Research

Algorithmic Literacy

All social media apps, and many other online services, now use algorithms to determine what content their users see. The question is: How aware are users of these algorithms? This new project aims to formalize the study of algorithmic literacy, in terms of its definition, its measurement, and what it tells us about what users know.

Related publications / presentations

Oeldorf-Hirsch, A. & Neubaum, G. (2023). Attitudinal and behavioral correlates of algorithmic awareness among German and U.S. social media users. Journal of Computer-Mediated Communication, 28(5). https://doi.org/10.1093/jcmc/zmad035

Oeldorf-Hirsch, A. & Neubaum, G. (2023). What do we know about algorithmic literacy? The status quo and a research agenda for a growing field. New Media & Society, 0(0). https://doi.org/10.1177/14614448231182662

Funding

Fulbright Fellowship (2021), Fulbright U.S. Scholar Program with Fulbright Germany. Hosted at Universität Duisburg-Essen: €14,400.

Social media user experience with algorithmic transparency cues (PI, 2023). Scholarship Facilitation Fund, Office of the Vice President of Research, University of Connecticut: $2,000.

Assessing predictors of algorithmic literacy across U.S. and German social media users (PI, 2022). SFF, OVPR, UConn: $2,000.

News and Mis/Disinformation on Social Media

The majority of Internet users now get at least some of their news through social media apps. My initial research exploring this, starting in 2010, looked at how users assess learn from and assess the credibility of news they find on social media. Given the growing problem with misinformation and disinformation, particularly since 2016, more recent work has focused on how to combat this with literacy interventions and design changes.

Select publications / presentations

Oeldorf-Hirsch, A., Schmierbach, M., Appelman, A., & Boyle, M. P. (2023). The influence of fact-checking is disputed! The role of party identification in processing and sharing fact-checked social media posts. American Behavioral Scientist, 0(0). https://doi.org/10.1177/00027642231174335

Oeldorf-Hirsch, A., & Srinivasan, P. (2022). An unavoidable convenience: How post-Millennials engage with the news that finds them on social and mobile media. Journalism, 23(9), 1939-1954. https://doi.org/10.1177/1464884921990251

Oeldorf-Hirsch, A., Schmierbach, M., Appelman, A., & Boyle, M.P. (2020). The ineffectiveness of fact-checking labels on news memes and articles. Mass Communication and Society, 23(5), 682-704. https://doi.org/10.1080/15205436.2020.1733613

Oeldorf-Hirsch, A. & DeVoss, C. (2020). Who posted that story? Processing layered sources in Facebook news posts. Journalism & Mass Communication Quarterly¸ 97, 141-160. https://doi.org/10.1177/1077699019857673

Oeldorf-Hirsch, A., (2018). The role of engagement in learning from active and incidental news exposure on social media. Mass Communication and Society, 21, 225-247. https://doi.org/10.1080/15205436.2017.1384022. Winner of the 2019 AEJMC Mass Communication and Society Division Article of the Year Award.

Funding

Social media literacy interventions for climate change misinformation (Co-PI; Schmierbach, Appelman, & Boyle). News Literacy Fund, College of Communications, Pennsylvania State University: $4,000.

question on facebook

Information Seeking via Social Networking Sites

Online social networks such as Facebook have grown into rich repositories of information that in certain cases are more useful and beneficial than search engines and other online resources. This research explores how people understand their social networks in terms of the information they contain and how they can successfully target these networks with information needs such as product recommendations, opinions, or favor requests.

Related publications / presentations

Oeldorf-Hirsch, A., & Gergle, D. (2020). ‘Who knows what’: Audience targeting for question asking on Facebook. Proceedings of the ACM on Human-Computer Interaction, 4(GROUP), 20 pages. https://doi.org/10.1145/3375191

Oeldorf-Hirsch, A., Hecht, B., Morris, M. R., Teevan, J., & Gergle, D. (2014). To search or to ask: The routing of information needs between traditional search engines and social networks. Proceedings of the 2014 Conference on Computer Supported Cooperative Work (CSCW '14). https://doi.org/10.1145/2531602.2531706

Science Communication

This research area started as a collaboration with researchers in Ecology and Evolutionary Biology, Journalism, and Education. The purpose was to assess the training methods used in a joint graduate STEM/undergraduate journalism science communication course in which scientists are trained to communicate their research to the public via media. It has since grown to assessments of science communication / communicators on social media.

Related publications / presentations

Coletti, A., McGloin, R., Oeldorf-Hirsch, A., & Hamlin, E. (2022). Science communication on social media: Examining cross-platform behavioral engagement. The Journal of Social Media in Society, 11(2), 236-263. https://thejsms.org/index.php/JSMS/article/view/995

Capers, R. S., Oeldorf-Hirsch, A., Wyss, R., Burgio, K. R., & Rubega, M. A. (2022). What did they learn? Objective assessment tools show mixed effects of training on science communication behaviors. Frontiers in Communication, 6(February), 1–11. https://doi.org/10.3389/fcomm.2021.805630

Rubega, M. A., Burgio, K. R., MacDonald, A. A. M., Oeldorf-Hirsch, A., Capers, R. S., & Wyss, R. (2020). Assessment by audiences shows little effect of science communication training. Science Communication, Online First. https://doi.org/10.1177/1075547020971639

Funding

Training STEM graduates to communicate in the digital age, and measuring whether it works (Senior Personnel; PI Rubega). National Science Foundation Research Traineeship (NRT) Program, 8/1/2015-7/31/2018; $500,000

Promoting equity, inclusion, and belonging: Examining women in STEM on TikTok (Co-PI; Steinke & Suk, 2022). Research in Academic Themes 2022 Funding Initiative, College of Liberal Arts & Sciences, UConn: $50,000.

Additional Select Publications

Pierre, L., Oeldorf-Hirsch, A., & Yang, Y. (2023). Exploring the effects of media format and disclosure of native Twitter ads on consumer evaluations and decision-making. Journal of Promotion Management, 11(5), 607-643. https://doi.org/10.1080/10496491.2022.2163039

Oeldorf-Hirsch, A., & Chen, Y. (2022). Mobile mindfulness: Predictors of mobile screen time tracking. Computers in Human Behavior, 129, 107170. https://doi.org/10.1016/j.chb.2021.107170

Obar, J. & Oeldorf-Hirsch, A. (2022). Older adults and “The biggest lie on the Internet”: From ignoring social media policies to the privacy paradox. International Journal of Communication, 16, 4779-4800. https://ijoc.org/index.php/ijoc/article/view/17146/3919

Obar, J. A. & Oeldorf-Hirsch, A. (2020). The biggest lie on the Internet: Ignoring the privacy policies and terms of service policies of social networking services. Information, Communication & Society, 23, 128-147. https://doi.org/10.1080/1369118X.2018.1486870

Oeldorf-Hirsch, A., High, A. C., & Christensen, J. L. (2019). Count your calories and share them: Health benefits of sharing mHealth information on social networking sites. Health Communication, 34(1), 1130-1140. https://doi.org/10.1080/10410236.2018.1465791

McGloin, R. & Oeldorf-Hirsch, A. (2018). Challenge accepted! Evaluating the personality and social network characteristics of individuals who participated in the ALS Ice Bucket Challenge. The Journal of Social Media in Society, 7, 443-455. https://thejsms.org/index.php/TSMRI/article/view/317

High, A., Oeldorf-Hirsch, A., & Bellur, S. (2014). Misery rarely gets company: The influence of emotional bandwidth on supportive communication on Facebook. Computers in Human Behavior, 34, 79-88. https://doi.org/10.1016/j.chb.2014.01.037

Full CV: http://bit.ly/aoh_cv