Hi there!

I am Yixue Wang [ee-shew-eh wong] (汪一雪), a Ph.D. student in the Technology and Social Behavior program at Northwestern University, a joint program in Computer Science and Communication. I am advised by Nicholas Diakopoulos in the Computational Journalism Lab. 

My research examines the role of algorithmic tools and interface designs in supporting civil, diverse and relevant news engagement. My work utilizes data science methods including machine learning and natural language processing, and human-centered design methods such as interviews and prototyping. My research has been published in venues such as ACM SIGCHI, ACM Transactions on Social Computing, ICWSM, and HICSS. 

I worked as a research intern at Facebook Core Data Science and Spotify Research, and I was a data engineer at HaystaqDNA before I joined Northwestern, focusing on building machine learning models and data process pipelines. I earned my M.S. in Urban Informatics from NYU and my B.Eng. (Hons) in Telecommunications Engineering from Beijing University of Posts and Telecommunications and Queen Mary, University of London.

Contact: yixue.wang[at]u.northwestern.edu

Research Projects
Comment Moderation and Designs

My work (nominated for the Best Paper Award) at HICSS discusses the positive correlation between NYT Picks and commenters’ commenting behaviors. We later published the paper at ACM Transactions on Social Computing: 

  • Y. Wang and N. Diakopoulos. Highlighting High-quality Content as a Moderation Strategy: The Role of New York Times Picks in Comment Quality and Engagement. ACM Transactions on Social Computing. 2021. (pre-print) 

I also published a workshop paper discussing how to personalize comment section design at the EACL Hackashop on News Media Content Analysis and Automated Report Generation. 

  • Y. Wang. Comment Section Personalization: Algorithmic, Interface, and Interaction Design. Proc. of the EACL Hackashop on News Media Content Analysis and Automated Report Generation. 2021. (PDF)
User-Generated Content Sourcing

I discussed how journalists source user-generated content (UGC), detailing what journalists typically look for in UGCs, and presented a UGC sourcing tool for journalists to filter and rank UGCs based on their needs at CHI 2021. 

  • Y. Wang and N. Diakopoulos. Journalistic Source Discovery: Supporting The Identification of News Sources in User Generated Content. Proc. Human Factors in Computing Systems (CHI). 2021. (pre-print)
News Article Personalization

I analyzed readers’ perceptions of personalized news articles and presented the results at the Computation + Journalism Symposium. 

  • Y. Wang​ and N. Diakopoulos. Readers’ Perceptions of Personalized News Articles. Proc. Computation + Journalism Symposium. 2020. (PDF)

I also explored design ideas around article-level personalization at ICWSM Workshop on Algorithmic Personalization and News.

  • Y. Wang ​and N. Diakopoulos. Considerations for Article-Level Personalization of News Content. Proc. ICWSM Workshop on Algorithmic Personalization and News. 2018. (PDF)
Gender Differences in Music Industry

I presented my work about gender differences in productivity and success in the music industry at IC2S2 in July 2020, and at ICWSM in Jun 2019. 

  • Y. Wang ​and A. Horvat. Gender Differences in the Global Music Industry: Evidence from MusicBrainz and The Echo Nest. International Conference on Web and Social Media (ICWSM). 2019. (PDF)