how individuals interacted with chatbots during the COVID-19 pandemic. Understanding user-chatbot interactions is crucial for developing services that can respond to people's needs during a global health emergency. OBJECTIVE: This study examined the COVID-19 pandemic-related topics online users discussed with a commercially available social chatbot and com
To increase reliability and robustness of missioncritical services in the face of routing changes, it is often desirable and beneficial to take advantage of path diversity provided by the network topology. One way of achieving this inside a single Autonomous System (AS) is to use two paths between every Origin-Destination (OD) pair. One path is the default path defined by the intra-domain routing protocol; the other path is defined as an overlay path that passes through a strategically placed re
BACKGROUND: COVID-19, caused by SARS-CoV-2, has led to a global pandemic. The World Health Organization has also declared an infodemic (ie, a plethora of information regarding COVID-19 containing both false and accurate information circulated on the internet). Hence, it has become critical to test the veracity of information shared online and analyze the evolution of discussed topics among citizens related to the pandemic. OBJECTIVE: This research analyzes the public discourse on COVID-19. It ch
Research Areas
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