Ross Dahlke
Biographic Data
| ID | 316702 |
|---|---|
| NAME | Ross Dahlke |
| GIVEN NAMES | Ross |
| FAMILY NAME | Dahlke |
| SIGNATURE | DAHLKE R |
| AFFILIATIONS | University of Wisconsin–Madison |
| ORCID | 0000-0002-5179-2525 |
| VERIFIED | Yes |
| TOTAL WORKS | 9 |
| TOTAL CITATIONS | 10 |
| AUTHOR COUNT | 9 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
Cross-platformization: How U.S. right-leaning media curate their posts on Twitter and Truth Social
This study examines how seven right-leaning media organizations utilize cross-platformization strategies to reach audiences across multiple platforms; in this case, Twitter and Truth Social. Focusing on both content volume and story packaging, we collect right-leaning media organizations’ social media posts and content from the 2022 U.S. midterm election. Combining computational and qualitative methods, we find that outlets posted only a small sh…
The Consumption of Pink Slime Journalism: Who, What, When, Where, and Why
Pink slime journalism refers to organizations masquerading as local news, often serving special interests. Past research and reporting have illuminated pink slime journalism production (e.g., identifying outlets and documenting practices) but have not systematically analyzed consumption. We combine web browsing behavior of a national sample of American adults during the 2020 election (N = 1,238; 21 M website visits) with a database of pink slime …
Multi-Platform Referrers of Misinformation: A Comparative Analysis of Misinformation Visits Referred by Facebook, Twitter, Instagram, Reddit, YouTube, Snapchat, and TikTok
Journalistic and scholarly accounts alike often depict social media platforms as key players in exposing people to misinformation. Unfortunately, existing research examining social media’s role in exposing people to misinformation online implicitly operates under what we call the direct referrer paradigm, focusing only on visits to misinformation that directly follow social media. We introduce the embedded referrer paradigm, which considers socia…
Style and substance on The Alex Jones Show predict InfoWars sales: A multi-modal analysis of a media empire
Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections
In this multi-platform, comparative study, we analyze social media messages from political candidates ( N = 1,517) running for Congress during the 2022 U.S. Midterm election. We collect data from seven social media platforms: Facebook, Twitter, Truth Social, Gettr, Instagram, YouTube, and Rumble over the 4 weeks before and after election day. With this unique dataset of posts, we apply computational methods to identify messages that sought to mob…
Audio-as-Data Tools: Replicating Computational Data Processing
The rise of audio-as-data in social science research accentuates a fundamental challenge: establishing reproducible and reliable methodologies to guide this emerging area of study. In this study, we focus on the reproducibility of audio-as-data preparation methods in computational communication research and evaluate the accuracy of popular audio-as-data tools. We analyze automated transcription and computational phonology tools applied to 200 epi…
Surviving or thriving political defeat on social media: A temporal analysis of how electoral loss exacerbates the gender gap in political expression
Extensive research reveals gender gaps in social media expression, particularly women’s reduced propensity for sharing political information and opinions. We examine the impact of political defeat on the gender gap in political expression on social media by pairing Twitter data from candidate supporters with a voter file. Our results indicate that Trump’s 2020 defeat reduced tweet volumes only among his female supporters, while his male supporter…
Quantifying the Systematic Bias in the Accessibility and Inaccessibility of Web Scraping Content From URL-Logged Web-Browsing Digital Trace Data
Social scientists and computer scientists are increasingly using observational digital trace data and analyzing these data post hoc to understand the content people are exposed to online. However, these content collection efforts may be systematically biased when the entirety of the data cannot be captured retroactively. We call this often unstated assumption the problematic assumption of accessibility. To examine the extent to which this assumpt…
Exposure to untrustworthy websites in the 2020 US election
Surviving or thriving political defeat on social media: A temporal analysis of how electoral loss exacerbates the gender gap in political expression
Extensive research reveals gender gaps in social media expression, particularly women’s reduced propensity for sharing political information and opinions. We examine the impact of political defeat on the gender gap in political expression on social media by pairing Twitter data from candidate supporters with a voter file. Our results indicate that Trump’s 2020 defeat reduced tweet volumes only among his female supporters, while his male supporter…
Exposure to untrustworthy websites in the 2020 US election
Quantifying the Systematic Bias in the Accessibility and Inaccessibility of Web Scraping Content From URL-Logged Web-Browsing Digital Trace Data
Social scientists and computer scientists are increasingly using observational digital trace data and analyzing these data post hoc to understand the content people are exposed to online. However, these content collection efforts may be systematically biased when the entirety of the data cannot be captured retroactively. We call this often unstated assumption the problematic assumption of accessibility. To examine the extent to which this assumpt…
Surviving or thriving political defeat on social media: A temporal analysis of how electoral loss exacerbates the gender gap in political expression
Extensive research reveals gender gaps in social media expression, particularly women’s reduced propensity for sharing political information and opinions. We examine the impact of political defeat on the gender gap in political expression on social media by pairing Twitter data from candidate supporters with a voter file. Our results indicate that Trump’s 2020 defeat reduced tweet volumes only among his female supporters, while his male supporter…
Quantifying the Systematic Bias in the Accessibility and Inaccessibility of Web Scraping Content From URL-Logged Web-Browsing Digital Trace Data
Social scientists and computer scientists are increasingly using observational digital trace data and analyzing these data post hoc to understand the content people are exposed to online. However, these content collection efforts may be systematically biased when the entirety of the data cannot be captured retroactively. We call this often unstated assumption the problematic assumption of accessibility. To examine the extent to which this assumpt…
Exposure to untrustworthy websites in the 2020 US election
Audio-as-Data Tools: Replicating Computational Data Processing
The rise of audio-as-data in social science research accentuates a fundamental challenge: establishing reproducible and reliable methodologies to guide this emerging area of study. In this study, we focus on the reproducibility of audio-as-data preparation methods in computational communication research and evaluate the accuracy of popular audio-as-data tools. We analyze automated transcription and computational phonology tools applied to 200 epi…
Candidates Be Posting: Multi-Platform Strategies and Partisan Preferences in the 2022 U.S. Midterm Elections
In this multi-platform, comparative study, we analyze social media messages from political candidates ( N = 1,517) running for Congress during the 2022 U.S. Midterm election. We collect data from seven social media platforms: Facebook, Twitter, Truth Social, Gettr, Instagram, YouTube, and Rumble over the 4 weeks before and after election day. With this unique dataset of posts, we apply computational methods to identify messages that sought to mob…
Cross-platformization: How U.S. right-leaning media curate their posts on Twitter and Truth Social
This study examines how seven right-leaning media organizations utilize cross-platformization strategies to reach audiences across multiple platforms; in this case, Twitter and Truth Social. Focusing on both content volume and story packaging, we collect right-leaning media organizations’ social media posts and content from the 2022 U.S. midterm election. Combining computational and qualitative methods, we find that outlets posted only a small sh…
The Consumption of Pink Slime Journalism: Who, What, When, Where, and Why
Pink slime journalism refers to organizations masquerading as local news, often serving special interests. Past research and reporting have illuminated pink slime journalism production (e.g., identifying outlets and documenting practices) but have not systematically analyzed consumption. We combine web browsing behavior of a national sample of American adults during the 2020 election (N = 1,238; 21 M website visits) with a database of pink slime …
Multi-Platform Referrers of Misinformation: A Comparative Analysis of Misinformation Visits Referred by Facebook, Twitter, Instagram, Reddit, YouTube, Snapchat, and TikTok
Journalistic and scholarly accounts alike often depict social media platforms as key players in exposing people to misinformation. Unfortunately, existing research examining social media’s role in exposing people to misinformation online implicitly operates under what we call the direct referrer paradigm, focusing only on visits to misinformation that directly follow social media. We introduce the embedded referrer paradigm, which considers socia…
Style and substance on The Alex Jones Show predict InfoWars sales: A multi-modal analysis of a media empire
Social media (6 works) · Social Media and Politics (6 works) · Computer Science (5 works) · Misinformation and Its Impacts (4 works) · Misinformation (3 works) · Political science (3 works) · Computational and Text Analysis Methods (2 works) · Data science (2 works) · Economics (2 works) · Internet privacy (2 works)