Each study was assessed for risk of bias on the following domains: randomization process, deviations from intended interventions, missing outcome data, measurement of the outcome, and selection of the reported results.
The mean effect was small ( g = −0.134, 95% confidence interval ). (2020) study had a sample size of 1570 subjects, while the Álvarez-Benjumea and Winter (2018) study had a sample size of 1469 tweets (nested in 180 subjects). Both studies evaluated the effectiveness of an online intervention for reducing online hate speech/cyberhate. However, we also present additional single effect sizes for the other treatment arms from the Álvarez-Benjumea and Winter (2018) study. For the purposes of the meta-analysis we chose the treatment arm from the Álvarez-Benjumea and Winter (2018) study that most closely aligned with the treatment condition in the Bodine-Baron et al. Two studies were included in the meta-analysis, one of which had three treatment arms. We computed a meta-analysis on two independent effect sizes. We extracted quantitative findings in the form of a standardized mean difference effect size. We coded characteristics of the intervention, sample, outcomes, and research methods. The systematic search covered Januto December 31, 2020, with searches conducted between Augand December 31, 2020, and supplementary searches undertaken between March 17 and 24, 2022. Eligible populations included youth (10–17 years) and adult (18+ years) participants of any racial/ethnic background, religious affiliation, gender identity, sexual orientation, nationality, or citizenship status. We included randomized and rigorous quasi-experimental studies of online hate speech/cyberhate interventions that measured the creation and/or consumption of hateful content online and included a control group. We systematically searched 2 database aggregators, 36 individual databases, 6 individual journals, and 34 websites, as well as bibliographies of published reviews of related literature, and scrutiny of annotated bibliographies of related literature. This review aimed to assess the effects of online interventions to reduce online hate speech/cyberhate. While there is some evidence of effective interventions to counter hate speech through television, radio, youth conferences, and text messaging campaigns, interventions for online hate speech have only recently emerged. The enormous frequency of hate speech/cyberhate within online environments creates a sense of normalcy about hatred and the potential for acts of intergroup violence or political radicalization. The unique feature of the Internet is that individual negative attitudes toward minoritized and racialized groups and more extreme, hateful ideologies can find their way onto specific platforms and instantly connect people sharing similar prejudices.
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