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Peer-Reviewed Journal Publications

My work has appeared in Journal of Media Psychology, Computers in Human Behavior, Social Media + Society, New Media & Society, Journal of Sex Research, Atlantic Journal of Communication, International Journal of Communication, Journal of Communication Technology, Digital Health, Journalism and Mass Communication Quarterly, Cyberpsychology, Behavior, and Social Networking, Journalism and Media, and the Interactive Journal of Medical Research.

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Conference Presentations

My research has been presented at international, national, and regional conferences, including the International Communication Association, National Communication Association, the Association for Education in Journalism and Mass Communication, and numerous regional conferences.

Our understanding of community has changed. Our social networks have shifted, sometimes as hybrid groups of offline and online friends, but occasionally as entirely digital connections. In my research I seek to understand how social media users see their social networks, how they use them for their benefit, and how they see their place within them.


Published Research

All datasets are available and may be shared upon request. I can also share Python scripts used for data collection.

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Imgur group identity and commenting norms

From an examination of Imgur posts and comments, findings suggest that users communicate in predictable patterns. More importantly, I theorize that these patterns stem from social identification and corresponding social norms.

Method: Content Analysis

Dataset: 105 Imgur posts and 4404 comments

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Reddit and the 2016 Presidential election

This project explored images shared by users of r/hillaryclinton and r/The_Donald during the 2016 election. Results indicated that Clinton supporters framed her as a unidimensional candidate, while Trump supporters portrayed him as a multidimensional and capable leader.

Method: Content Analysis

Dataset: 701 Reddit posts

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Imgur, depression, and social support

This work examined Imgur posts that discussed depression and the comments submitted in response. Findings suggest that Imgur users are supportive of community members dealing with mental health issues, frequently offering empathy and advice.

Method: Content Analysis

Dataset: 20 Imgur posts and 5584 comments

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YouTube cancer vlogging and social support

Through an exploration of YouTube cancer vlogs and corresponding user comments, this study indicates that vlogging may be an effective way for cancer patients to find support. The results also suggest that narrative features differ in how much support they elicit.

Method: Content Analysis

Dataset: 70 YouTube vlogs and 869 comments

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YouTube, obesity, and prejudice in comments

Following the viral videos “Fat Girl Tinder Date” and “Fat Guy Tinder Date,” this project analyzed YouTube comments concerning gender and weight. Findings suggest that attacks on overweight people were far more common than defenses, especially when targeting women.

Method: Content Analysis

Dataset: 2 YouTube videos and 320 comments

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Telling a story through personal experience

This experimental study tested whether personal testimonies in news coverage would influence how people make sense of social problems. The results indicate that empathetic viewers respond to personal testimonies by assigning blame to systemic causes.

Methods: Experiment, Content Analysis

Dataset: 80 participants, 560 open-ended responses

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Journalistic differences across audio and video

This methodological study examined how German news stories represented refugees and asylum seekers across audio and video. These results suggest that audio and visual material may occasionally disagree, changing how consumers understand the news.

Methods: Content Analysis

Dataset: 98 German news stories

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Imgur posts about cancer and social support

This project examined comment responses to Imgur posts about cancer. These findings suggest that Imgur users frequently respond with empathy, providing reassurance and information to community members dealing with various forms of cancer.

Method: Content Analysis

Dataset: 117 Imgur posts and 2511 comments

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Image perception and camera framing

This work tested the effects of camera framing (angle and distance) on audience’s emotional reactions. The results indicate that framing and angle influence perceivers’ feelings of arousal, positivity, and dominance, meaning that the way images are captured has important implications for how they are perceived.

Method: Experiment, Content Analysis

Dataset: 722 images from the IAPS database

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Reddit as a source for COVID-19 information

This project examined user activity in the r/Coronavirus subreddit. In particular, this project focused on information sharing within the subreddit and discourse surrounding the COVID-19 pandemic, identifying the types of information that users prioritized during the pandemic’s infancy.

Methods: Content Analysis

Dataset: 226 Reddit posts and 2260 comments

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Imgur group identity and persuasion

This work sought to understand how users process persuasive messages presented by their community. Findings indicated that users process messages more deeply, and are more persuaded after reading a message in an Imgur post than elsewhere.

Methods: Experiment, Survey

Dataset: 323 participants, closed and open-ended survey responses

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Identity plurality and social media use

Through a survey of Nigerian Facebook users, this project examined the connection between online behaviors and aspects of identity. Findings suggested that personal and social behaviors contributed to a pluralistic sense of identity that merged individual and social identities.

Methods: Survey

Dataset: 429 respondents, closed-ended survey responses

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Communicating sex work through Reddit

This project explored the types of communication that emerged in r/SexWorkers, a subreddit designed to facilitate conversations between sex workers, clients, and other parties. Our findings indicated that communication in this platform revolved around risk mitigation, information exchange, and stigma.

Methods: Content Analysis

Dataset: 103 Reddit posts and 967 comments

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Reddit and politics after the Capitol riot

This study examined patterns in political conversations in r/politics and r/conservative following the January 6th Capitol riot. Our results suggest that Donald Trump received immediate backlash for his role in the riot, but that this weakened support was short-lived.

Methods: Content Analysis

Dataset: 400 Reddit posts and 1,999 comments

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Framing health workers and patients during COVID-19

This project explored the language used by news organizations and social media users to explain the role of healthcare workers and patients during the early COVID-19 pandemic. Did we see and describe these people as heroes? Martyrs? Victims?

Methods: Content Analysis

Dataset: 217 Reddit posts (and linked news articles) and 2164 comments

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Selected Ongoing Research

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Reddit as a platform for political identity

This developing project examines user activity in r/The_Donald and r/Conservative. Centrally, this research focuses on political conservativism and how this ideology is signaled by users of these subreddits.

Methods: Content Analysis, Linguistic Analysis

Dataset: 600+ Reddit posts and 40,000+ comments

Presidential framing of Kamala Harris

This ongoing project investigates the leadership framing of Kamala Harris during the 2024 presidential campaign, with a specific focus on how leadership portrayals by her supporters (users of the r/KamalaHarris subreddit) differed from Hillary Clinton in the 2016 campaign.

Methods: Content Analysis

Dataset: 500+ Reddit posts and 20,000+ comments

Ukrainian flag on a fence. Photo courtesy of noah eleazar on Unsplash.

Humanitarian efforts toward the Ukraine-Russia War

This project examines the strategies four United Nations humanitarian organizations discussed the Ukraine-Russia war during its emergence. Findings suggest that certain types of messages, and message features, encouraged positive (and stronger) responses from Facebook users than others.

Methods: Content Analysis

Dataset: 355 Facebook posts and approximately 3.8 million reactions