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From the Great Speeches of History to Data Operations within Political Campaigns: A Conversation with Ross Dahlke

Recently, we had the pleasure of speaking with Ross Dahlke, a PhD student, who's both a Stanford Data Science Scholar and Knight Hennessy Scholar in Stanford University’s Social Media Lab where he studies the feedback loop between online information exposure and offline beliefs and behaviors. Our conversation was incredibly insightful, covering his background, current projects, and perspectives on data science’s role in political campaigns and beyond.

Beginnings: From Struggle to Strength

After completing his undergraduate education at the University of Wisconsin-Madison, where he graduated with Comprehensive Honors, Ross worked as a Data Scientist at a digital marketing and measurement firm in Minneapolis, MN where he developed and deployed Bayesian machine learning models, conducted large-scale A/B testing, and worked with client teams to optimize digital marketing budgets for Fortune 500 companies. Ross has also consulted for over 80 political campaigns.

When asked about his journey into data science, Ross shared an inspiring story from his youth. Growing up with a speech impediment, he faced significant challenges in communication. Determined to overcome this, he took the initiative to improve his skills by studying the great speeches of history. This endeavor not only helped him conquer his stutter but also ignited a passion for communication and public speaking.

“One day I went to my public library, and I checked out a book on the great speeches of history,” shares Ross. “I would stay up at night, and I would practice these speeches that other people had given. And I become captivated by communication’s ability to inspire social movements.”

Ross Dahlke

Ross joined his high school speech team, excelling in competitive speaking and eventually venturing into politics. While in high school, he became the vice chair of his local political party and actively volunteered in local campaigns. Through these experiences, Ross realized that political opinions were more influenced by individual media consumption rather than grandiose speeches. This revelation sparked his interest in data science, leading him to work on political campaigns and eventually transition to academic research.

Academic Pursuit

Ross's journey into data science began with a deep curiosity about the effects of media on political campaigns. He observed that the focus of political data work had shifted from speechwriting and press relations to data-driven strategies. Intrigued by this shift, Ross immersed himself in the study of data operations within political campaigns.

Through his work, Ross discovered the limitations of traditional data collection methods in capturing the nuanced effects of media on voters. He recognized the need for innovative approaches to studying media ecosystems, leading him to develop computational tools for collecting unique data and conducting field experiments.

Data Science Innovations: Blocking Misinformation Websites

Ross Dahlke presenting

Ross's dissertation project focuses on political content, particularly misinformation and AI-generated content, in encrypted messaging channels, such as WhatsApp. While many researchers have speculated that these types of political content have moved to encrypted messaging spaces, they’re notoriously difficult to study. Ross built a tool that, with user-informed consent, saves and analyses messages participants receive in real time. Ross hopes to shed light on the prevalence of misinformation and AI-generated content in these private channels, as well as the attitudinal and behavioral effects of this content.

Interdisciplinary Collaboration

Ross emphasizes the importance of interdisciplinary collaboration in his work. At Stanford, he has engaged with experts across campus, including political science, economics, engineering, and critical media studies. This diverse intellectual environment enriches his research and helps him consider the broader societal impacts of his work.

The Stanford Data Science (SDS) program has been instrumental in supporting Ross and Ross's academic pursuits. He praises SDS's sense of community and belonging, highlighting the value of having a network of peers and mentors who share their passion for data science. For example, he recently had a project that required high-performance computing with a short turnaround time. Ross shared how the SDS community came to help him complete the project much quicker than he could have otherwise. He also praised the weekly SDS meetings as the highlight of his week: “Having this interdisciplinary community at Stanford where experts from different backgrounds can come together to talk about data science is so unique. It’s truly been one of my favorite experiences at Stanford.”

Looking Ahead

Ross Dahlke

Ross is optimistic about the future of data science, computational social science, and the study of communication. “With advancements in AI, data science, and causal inference, it is an exciting time to be a media researcher. Through the ability to collect new data and conduct field experiments at a scale, we can ask and answer questions that respond to society’s most pressing challenges.”

Join us in congratulating Ross as he embarks on his next adventure as an Assistant Professor at the University of Wisconsin-Madison School of Journalism and Mass Communication in January 2025.

Publications & Pre-Prints

  • Dahlke, R., & Pan, J. (2024). January 6 arrests and media coverage do not remobilize conservatives on social media. Proceedings of the National Academy of Sciences, 121(23), e2401239121. https://doi.org/10.1073/pnas.2401239121  
  • Moore,* R. C., Dahlke*, R., & Hancock, J. T. (2023). Exposure to untrustworthy websites in the 2020 US election. Nature Human Behaviour, 7(7), 1096-1105. https://doi.org/10.1038/s41562-023-01564-2 *indicates equal authorship
  • Dahlke, R., Moore, R., Forberg, P., & Hancock, J. (2024). The private life of QAnon: A mixed methods investigation of Americans’ exposure to QAnon content on the web. Forthcoming at the 27th ACM SIGCHI Conference on Computer-Supported Cooperative Work & Social Computing (CSCW). Preprint doi: https://doi.org/10.31219/osf.io/u6vgz 
  • Dahlke, R., & Zhang, Y. (2024). Surviving or thriving political defeat on social media: a temporal analysis of how electoral loss exacerbates the gender gap in political expression. Journal of Computer-Mediated Communication, 29(1), zmad051. https://doi.org/10.1093/jcmc/zmad051
  • Dahlke, R., Kumar, D., Durumeric, Z., & Hancock, J. T. (2023). Quantifying the Systematic Bias in the Accessibility and Inaccessibility of Web Scraping Content from URL-Logged Web-Browsing Digital Trace Data. Social Science Computer Review, 08944393231218214. https://doi.org/10.1177/08944393231218214
  • Dahlke, R., & Hancock, J. (2022). The effect of online misinformation exposure on false election beliefs. OSF Preprints, 17. https://doi.org/10.31219/osf.io/325tn
  • Moore, R., Dahlke, R., Bengani, P., & Hancock, J. (2023). The Consumption of Pink Slime Journalism: Who, What, When, Where, and Why?. OSF Preprints, https://doi.org/10.31219/osf.io/3bwz6 
  • Bin Chen, B., Borah, P., Dahlke, R. Lukito, J (2024). Battle for Inbox and Bucks: Comparing Email Fundraising Strategies of Donald Trump and Joe Biden in the 2020 U.S. Presidential Election. https://doi.org/10.51685/jqd.2024.012
  • Lukito, J., Greenfield, J., Yang, Y., Dahlke, R., Brown, M. A., Lewis, R., & Chen, B. (2024). Audio-as-Data Tools: Replicating Computational Data Processing. Media and Communication, 12. https://doi.org/10.17645/mac.7851