Hannah Mieczkowski

12 papers receiving 984 citations

Hannah Mieczkowski's Hit Papers

Artificial intelligence in communication impacts language and social relationships 2023 · 110 citations
1100+1+3Years since publication100200300400

Peers

Hannah Mieczkowski
Comparison fields: 5 of 80
  • Applied Psychology 158
  • Communication 155
  • Health Informatics 18
  • Sociology and Political Science 554
  • Information Systems and Management 60
Replace Bingjie Liu with:
Bingjie Liu United States
Jianning Dang China
Philipp K. Masur Germany
Mufan Luo United States
Christa S. C. Asterhan Israel
Jeffrey N. Rokkum United States
T. Franklin Waddell United States
Eun Hwa Jung United States
Sven Joeckel Germany
Samuel Hardman Taylor United States
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Citations per year

Countries citing papers authored by Hannah Mieczkowski

Since Specialization
Citations

This map shows the geographic impact of Hannah Mieczkowski's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Hannah Mieczkowski with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hannah Mieczkowski more than expected).

Fields of papers citing papers by Hannah Mieczkowski

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Hannah Mieczkowski. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Hannah Mieczkowski. The network helps show where Hannah Mieczkowski may publish in the future.

Co-authors

The 18 scholars most cited alongside Hannah Mieczkowski, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Hannah Mieczkowski Line = papers co-authored together Hannah Mieczkowski links everyone, so they are left out of the graph.

All Works

12 of 12 papers shown
#Work
1
A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use
Hit paper breakdown →
2021487
2
Artificial intelligence in communication impacts language and social relationships
Hit paper breakdown →
2023110
3 202287
4 202160
5 202147
6 202147
7 202243
8 202035
9 201932
10 202031
11 202220
12 202215

About Hannah Mieczkowski

Hannah Mieczkowski is a scholar working on Sociology and Political Science, Communication, Social Psychology, Information Systems and Management and Artificial Intelligence, having authored 12 papers that have together received 1.0k indexed citations. Recurring topics across this work include Impact of Technology on Adolescents (6 papers), Social Media and Politics (3 papers), Digital Mental Health Interventions (2 papers), Social and Intergroup Psychology (2 papers), Ethics and Social Impacts of AI (2 papers), Technology Adoption and User Behaviour (2 papers), Death Anxiety and Social Exclusion (1 paper) and Digital Media and Philosophy (1 paper). The work is most often cited by research in Applied Psychology (158 citations), Communication (155 citations), Health Informatics (18 citations), Sociology and Political Science (554 citations) and Information Systems and Management (60 citations). Hannah Mieczkowski has collaborated with scholars based in United States, South Africa and United Kingdom. Frequent co-authors include Douglas A. Parry, Brittany I Davidson, Craig Sewall, Jacob T. Fisher, Jeffrey T. Hancock, Daniel Quintana, Xun Liu, Angela Y. Lee, Mor Naaman and Malte Jung. Their work appears in journals such as Proceedings of the ACM on Human-Computer Interaction, Computers in Human Behavior, Nature Human Behaviour, Current Opinion in Psychology and Cyberpsychology Behavior and Social Networking.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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