Using Twitter-Based Data for Sexual Violence Research: Scoping Review

Abstract

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.

Bridging and Bonding Social Capital by Analyzing the Demographics, User Activities, and Social Network Dynamics of Sexual Assault Centers on Twitter: Mixed Methods Study

“…Our findings align with the broader literature on social capital, specifically bridging and bonding social capital. Among the various social media platforms, Twitter emerges as a valuable data set to study sexual violence [ 46 ] as well as a notable facilitator of bridging social capital, consistent with previous research that has underscored Twitter’s ability to connect organizations with a diverse and expansive audience [ 22 ].…”

Topic Modeling mediante Machine Learning no supervisado de artículos científicos sobre Salud Laboral y Servicios de Atención de Salud a Domicilio

“…Además, el empleo de AS también ha sido empleado en las ciencias de la salud para diversos objetivos. Estudios de tendencias de violencia sexual en institutos mediante el uso de Twitter (15) , estudios epidemiológicos de las enfermedades transmitidas por los mosquitos (16) , estudio de riesgo de suicidios en la población (17) , herramienta de análisis de ciencias alimentarias y nutrición (18) , y por supuesto, también se ha empleado con éxito para la monitorización de brotes epidemiológicos durante la crisis del COVID-19 (19) .…”