TY  - JOUR
AU  - Xue, Jia
AU  - Zhang, Bolun
AU  - Zhang, Qiaoru
AU  - Hu, Ran
AU  - Jiang, Jielin
AU  - Liu, Nian
AU  - Peng, Yingdong
AU  - Li, Ziqian
AU  - Logan, Judith
PY  - 2023
DA  - 2023/5/15
TI  - Using Twitter-Based Data for Sexual Violence Research: Scoping Review
JO  - J Med Internet Res
SP  - e46084
VL  - 25
KW  - Twitter data
KW  - sexual violence
KW  - sexual assault
KW  - scoping review
KW  - review method
KW  - data analysis
KW  - data collection
KW  - Twitter
KW  - social media
KW  - women’s health
KW  - violence
KW  - abuse
KW  - public health
KW  - domestic violence
AB  - Background: Scholars have used data from in-person interviews, administrative systems, and surveys for sexual violence research. Using Twitter as a data source for examining the nature of sexual violence is a relatively new and underexplored area of study. Objective: We aimed to perform a scoping review of the current literature on using Twitter data for researching sexual violence, elaborate on the validity of the methods, and discuss the implications and limitations of existing studies. Methods: We performed a literature search in the following 6 databases: APA PsycInfo (Ovid), Scopus, PubMed, International Bibliography of Social Sciences (ProQuest), Criminal Justice Abstracts (EBSCO), and Communications Abstracts (EBSCO), in April 2022. The initial search identified 3759 articles that were imported into Covidence. Seven independent reviewers screened these articles following 2 steps: (1) title and abstract screening, and (2) full-text screening. The inclusion criteria were as follows: (1) empirical research, (2) focus on sexual violence, (3) analysis of Twitter data (ie, tweets or Twitter metadata), and (4) text in English. Finally, we selected 121 articles that met the inclusion criteria and coded these articles. Results: We coded and presented the 121 articles using Twitter-based data for sexual violence research. About 70% (89/121, 73.6%) of the articles were published in peer-reviewed journals after 2018. The reviewed articles collectively analyzed about 79.6 million tweets. The primary approaches to using Twitter as a data source were content text analysis (112/121, 92.5%) and sentiment analysis (31/121, 25.6%). Hashtags (103/121, 85.1%) were the most prominent metadata feature, followed by tweet time and date, retweets, replies, URLs, and geotags. More than a third of the articles (51/121, 42.1%) used the application programming interface to collect Twitter data. Data analyses included qualitative thematic analysis, machine learning (eg, sentiment analysis, supervised machine learning, unsupervised machine learning, and social network analysis), and quantitative analysis. Only 10.7% (13/121) of the studies discussed ethical considerations. Conclusions: We described the current state of using Twitter data for sexual violence research, developed a new taxonomy describing Twitter as a data source, and evaluated the methodologies. Research recommendations include the following: development of methods for data collection and analysis, in-depth discussions about ethical norms, exploration of specific aspects of sexual violence on Twitter, examination of tweets in multiple languages, and decontextualization of Twitter data. This review demonstrates the potential of using Twitter data in sexual violence research. 
SN  - 1438-8871
UR  - https://www.jmir.org/2023/1/e46084
UR  - https://doi.org/10.2196/46084
UR  - http://www.ncbi.nlm.nih.gov/pubmed/37184899
DO  - 10.2196/46084
ID  - info:doi/10.2196/46084
ER  -