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차미영 교수

Mee Young Cha

KAIST 디지털인문사회과학부 · 사회과학

연구실 소개

차미영 교수의 연구실은 온라인 소셜 미디어와 사용자 생성 콘텐츠 기반의 정보 확산 메커니즘을 중심으로 연구를 진행합니다. 특히 트위터와 유튜브 등 대규모 플랫폼을 대상으로 유저 영향력, 뉴스 및 루머의 확산 패턴, 콘텐츠 공유 행동의 동적 특성을 분석합니다. 연구는 실시간 데이터 기반의 통계적 분석과 시계열적 변화 추적을 통해 디지털 커뮤니케이션의 구조적 특성과 비즈니스 응용 가능성을 탐구합니다.

소셜 미디어정보 확산루머 분류사용자 영향력콘텐츠 공유 패턴

연구 현황

논문 수
304
총 인용 수
15,946
최근 5년 논문
124
주요 분야
사회과학

연구 성과 추이

표시된 성과는 수집된 데이터 기준으로 산출되며, 일부 차이가 있을 수 있습니다.

5개년 연도별 논문 게재 수
124총합
2022
2023
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2026
5개년 연도별 피인용 수
1,064총합
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주요 논문

15
1
논문|인용수 3,009·2010
Measuring User Influence in Twitter: The Million Follower Fallacy
Meeyoung Cha, Hamed Haddadi, Fabrí­cio Benevenuto, Krishna P. Gummadi
Proceedings of the International AAAI Conference on Web and Social MediaOA

Directed 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

Statistical and Nonlinear PhysicsPhysics and Astronomy
2
논문|인용수 1,590·2007
I tube, you tube, everybody tubes
Meeyoung Cha, Haewoon Kwak, Pablo Rodríguez, Yong‐Yeol Ahn, Sue Moon
OA

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Computer Networks and CommunicationsComputer Science
3
논문|인용수 767·2009
A measurement-driven analysis of information propagation in the flickr social network
Meeyoung Cha, Alan Mislove, Krishna P. Gummadi

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.

Statistical and Nonlinear PhysicsPhysics and Astronomy
4
논문|인용수 497·2009
Analyzing the Video Popularity Characteristics of Large-Scale User Generated Content Systems
Meeyoung Cha, Haewoon Kwak, P. Rodríguez, Yong‐Yeol Ahn, Sue Moon
SJR Q1IEEE/ACM Transactions on Networking

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

Computer Networks and CommunicationsComputer Science
5
논문|인용수 357·2017
Rumor Detection over Varying Time Windows
Sejeong Kwon, Meeyoung Cha, Kyomin Jung
SJR Q1PLoS ONEOA

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

Sociology and Political ScienceSocial Sciences
6
논문|인용수 262·2008
Watching television over an IP network
Meeyoung Cha, Pablo Rodríguez, Jon Crowcroft, Sue Moon, Xavier Amatriain

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

Computer Networks and CommunicationsComputer Science
7
논문|인용수 153·2012
The World of Connections and Information Flow in Twitter
Meeyoung Cha, Fabr ́ icio Benevenuto, Hamed Haddadi, Krishna P. Gummadi
IEEE Transactions on Systems Man and Cybernetics - Part A Systems and Humans

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,

CommunicationSocial Sciences
8
논문|인용수 147·2008
Characterizing social cascades in flickr
Meeyoung Cha, Alan Mislove, Ben Adams, Krishna P. Gummadi

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

Statistical and Nonlinear PhysicsPhysics and Astronomy
9
논문|인용수 107·2008
On next-generation telco-managed P2P TV architectures
Meeyoung Cha, Pablo Rodríguez, Sue Moon, Jon Crowcroft

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

Computer Networks and CommunicationsComputer Science
10
논문|인용수 104·2022
Misinformation, believability, and vaccine acceptance over 40 countries: Takeaways from the initial phase of the COVID-19 infodemic
Karandeep Singh, Gabriel Lima, Meeyoung Cha, Chiyoung Cha, Juhi Kulshrestha, Yong‐Yeol Ahn, Onur Varol
SJR Q1PLoS ONEOA

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

Sociology and Political ScienceSocial Sciences
11
논문|인용수 74·2014
Sharing political news: the balancing act of intimacy and socialization in selective exposure
Jisun An, Daniele Quercia, Meeyoung Cha, Krishna P. Gummadi, Jon Crowcroft
SJR Q1EPJ Data ScienceOA

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

CommunicationSocial Sciences
12
논문|인용수 50·2023
User-Chatbot Conversations During the COVID-19 Pandemic: Study Based on Topic Modeling and Sentiment Analysis
Hyojin Chin, Gabriel Lima, Mingi Shin, Assem Zhunis, Chiyoung Cha, Junghoi Choi, Meeyoung Cha
SJR Q1Journal of Medical Internet ResearchOA

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

Artificial IntelligenceComputer Science
13
논문|인용수 42·2006
Placing Relay Nodes for Intra-Domain Path Diversity
Meeyoung Cha, Sue Moon, C.-D. Park, Aman Shaikh

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

Computer Networks and CommunicationsComputer Science
14
논문|인용수 42·2021
COVID-19 Discourse on Twitter in Four Asian Countries: Case Study of Risk Communication
Sungkyu Park, Sungwon Han, Jeongwook Kim, Mir Majid Molaie, Hoang Dieu Vu, Karandeep Singh, Jiyoung Han, Wonjae Lee, Meeyoung Cha
SJR Q1Journal of Medical Internet ResearchOA

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

Sociology and Political ScienceSocial Sciences
15
논문|인용수 41·2011
Delayed information cascades in Flickr: Measurement, analysis, and modeling
Meeyoung Cha, Fabrí­cio Benevenuto, Yong‐Yeol Ahn, Krishna P. Gummadi
SJR Q1Computer NetworksOA
Statistical and Nonlinear PhysicsPhysics and Astronomy

대표 연구 분야

Artificial IntelligenceSociology and Political ScienceCommunicationStatistical and Nonlinear PhysicsSafety ResearchSocial Psychology

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