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. 2021 Jun;116(Pt 2):104747.
doi: 10.1016/j.chiabu.2020.104747. Epub 2020 Sep 17.

Using social media data for assessing children's exposure to violence during the COVID-19 pandemic

Pouria Babvey  1 , Fernanda Capela  2 , Claudia Cappa  3 , Carlo Lipizzi  4 , Nicole Petrowski  5 , Jose Ramirez-Marquez  6
Affiliations

Using social media data for assessing children's exposure to violence during the COVID-19 pandemic

Pouria Babvey et al. Child Abuse Negl. 2021 Jun.

Abstract

Background: The COVID-19 pandemic brought unforeseen challenges that could forever change the way societies prioritize and deal with public health issues. The approaches to contain the spread of the virus have entailed governments issuing recommendations on social distancing, lockdowns to restrict movements, and suspension of services.

Objective: There are concerns that the COVID-19 crisis and the measures adopted by countries in response to the pandemic may have led to an upsurge in violence against children. Added stressors placed on caregivers, economic uncertainty, job loss or disruption to livelihoods and social isolation may have led to a rise in children's experience of violence in the home. Extended online presence by children may have resulted in increased exposure to abusive content and cyberbullying.

Participants and setting: This study uses testimonial-based and conversational-based data collected from social media users.

Methods: Conversations on Twitter were reviewed to measure increases in abusive or hateful content, and cyberbullying, while testimonials from Reddit forums were examined to monitor changes in references to family violence before and after the start of the stay-at-home restrictions.

Results: Violence-related subreddits were among the topics with the highest growth after the COVID-19 outbreak. The analysis of Twitter data shows a significant increase in abusive content generated during the stay-at-home restrictions.

Conclusions: The collective experience of the COVID-19 pandemic and related containment measures offers insights into the wide-ranging risks that children are exposed to in times of crisis. As societies shift towards a new normal, which places emerging technology, remote working and online learning at its center, and in anticipation of similar future threats, governments and other stakeholders need to put in place measures to protect children from violence.

Keywords: Abuse; Big data; COVID-19; Children; Cyberbullying; Social media; Violence.

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Figures

Fig. 1
Fig. 1
Approach to assessing change in cyberbullying and abusive or hateful content on Twitter.
Fig. 2
Fig. 2
Weekly number of abusive tweets per 100,000 population before and after the stay-at-home restrictions started by state. Note: The values for the District of Columbia are not presented in the maps.
Fig. 3
Fig. 3
Ratio between the number of tweets from November-December 2019 and March-April 2020 by whether the tweets were abusive or non-abusive. Note: A ratio above 1 indicates an increase in number of tweets.
Fig. 4
Fig. 4
Ratio between the number of tweets from November-December 2019 and March-April 2020, and the SI.
Fig. 5
Fig. 5
Ratio between the number of tweets from November-December 2019 and March-April 2020, and the HDI.
Fig. 6
Fig. 6
Ratio of the number of weekly posts to the average in the 18 months between January 2019 and July 2020 for selected subreddits. Note: Abuse-related subreddits are in bold.
Fig. 7
Fig. 7
Ratio of the number of daily posts before and after the stay-at-home restrictions started for selected subreddits. Notes: The size of the circles is proportional to the average daily number of posts for each subreddit. Small-size and mid-size subreddits are displayed on the left side of the figure and large subreddits are on the right side. OCD stands for obsessive-compulsive disorder; BPD stands for borderline personality disorder; DPDR stands for depersonalization and derealization; EOOD stands for exercise out of depression; SLP stands for speech-language therapy; and MMFB stands for make me feel better.
Fig. 8
Fig. 8
Number of newly active users on abuse-related subreddits before and after the stay-at-home restrictions started.
Fig. 9
Fig. 9
Average monthly number of posts for each of the five categories of abuse.
See this image and copyright information in PMC

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