**Condition or domain being studied**
A new coronavirus infection, called COVID-19, was first identified in Wuhan, China, in late 2019. COVID-19 is caused by coronavirus 2 of the severe acute respiratory syndrome (SARS-CoV-2), and has spread quickly to other countries – Pandemic declared by the World Health Organization (WHO, 2020). Opinions and feelings related to COVID-19 spread quite rapidly nowadays, thus likely influencing public behavior during the epidemic (Wang Z and Ye X, 2017). Nowadays, social media has become the main channel through which the public can obtain information and express their opinions and feelings (Han et al., 2020).
**Inclusion Criteria**
We will include studies that assessed COVID-19’s news distribution through any type of social media during the pandemic, without language restrictions. We will search for studies from November 2019 till now.
**Information sources**
Databases: PubMed, Embase, LILACS, Web of Science, Scopus, Altimetrics.
Grey literature: Google Scholar and OpenGray
Additional Search: Hand searches of reference list from included studies.
**Data management:** EndNote and Rayyan
**Selection Process**
The selection process will be done in two phases. Three independent reviewers will select the included articles. In phase one, the reviewers will read titles and abstracts to apply the eligibility criteria. In phase two, the same reviewers will perform a full text reading by applying the same eligibility criteria. In both phases, all the retrieved information will be crosschecked by the fourth review. Final selection will be always based on the full-text of the publication.
**Data collection process**
The data collection will be done by two independent reviewers. They will collect the data and insert them in a predefined spreadsheet. Subsequently, the retrieved information will be crosschecked. Any disagreement will be discussed between. If it is necessary, a third reviewer will be included in the discussion. The following data will be extracted and recorded for each included study: author; year of publication; country; characteristics of the social media; outcome measures; results, conclusion and study design.
**Risk of bias assessment**
JBI Critical Appraisal Checklist for Analytical Cross Sectional Studies
JBI Critical Appraisal Checklist for Cohort Studies
**Confidence in cumulative evidence**
Two independent reviewers will collect data from the selected articles and the level of evidence will be analyzed by using GRADE. Any disagreement will be discussed between them and the third reviewer.
**Data Synthesis**
We will perform a narrative synthesis based on the following outcomes:
Advantages and disadvantages of the use of social medial: we will synthesize in a qualitative analysis
Association between the type of social media and fake news (or news without scientific evidence): we will calculate odds ratio (OR)
Frequency of the most used social medias: we will use proportions (%)
Frequency of the each topic discussed: we will use proportions (%)
Qualitative analysis of the best good communication strategies: we will synthesize in a qualitative analysis
The results and the form to present and interpret them will be discussed between the authors.
**References**
1: Han X, Wang J, Zhang M, Wang X. Using Social Media to Mine and Analyze Public Opinion Related to COVID-19 in China. International Journal of Environmental Research and Public Health. 2020 Jan;17(8):2788.
2: O'Brien M, Moore K, McNicholas F. Social Media Spread During Covid-19: The Pros and Cons of Likes and Shares. Irish Medical Journal. 2020 Apr 3;113(4):52.
3: Liu Q, Zheng Z, Zheng J, Chen Q, Liu G, Chen S, Chu B, Zhu H, Akinwunmi B, Huang J, Zhang CJ. Health Communication Through News Media During the Early Stage of the COVID-19 Outbreak in China: A Digital Topic Modeling Approach. medRxiv. 2020 Jan 1.
4: Gao J, Zheng P, Jia Y, Chen H, Mao Y, Chen S, Wang Y, Fu H, Dai J. Mental health problems and social media exposure during COVID-19 outbreak. Plos one. 2020 Apr 16;15(4):e0231924.
5: Basch CE, Basch CH, Hillyer GC, Jaime C. The Role of YouTube and the Entertainment Industry in Saving Lives by Educating and Mobilizing the Public to Adopt Behaviors for Community Mitigation of COVID-19: A Successive Sampling Design. JMIR Public Health and Surveillance. 2020 Apr 10.
