Leticia Bode

7.9k total citations · 5 hit papers
76 papers, 4.6k citations indexed

About

Leticia Bode is a scholar working on Communication, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Leticia Bode has authored 76 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 60 papers in Communication, 53 papers in Sociology and Political Science and 18 papers in Artificial Intelligence. Recurrent topics in Leticia Bode's work include Social Media and Politics (59 papers), Misinformation and Its Impacts (34 papers) and Media Studies and Communication (18 papers). Leticia Bode is often cited by papers focused on Social Media and Politics (59 papers), Misinformation and Its Impacts (34 papers) and Media Studies and Communication (18 papers). Leticia Bode collaborates with scholars based in United States, United Kingdom and Russia. Leticia Bode's co-authors include Emily K. Vraga, Melissa Tully, Dhavan V. Shah, Sonya V. Troller‐Renfree, Kajsa E. Dalrymple, Stephanie Edgerly, Porismita Borah, Amy B. Becker, Kjerstin Thorson and Esther Thorson and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and Emerging infectious diseases.

In The Last Decade

Leticia Bode

73 papers receiving 4.3k citations

Hit Papers

See Something, Say Something: Correction of Global Health... 2015 2026 2018 2022 2017 2015 2015 2017 2020 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Leticia Bode United States 33 3.5k 2.8k 1.1k 540 509 76 4.6k
Emily K. Vraga United States 43 5.1k 1.4× 3.3k 1.2× 1.4k 1.3× 1.1k 2.1× 867 1.7× 108 6.6k
Edson C. Tandoc Singapore 42 4.8k 1.4× 4.3k 1.5× 998 0.9× 220 0.4× 554 1.1× 167 7.0k
Cristian Vaccari United Kingdom 31 2.4k 0.7× 2.3k 0.8× 747 0.7× 839 1.6× 153 0.3× 80 4.2k
Stephen A. Rains United States 35 2.8k 0.8× 1.7k 0.6× 725 0.6× 496 0.9× 584 1.1× 124 5.1k
Joseph E. Uscinski United States 26 3.2k 0.9× 1.1k 0.4× 957 0.9× 710 1.3× 240 0.5× 80 3.7k
Andrew M. Guess United States 24 3.4k 1.0× 2.4k 0.9× 1.1k 0.9× 193 0.4× 214 0.4× 37 4.3k
Rasmus Kleis Nielsen United Kingdom 35 3.0k 0.9× 3.7k 1.3× 574 0.5× 84 0.2× 260 0.5× 125 5.2k
Yan Jin United States 34 3.0k 0.9× 3.0k 1.1× 360 0.3× 406 0.8× 562 1.1× 119 4.6k
Emily Thorson United States 12 2.7k 0.8× 1.3k 0.5× 844 0.8× 163 0.3× 219 0.4× 20 3.2k
Porismita Borah United States 25 1.5k 0.4× 1.3k 0.5× 352 0.3× 334 0.6× 337 0.7× 90 2.4k

Countries citing papers authored by Leticia Bode

Since Specialization
Citations

This map shows the geographic impact of Leticia Bode'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 Leticia Bode with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leticia Bode more than expected).

Fields of papers citing papers by Leticia Bode

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leticia Bode. 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 Leticia Bode. The network helps show where Leticia Bode may publish in the future.

Co-authorship network of co-authors of Leticia Bode

This figure shows the co-authorship network connecting the top 25 collaborators of Leticia Bode. A scholar is included among the top collaborators of Leticia Bode based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Leticia Bode. Leticia Bode is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Liu, Ruihan, et al.. (2025). Assessing Menstrual Stigma: A Content Analysis of Menstrual Product Posts on Two Chinese Social Media Platforms. Women s Reproductive Health. 12(3). 593–618.
2.
Bode, Leticia, et al.. (2025). Automating Accuracy: Scalable Approaches to Correcting Disinformation With Artificial Intelligence on Social Media. Journalism & Mass Communication Quarterly. 102(4). 1044–1070.
4.
Tully, Melissa, et al.. (2024). Effects of a News Literacy Video on News Literacy Perceptions and Misinformation Evaluation. Media and Communication. 13. 1 indexed citations
5.
Ryan, Rebecca M., et al.. (2022). Parenting online: analyzing information provided by parenting-focused Twitter accounts. Atlantic Journal of Communication. 31(3). 243–259. 1 indexed citations
6.
Suk, Jiyoun, Dhavan V. Shah, Leticia Bode, et al.. (2022). Political Events in a Partisan Media Ecology: Asymmetric Influence on Candidate Appraisals. Mass Communication & Society. 26(2). 275–299. 1 indexed citations
7.
Vraga, Emily K., Melissa Tully, & Leticia Bode. (2021). Assessing the relative merits of news literacy and corrections in responding to misinformation on Twitter. New Media & Society. 24(10). 2354–2371. 47 indexed citations
8.
Vraga, Emily K. & Leticia Bode. (2021). Addressing COVID-19 Misinformation on Social Media Preemptively and Responsively. Emerging infectious diseases. 27(2). 396–403. 85 indexed citations
9.
Singh, Lisa, et al.. (2020). Understanding high- and low-quality URL Sharing on COVID-19 Twitter streams. Journal of Computational Social Science. 3(2). 343–366. 45 indexed citations
10.
Bode, Leticia, Emily K. Vraga, & Melissa Tully. (2020). Correcting Misperceptions About Genetically Modified Food on Social Media: Examining the Impact of Experts, Social Media Heuristics, and the Gateway Belief Model. Science Communication. 43(2). 225–251. 43 indexed citations
12.
Vraga, Emily K., et al.. (2019). Accidentally Attentive:Comparing visual, close-ended, and open-ended measures of attention on social media. Computers in Human Behavior. 99. 235–244. 29 indexed citations
13.
Connolly, Jennifer M., et al.. (2018). Explaining the Varying Levels of Adoption of E-government Services in American Municipal Government. State and Local Government Review. 50(3). 150–164. 10 indexed citations
14.
Bode, Leticia, Emily K. Vraga, & Kjerstin Thorson. (2018). Fake News. Oxford University Press eBooks. 2 indexed citations
15.
Vraga, Emily K. & Leticia Bode. (2017). Using Expert Sources to Correct Health Misinformation in Social Media. Science Communication. 39(5). 621–645. 331 indexed citations breakdown →
16.
Vraga, Emily K., Leticia Bode, & Sonya V. Troller‐Renfree. (2016). Beyond Self-Reports: Using Eye Tracking to Measure Topic and Style Differences in Attention to Social Media Content. Communication Methods and Measures. 10(2-3). 149–164. 117 indexed citations
17.
Bode, Leticia. (2016). Closing the gap: gender parity in political engagement on social media. Information Communication & Society. 20(4). 587–603. 94 indexed citations
18.
Vraga, Emily K., Leticia Bode, Chris Wells, Kevin Driscoll, & Kjerstin Thorson. (2013). The Rules of Engagement: Comparing Two Social Protest Movements on YouTube. Cyberpsychology Behavior and Social Networking. 17(3). 133–140. 17 indexed citations
19.
Edgerly, Stephanie, Leticia Bode, Young Mie Kim, & Dhavan V. Shah. (2012). Campaigns go social: Are Facebook, YouTube and Twitter changing elections?. 82–99. 3 indexed citations
20.
Bode, Leticia, et al.. (2011). Putting New Media in Old Strategies: Candidate Use of Twitter During the 2010 Midterm Elections. SSRN Electronic Journal. 2 indexed citations

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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