This article presents a bibliometric analysis of the field of misinformation detection, examining its evolution, trends, influential authors, collaborative networks, key terms, institutional affiliations, and research themes. The study analyzed 56 papers published between 2016 and 2022, focusing on misinformation detection, with an emphasis on the impact of misinformation on society, particularly in the context of the COVID-19 pandemic. The analysis highlights the role of social media in the spread of misinformation and the importance of verified sources in combating it. The study also identifies key contributors, such as King Saud University, and the top countries contributing to the field, including the USA, India, China, Spain, and the UK. The results show that IEEE Access is the most cited journal in the field, and that the majority of the research is concentrated in computer science and social sciences. The study also reveals that the number of papers on misinformation detection has increased significantly, especially in the wake of the pandemic. The analysis further identifies the top 10 most cited papers, which cover a range of topics, including the use of deep learning, natural language processing, and machine learning in detecting misinformation. The study concludes that misinformation detection is a critical area of research, with significant implications for public health, democracy, and information integrity. The findings suggest that collaboration among researchers, the use of advanced technologies, and the promotion of verified sources are essential in combating misinformation. The study also highlights the importance of interdisciplinary research in addressing the challenges posed by misinformation.This article presents a bibliometric analysis of the field of misinformation detection, examining its evolution, trends, influential authors, collaborative networks, key terms, institutional affiliations, and research themes. The study analyzed 56 papers published between 2016 and 2022, focusing on misinformation detection, with an emphasis on the impact of misinformation on society, particularly in the context of the COVID-19 pandemic. The analysis highlights the role of social media in the spread of misinformation and the importance of verified sources in combating it. The study also identifies key contributors, such as King Saud University, and the top countries contributing to the field, including the USA, India, China, Spain, and the UK. The results show that IEEE Access is the most cited journal in the field, and that the majority of the research is concentrated in computer science and social sciences. The study also reveals that the number of papers on misinformation detection has increased significantly, especially in the wake of the pandemic. The analysis further identifies the top 10 most cited papers, which cover a range of topics, including the use of deep learning, natural language processing, and machine learning in detecting misinformation. The study concludes that misinformation detection is a critical area of research, with significant implications for public health, democracy, and information integrity. The findings suggest that collaboration among researchers, the use of advanced technologies, and the promotion of verified sources are essential in combating misinformation. The study also highlights the importance of interdisciplinary research in addressing the challenges posed by misinformation.