Ethical and Methodological Considerations of Twitter Data for Public Health Research: Systematic Review

Abstract

Background Much research is being carried out using publicly available Twitter data in the field of public health, but the types of research questions that these data are being used to answer and the extent to which these projects require ethical oversight are not clear. Objective This review describes the current state of public health research using Twitter data in terms of methods and research questions, geographic focus, and ethical considerations including obtaining informed consent from Twitter handlers. Methods We implemented a systematic review, following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, of articles published between January 2006 and October 31, 2019, using Twitter data in secondary analyses for public health research, which were found using standardized search criteria on SocINDEX, PsycINFO, and PubMed. Studies were excluded when using Twitter for primary data collection, such as for study recruitment or as part of a dissemination intervention. Results We identified 367 articles that met eligibility criteria. Infectious disease (n=80, 22%) and substance use (n=66, 18%) were the most common topics for these studies, and sentiment mining (n=227, 62%), surveillance (n=224, 61%), and thematic exploration (n=217, 59%) were the most common methodologies employed. Approximately one-third of articles had a global or worldwide geographic focus; another one-third focused on the United States. The majority (n=222, 60%) of articles used a native Twitter application programming interface, and a significant amount of the remainder (n=102, 28%) used a third-party application programming interface. Only one-third (n=119, 32%) of studies sought ethical approval from an institutional review board, while 17% of them (n=62) included identifying information on Twitter users or tweets and 36% of them (n=131) attempted to anonymize identifiers. Most studies (n=272, 79%) included a discussion on the validity of the measures and reliability of coding (70% for interreliability of human coding and 70% for computer algorithm checks), but less attention was paid to the sampling frame, and what underlying population the sample represented. Conclusions Twitter data may be useful in public health research, given its access to publicly available information. However, studies should exercise greater caution in considering the data sources, accession method, and external validity of the sampling frame. Further, an ethical framework is necessary to help guide future research in this area, especially when individual, identifiable Twitter users and tweets are shared and discussed. Trial Registration PROSPERO CRD42020148170; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=148170

Identifying Potential Lyme Disease Cases Using Self-Reported Worldwide Tweets: Deep Learning Modeling Approach Enhanced With Sentimental Words Through Emojis

“…Owing to the nature of Twitter data, the analysis requires developing and evaluating machine learning–based methodologies [ 61 , 72 ]. Figure 1 illustrates the methodology used to classify the tweets.…”

“…The use of tweets for academic research purposes is provided for in Twitter’s development policy and the consent form signed by users [ 61 ]. Social media data are publicly accessible data.…”

“…With the extended use of the internet and social media platforms where health-related information is often shared, researchers have found an opportunity to improve disease surveillance systems by leveraging web data [ 61 , 62 ]. This new field of research is referred to as digital surveillance or infodemiology [ 63 ].…”

“…Among all current social media platforms, Twitter is one of the most popular social media platforms, with over 145 million daily active accounts, and it is the most widely used data source for digital health owing to certain advantages: its data can be easily accessed through the Twitter application programming interface (API), the size of the text (tweets) is limited to 280 characters (140 characters before 2017), and it is possible to geolocate the tweets [ 64 ]. A recent systematic review suggested that less than half of existing studies on digital health surveillance using Twitter data were focused mainly on prediction, and only a few studies focused on developing tools for adequate analysis of these types of data [ 61 ]. Owing to the novelty of digital surveillance in public health research, there is an unevenness in the different methodological approaches and data sets used [ 63 ].…”

Using Twitter to Understand COVID-19 Vaccine-Related Ageism During the Pandemic

“…Our research did not seek ethics approval because our study was based on publicly available information ( Takats et al, 2022 ). More specifically, our research analyzed large volumes of text (i.e., tweets) that were publicly shared on Twitter and are typically not deemed human subject research ( JMIR, 2022 ).…”