CHA Meeyoung, CI of the Data Science Group, is selected as the winner of the Test of Time Award by the American Association for AI (AAAI)

CHA Meeyoung, the CI of the Data Science Group of the IBS Pioneer Research Center for Mathematical and Computational Sciences and Professor at the KAIST School of Computing, won the Test of Time Award during the 14th International AAAI Conference on Web and Social Media (ICWSM 2020), which was held online on June 8.

ICWSM has selected the winners of its annual Test of Time Award among researchers who engaged in research projects that have had a continued influence in academia over an extended period of time. Cha was recognized for her research work published on ICWSM in 2010. Her article entitled “Measuring User Influence in Twitter: The Million Follower Fallacy” has been cited 3,669 times as of this day.

Her research described the “million follower fallacy”, which states that the number of followers is not necessarily correlated with the viral potential of the message. The research was based on the comparison of diverse measurement methods to assess the influence of users on social network platforms. Cha analyzed 1.96325 billion follow links and 1.75592 billion tweets posted by 54.98 million Twitter users. At the time, her attempt to analyze such a vast network was praised as an exceptional research, and thousands of follow-up studies have stemmed from her work.

Through her research, she succeeded in defining how long influencers can remain active and how far-reaching their influence can be. She also presented some strategies to rapidly emerge as an influencer by analyzing cases of recognized influencers. Her strategies can provide new insight to corporations and institutions that are seeking to select influencers to advertise on social network platforms.

Cha performed this project while serving as a post-doctoral researcher at Germany’s Max Planck institute. Cha said, “Although social network platform data has not garnered much attention in computer science, I found it intriguing that online data could be used to resolve issues related to social science and stayed up for many nights delving into this subject. I am grateful that my research has remained influential over so many years.”