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Abstract

Racism evolves over time, adapting to new contexts such as online spaces, where anonymity enables widespread expression of racist views. Researchers have developed measures of online racism, but these measures can overlook the nuanced context in which online racism occurs. Research using digital qualitative methods may help uncover insights into experiences of online racism, its impacts, and strategies to mitigate its effects. This protocol describes a ‘methodological strips’ approach, integrating multiple research strategies to explore online racial discrimination. This approach pragmatically combined techniques found in rapid collective auto-ethnography, digital anthropology, and photo-voice to develop a protocol to capture the complexity of online racial discrimination. A diverse team of scholars completed the Very Brief Online Racism Measure and then submitted screenshots of online racial discrimination, accompanied by reflections on their emotional, mental, and behavioral responses. We then revisited online micro-contexts where incidents occurred. Findings suggest that a screenshotting protocol should consider the possibility that greater social media usage increases exposure to online racial discrimination, with the nature of these experiences being shaped by online behaviors (e.g., posting in comment sections). Reactions to online racial discrimination varied, including rumination, distress, desensitization, and disengagement. Micro-contexts appeared to play a role in mitigating or intensifying the impact of racist content. Exposure to online racial discrimination may depend on the historical moment and algorithms that respond to user engagement. Screenshot methods may take a psychological toll on both research participants and researchers who code the data. We present a screenshotting protocol that can be used to refine measurement tools and deepen understanding of how online racism is perceived and processed. Future research may explore the need for protective measures in the face of online racism.

Keywords

online racism discrimination digital ethnography

Background

Racism has a profound impact on mental health, and emerging research continues to explore how racism impacts our mental health (Bailey et al., 2017; Bourabain & Verhaeghe, 2021). One major way that racism impacts mental health is through racial discrimination, defined as the experience of negative treatment of members of marginalized racial/ethnic backgrounds (Williams et al., 1997), which studies have shown can increase risk for mental health problems (Paradies et al., 2015; Williams & Mohammed, 2009). Most racial discrimination measures are based on self-report, which can be vulnerable to perception biases (Lewis et al., 2015). Refining racial discrimination measures is critical, as inconsistencies often emerge when comparing cross-sectional self-reported frequency of past exposure with more ‘in the moment' frequency via intensive longitudinal data collection. For instance, individuals may report experiencing discrimination ‘all of the time’ on cross-sectional studies but may report no incidents of discrimination when asked multiple times daily over a period of two weeks. While we can expect a certain level of discrepancies that may reflect reporting biases tied to specific data collection strategies, we acknowledge that measurement of racial discrimination purely based on self-report using existing scales remains a challenge and requires reconciliation through complementary methods.

Manifestations of racism can ‘shapeshift’ over time, adapting to new contexts, and necessitating innovative methods for capturing its existence and impact. The advent of the Internet presented a need to examine how racism has evolved in this space. Online platforms can often provide anonymity, enabling individuals to conveniently and widely express racist views without fear of direct consequences (Keum & Miller, 2018a). Scholars have referred to ‘dissociative anonymity’ to describe how people may feel that they can hide or change their identities online, resulting in a disinhibition effect that allows them to act differently than they would in person and express socially deviant views (Barlett & Scott, 2023; Suler, 2004; Wu et al., 2017). This creates avenues for people of color to be subjected to online racial discrimination, profoundly affecting their mental health and well-being. To better understand these experiences, online racial discrimination measures were developed to capture the frequency of such experiences, which includes exposure to texts, videos, images, and symbols that reflect racist views and ideologies. Online racism measures assess for direct attacks (e.g., harassment, threats, or bullying) but also vicarious exposures to negative content, messages, or interactions (Bliuc et al., 2018; Keum & Miller, 2017; Tynes et al., 2018; Volpe et al., 2021). Qualitative approaches have allowed the examination of rich and distinctive insights and lived experiences of how people experience online racial discrimination (Keum, 2017).

Aims

In this ‘Method and Protocol’ commentary, we sought to develop a protocol to understand how individuals interpret and experience online racial discrimination. The online context offers a unique advantage by allowing researchers to directly observe racial discrimination, something rarely possible in offline settings. We developed an eclectic methodological ‘strips’ approach that combines techniques from ethnography (rapid, digital, collective auto-ethnography), photovoice, and critical visual methodology, to explore how online racial discrimination is perceived. This protocol provides insights into how to explore the lived realities of online racism.

Method

Justification of Method and Study Design

In developing this protocol, we adapted a ‘methodological strips’ approach to data collection and analysis. The concept of ‘strips’ is a hallmark of the social work profession (see Letha See’s concept of theoretical strips; Lee See, 1998), which posits that theories of human development are based on samples of White populations and largely inadequate in describing the unique experiences of people of color. Thus, scholars can use theoretical strips to draw from an eclectic range of theories to best capture the experiences of diverse populations. Similarly, we use methodological strips to borrow and combine strategies as a pragmatic way to grapple with a complex phenomenon.

Our protocol draws heavily from ethnography, which is a methodology used to understand cultures and social processes through participant observation in naturalistic settings (Brewer, 2000). Ethnography has been used to capture racism in many forms and across domains (Bansal et al., 2022; Vaught, 2011). In recent years, ethnography has been conducted rapidly in the field of public health, particularly when researchers are also members of the populations being studied, enabling deeper insight and authenticity to generate short-term and immediately applicable outcomes (Oh & Yamada, 2021). In this study, we extended this approach by incorporating elements of collective auto-ethnography, as we examined our own lives while coming together to share our observations as a group (Chang, 2016). This auto-ethnographic exercise has been critical for helping us develop a safe and acceptable protocol in an expeditious manner before launching the protocol with real study participants in a full-scale study. Additionally, we drew upon techniques from digital ethnography, which has been increasingly used to understand online spaces as sites of cultural analysis (Boellstorff, 2015).

To further enrich our approach, we integrated principles of photo-voice, using our smartphones and computers as tools to visually document and interpret the world through our own perspectives. Photovoice has been used as a participatory method often with marginalized communities, where participants take photos to document, communicate, and reflect on their experiences (Wang & Burris, 1997), pertaining to a range of topics in health and public health research (Catalani & Minkler, 2010). Now that phones and computers can easily take screenshots, the principles of photovoice have carried forward into a digital age. Photovoice has previously been used to allow people to share their experiences of racism (Hassen, 2025; Ornelas et al., 2009).

By employing an eclectic methodology —that is, drawing from multiple perspectives and coalescing different methods —we set forth a protocol to critically and flexibly engage with our lived experiences while capturing digital artifacts that reflect the online spaces we navigated. As a pilot study to develop this protocol, we analyzed our experiences of online racial and ethnic discrimination observed between December 6, 2024 - February 1, 2025.

Recruitment and Participants

A subset of authors served as study participants (N = 7) to understand what tasks we would ask future participants to perform. We limited all screenshots to content that was publicly available on the Internet. The research team was instructed the to use social media platforms as usual but not actively seek out content for the purposes of this study. We censored individual identity markers as necessary. Our team is diverse and represents a range of ethno-racial backgrounds, including people who identify as Black, Asian, multiracial Asian/Hispanic, and White. We are also all scholars and students in higher education, and interpret our findings from our positions in academia. We acknowledge that race is a social construct, and that there is tremendous heterogeneity within racial groups. We also acknowledge that our own positionalities are complex and include many other aspects of identity, such as gender, sexual orientation, and immigration status.

Protocol

We began by completing the Very Brief Online Racism Measure (Keum, 2021), which served as a ‘calibration’ activity for the team to both understand our past experiences with online racial discrimination, and prepare us for what to pay attention to in the screenshotting activity. Primed by the six items, we submitted screenshots of online racial discrimination that we encountered, accompanied by concise descriptions of how these incidents impacted us emotionally or behaviorally Table 1.

Table 1.

Online Racism Scale – Very Brief

Instruction: We are interested in your personal experiences of racism in online settings as you interact with others and surf the Internet. As you answer the questions below, please think about your online experiences in the past 6 months.

Please rate your responses based on the following options: 1 = Never, 2 = Rarely, 3 = Sometimes, 4 = Often, 5 = Always.

In the past 6 months, I have…

1. Seen other racial/minority users receive racist comments.

2. Encountered online hate groups/communities against non-White racial/ethnic groups.

3 Seen photos that portray my racial/ethnic group negatively.

4. Been informed about a viral/trending racist event that I was not aware of.

5. Seen online videos (e.g., YouTube) that portray my racial/ethnic group negatively.

6. Received posts with racist comments.

All screenshots and comments were cataloged in a de-identified format for analysis. When available, we also re-visited the websites where instances of online racial discrimination occurred to gather additional context. We sought to uncover insights into our own experiences making sense of the online racial discrimination. Our objective was to analyze our interpretations of the items related to the online racism measurement, while concurrently documenting our personal understandings of the concept of online racism. However, we conducted participant observation over the course of approximately one month (Harris et al., 1997; Sangaramoorthy & Kroeger, 2020).

Procedure

In working through this protocol, we present initial results of our observations and memos about the process of exploring online racial discrimination incidents through screenshots. We also analyzed our written responses describing our reactions to online racism using reflexive thematic analysis (Braun & Clarke, 2006).

Greater Social Media and Internet Usage Allowed for More Occasions to Experience Online Racism

We found that the extent of online racial discrimination we experienced was closely linked to our overall social media and Internet usage patterns. While some of us minimized social media use, others were frequent users and had more occasions to experience online racial discrimination. The type of online racism we encountered often depended on our specific online activities. For example, the likelihood of experiencing direct online racial discrimination, such as being the target of a racist comment, was directly linked to how frequently we participated in social media (e.g., engaging in the comment sections). Notably, regardless of the use frequency, we tended to report vicarious online racial discrimination, such as viral news stories. Future research may consider that there is a significant group of people who actively avoid social media due to past experiences of online racial discrimination or because they have witnessed online racial discrimination around them. Overall, we generated 25 submissions over two months across seven team members.

Reactions to Online Racism Varied Across Situations and Individuals

Our reactions to these events varied widely. At times, we found ourselves ruminating and feeling deeply disturbed, replaying the images in our minds. At other times, we became desensitized and ignored the incidents altogether or were only mildly offended. Our responses included feelings of sadness, shock, numbness, anger, and confusion. We noticed that different coping styles significantly influenced how we engaged with social media. For some, these experiences of online racism led to disengagement, avoiding social media comments sections, unfollowing accounts, and unsubscribing to certain channels. For others, online racism prompted more active participation, such as posting comments, or ‘disliking’ (thumbs down) the content. Some of us felt some degree of uncertainty at times, unsure if what we were viewing was online racism and how we should feel about it.

Micro-Contexts can Intensify or Mitigate the Impact of Online Racism

We use the term micro-context to describe the immediate digital space surrounding a given online artifact. We found that these micro-contexts included how online racism was presented and framed, which significantly influenced its impact. For example, the overall sentiment surrounding the racist content —such as comments of condemnation, a call to action, or evidence of justice being served —would often mitigate the impact of the racist content. Certain types of content appeared to have a protective effect. As one team member reflected, “I felt briefly vindicated and glad that she [the perpetrator of racism] was going to experience some sort of backlash or get canceled for what she did.” Similarly, videos in which victims shared their experiences and informed the audience of some sort of resolution were less distressing to watch. These instances created a perception of exposure and shame for the perpetrator, fostering a collective alliance with the victim and shared indignation toward racism, which seemed to produce a less bothersome reaction to the content. However, online racist content that was surrounded by racist comments and no indication of any condemnation of the content appeared to feel more distressing. A key area of future research is to understand who the perpetrators of online racial discrimination are, who the targets are, and who is observing. This is not always clear in online spaces, where identities may be anonymized or otherwise masked (e.g., a profile picture of a cat) or where people can be impersonated or present an online persona that is not phenotypically similar to their offline persona (Keum & Miller, 2018b).

Using Multiple Platforms can Lead to Repeated Exposures

People are frequently exposed and re-exposed to online racist content, particularly when such content “goes viral” and spreads across multiple platforms (Keum & Miller, 2018b). Respondents who use multiple platforms may encounter the same content repeatedly, especially given the symbiotic relationship between TikTok and Instagram, where TikTok content is often aggregated, compiled, and widely disseminated on Instagram. We noticed that we were sometimes exposed to content that had occurred a few years prior to our data collection, meaning online racist content can resurface. Engagement by viewing content and taking screenshots may also cause algorithms to show even more content of the same nature. However, in a way, this resurfacing is consistent with notions that social stressors are not discrete events with rigid start and end points —social stressors often endure and proliferate, waxing and waning in intensity over time.

Historical Timing May Yield Different Results

Endorsement of online racism may be influenced by the historical and social context at the time of data collection. For instance, the timing of data collection (e.g., immediately following the high-profile killing of an unarmed Black person) could heighten racial tensions, amplify public discourse about race, and increase exposure to both overtly racist views and counter-narratives, as observed in the year 2020 (Lupu et al., 2023). Such events often provoke polarized discussions online, creating more opportunities to witness or participate in conversations laden with racial bias or racial discrimination. In our study, the data collection occurred during a politically charged period, which was the month leading up to the 2024 election of Donald Trump, his inauguration, and his first month as president. This timeframe was marked by both heightened racial and political rhetoric, but also a disengagement from media out of fatigue and despondency. However, it is possible that our findings would have been different had data collection taken place following an event where justice prevailed, such as a high-profile case where a perpetrator of racism was held accountable (e.g., the guilty conviction of the officer responsible for killing George Floyd). Such an event can alter discourse toward a tone of vindication, accountability, and social progress, underscoring the importance of considering the broader historical and social backdrop when interpreting findings related to online racism. Moreover, since data analysis and interpretation tends to occur after the data collection, the researchers should be mindful that they may be interpretting the data at a different historical moment with the advantage of hindsight.

Analysis Requires an Eclectic Use of Approaches

While we all began the screenshotting activity by completing the online racism scale and reflecting on its measures, we found that even within our team, the types of submissions people contributed were heterogeneous and complex. This unpredictability posed a challenge in selecting a qualitative analytic approach, and we realize that a screenshotting protocol will need to employ several strategies to analyze a variety of experiences and interpretations.

First, we found that we needed to analyze how participants perceived and interpreted their experiences of online racial discrimination. This includes examining how they understood the context, identified implicit messages, and distinguished between intentional racism, satire, or ambiguous content. Participants’ ability to interpret these events may have been influenced by their personal histories, cultural knowledge, and sensitivity to subtle forms of discrimination.

Second, we needed to analyze our own perspectives as we revisited the virtual spaces in which the online racial discrimination occurred. This step involved interpreting the content in its original context, including any accompanying comments, visuals, or interactions that may not have been immediately apparent to the participant. This dual perspective allowed us to compare the participant’s initial experience of the event with our own observations, identifying any discrepancies or additional insights.

The inherently ambiguous nature of online racial discrimination adds another layer of complexity to the analysis. Context and intention are not always clear in digital content. For instance, sarcasm or satire may be misinterpreted as racial discrimination, or subtle microaggressions might be dismissed as harmless by some but deeply felt by others. This ambiguity requires careful consideration and nuanced interpretation in the analytic process.

In one instance, a member of our team reported an experience that would be more appropriately labelled as ‘prejudice’, describing an event where an Asian person made a comment about a specific Asian ethnic group, rather than mistreatment from the White group against a minoritized groups. This is an example of how screenshotting can help us consider measurement errors, as we would not technically consider this racial discrimination per se, even though many people might consider the event as ‘racism’.

Given these challenges, a multi-layered analytic framework is essential to capture how online racism is experienced, perceived, and interpreted across diverse individuals and settings.

Our preliminary findings led us to develop an approach to data collection and analysis that falls in the tradition of pragmatism (Vaismoradi et al., 2013), requiring a fair amount of flexibility while ‘borrowing’ strips of other qualitative methodologies. Consistent with the methodological strips approach, we concluded that screenshotting requires multiple analytic strategies to analyze the range of qualitative data that we generated. Researchers who employ only a single qualitative approach when studying complex social phenomena may suffer from the “precariousness of a one-legged stool” (Hall & Rist, 1999). A pluralistic view of qualitative research is needed to meet the complexity of the data generated (Chamberlain et al., 2011). As such, we propose using the concept of ‘strips’ to describe the eclectic use of approaches to analyze and interpret screenshots. In Table 2, we present a contingency table that may help lay out potential analytic strategies that can be used for screenshots.

Table 2.

Contingency Tables for Analysis

If the respondents send screenshots of…	Then we will use…	To understand…	Examples
Dialogue, comments	Critical discourse analysis	The racist language and conversations that occur online	Are there socio-demographic differences in the way people talk about, understand, or communicate racism? What words do people use? How do people use coded language to communicate racist ideas without saying overtly racist things? How is racism implicitly integrated into political rhetoric?
Tweets, news stories	Content analysis	The frequency that a racist idea is mentioned	How often does micro-aggression appear in the content that people submit?
Images or links	Memoing⁶⁰	The micro-contexts of content	How is the distressing nature of racist videos mitigated by the comments denouncing the racist actions?
Experiences of online racism, screenshot captions	Interpretive phenomenological analysis	Sense-making of online racism	How do people make sense or meaning of their experiences of online racism?

For example, when respondents provide screenshots of tweets or news headlines, we may need to use content analysis (Hsieh & Shannon, 2005) to count the number of words or images related to racism that come up in the screenshots. But when screenshots involve remarks made in the comments section of social media or in an online forum, it may be necessary to use critical discourse analysis to gain a sense of who said what to whom and when, why, and how was it said, paying attention to the language being used, how the sentences are structured, the omissions, and the power dynamics across parties within various digital contexts (Blommaert & Bulcaen, 2000). When we ask participants to comment briefly on how they were impacted by the online racial discrimination, we can analyze their responses using reflexive thematic analysis (Braun & Clarke, 2006), coding both inductively and deductively. Throughout the entire data collection and analysis, we can use qualitative ‘memoing’ to reflect on all the screenshots as a whole (Razaghi et al., 2015). Interpretive phenomenological analysis (Smith, 2011) offers a useful concept of the ‘double hermeneutic’, where participants are making sense of their experiences, while the researchers also make sense of what the participants are experiencing. This double hermeneutic may be essential for driving the field of online racism measurement forward. But given the interpretive nature of the analysis, it may be beneficial to assess the racial attitudes, biases, and awareness of the coders (e.g., implicit bias tests), and ascertain the need for consciousness raising. Nonetheless, we note that regular team meetings are necessary while conducting a methodological strips approach in order to check for blind spots and biases.

Ethical Considerations

We were concerned that prompting participants to actively document instances of online racial discrimination in their lives may inadvertently encourage them to seek out or focus on such exposures, potentially increasing their encounters with harmful content. This process of screenshotting social media posts could also have unintended consequences on platform algorithms, where interacting with and capturing certain content might inadvertently signal increased interest in similar topics, leading algorithms to prioritize and amplify the appearance of online racist content in their feeds. Further, drawing heightened attention to online racism could raise participants’ awareness of these incidents, forcing them to engage more deeply with experiences they might otherwise dismiss or avoid. Asking participants to slow down, reflect on, and process these encounters could impose a heavier emotional toll, increasing feelings of distress, anger, or helplessness. Our experiences suggest the need for strategies to minimize harm, such as providing participants with support resources or ensuring opportunities for debriefing and emotional processing during the study.

The researchers conducting research on online racism also face significant risks, as they are inevitably exposed to a steady stream of racist content throughout the research process. This exposure can include receiving hundreds of images depicting subtle to explicit forms of online racism, revisiting virtual spaces where such content proliferates, and constantly confronting a racist reality. The cumulative effect can be distressing, potentially leading to emotional exhaustion, secondary trauma, or burnout. To mitigate these adverse effects, it is essential to adopt strategies that prioritize the mental health and well-being of the research team. Distributing the workload across a large and diverse team can help prevent any one individual from bearing the brunt of the exposure to online racism. Regular team check-ins can provide an opportunity for members to share their experiences, process emotions, and offer mutual support. Creating a supportive environment where team members feel safe discussing how they are impacted by viewing online racist content is critical. Additionally, implementing structured debriefing sessions can help researchers collectively process the harmful content they encounter and reaffirm their shared commitment to denouncing and addressing racism. Providing access to mental health resources can further support researchers in managing the psychological toll of this work. Establishing clear boundaries, such as limiting the amount of time spent reviewing harmful content or setting a cap on daily exposures, may also help reduce the risk of burnout.

Logistical Considerations

There were several logistical challenges we needed to address when collecting screenshots. First, we had to ensure that the files being shared were free from viruses or malware, which required implementing secure file transfer methods and thorough scanning protocols. Second, we only viewed public content for this protocol, but realize that in the future, gaining access to closed or private groups will pose a challenge, as these spaces often require permissions or invitations, limiting our ability to capture content from those environments. Finally, it was essential to protect the privacy of individuals involved, particularly in direct message exchanges. This means censoring personal identifiers, such as usernames, profile pictures, and other sensitive details, to maintain ethical standards and safeguard participants’ anonymity.

Discussion

In this study, we sought to develop a protocol to understand how people experience online racial discrimination, adopting a methodological strips approach that combines elements of rapid digital collective auto-ethnography with photovoice techniques and multiple analytic strategies. Since very few protocols have been developed toward this end, we became the subjects of the research and personally immersed ourselves into the data collection process using our own lived experiences to understand how we might engage participants in the activity. This process produced preliminary themes and an understanding of the methodological challenges of doing this kind of research. Ultimately, we hope to stimulate discussion on how to enhance measures of racial discrimination, which in turn may increase accuracy of studies that examine the impact of racism on mental health and wellbeing.

We found that people who were engaged in social media had more encounters with online racial discrimination. However, emotional reactions to online racial discrimination varied, from being mildly bothered to being deeply frustrated. Behaviorally, some of us ignored the content while others took time to react to the content. We found that micro-contexts can intensify or mitigate the impact of online racial discrimination, meaning the impact may depend on the way in which it is presented and framed. Content that is framed with an eye toward social justice (e.g., a comments section where people express their condemnation of racism) appeared less distressing. We also became mindful that the activity of screenshotting can potentially alter algorithms to show more racist content. Further, we realized that the historical timing of the activity may largely determine the amount of online racist content produced and perpetuated at a given time. Overall, given the complexity of the phenomenon, an eclectic use of analytic approaches is critical.

Implications

The screenshotting protocol can be widely applicable for various forms of discrimination, not limited to racial discrimination, including discrimination stemming from homophobia, sexism, and ablism, which all face similar challenges in research. Because studies of racism rely heavily on self-report, improving accuracy and minimizing bias are paramount. A major challenge in studying discrimination is the risk of false positives and false negatives, which depend on how self-report instruments are administered, interpreted, and whether individuals recognize discrimination in their daily lives. As theories of racism and health have become more robust and nuanced, a growing disconnect has emerged between how academic researchers and communities understand racism (Oh et al., 2024). Thus, it is important to qualitatively examine how people make sense of the instruments we develop to measure racial discrimination. In most studies of racial discrimination, researchers rarely witness incidents firsthand. However, studying online spaces through observers’ perspectives directly offers a unique opportunity to observe racial discrimination in its exact form. This allows for a more direct understanding of how individuals perceive and experience online racism, helping refine measures and methods to assess both online and offline racial discrimination more accurately.

Screenshotting may serve multiple purposes by prompting awareness and reflection in participants, providing insight into the perspectives of participants. It can allow researchers to see whether the instruments we administer are being interpreted the way we intended, anchored to concrete and real-world examples that we can scrutinize with our own eyes. Incorporating a ‘screenshot’ component into intensive longitudinal data collection studies (e.g., daily diary or ecological momentary assessment) may also help contextualize the content of screenshots. For instance, the screenshot task cues the participant to reflect on their experiences of online racial discrimination, while quickly and easily documenting an event, and potential associations can be examined with other constructs or health behaviors measured within the same timeframe. The screenshot also serves as the impetus to clarify, complexify, and expand existing measures to accommodate real world experiences. The screenshots aided the research team in visualizing the micro-contexts in which the online racial discrimination submissions occurred, which gave us a much deeper understanding than just the endorsement of a frequency scale or even a written description of how online racial discrimination is understood, recognized, and felt.

Future Directions

Engagement in the screenshotting activity was relatively high given that we as researchers were the ones doing the activity. However, we did not generate a tidal wave of screenshots. When implemented with a sample of participants from the general population, it is possible that engagement may be low, and it is unclear if this would be because online racial discrimination is not occurring or if it is because individuals are not reporting. If online racial discrimination is happening but not being reported, several factors might contribute to this behavior. For instance, the reporting process might be perceived as inconvenient, time-consuming, or stressful. Additionally, individuals may avoid reporting to minimize their emotional distress or to disengage from the experience entirely. Exploring these possibilities is critical to understanding the barriers to reporting and identifying ways to encourage more active participation in the online racism screenshot activity.

Screenshotting can be conducted uniquely in diverse groups, including people of various ages, genders, races/ethnicities, and political orientations. Experiences of online racial discrimination are likely shaped by these intersecting factors, as these demographics influence both patterns of social media usage and exposure to specific types of content (Pew Research Center, 2016). Different groups tend to gravitate toward distinct online platforms, which in turn can shape the forms and frequency of online racial discrimination they encounter (Pew Research Center, 2024). For instance, none of the research team had actively used Facebook, which older age groups are more likely to use, compared to most other platforms (Pew Research Center, 2024). Instead, most of the team’s data were collected on platforms like TikTok or Instagram. Similarly, gender plays a critical role in shaping online experiences. Men, for example, may be more likely to use forums like Reddit or online gaming platforms such as Twitch or Discord, where racism is often expressed in the form of offensive language, slurs, or harassment during live sessions (TaeHyuk Keum & Hearns, 2022). Women may encounter racism differently, such as through targeted sexual harassment, doxxing, or microaggressions in online forums, dating apps, or social media spaces. The intersection of gender and race further compounds these experiences, as women of color face both racist and sexist abuse online (Francisco & Felmlee, 2022; Onuoha et al., 2024; Volpe et al., 2024). Furthermore, generational differences in digital literacy and platform familiarity may affect how users interpret and respond to instances of online racial discrimination.

We realize that much of one’s ability to recognize racist content and one’s reaction to the racist content depended on one’s ideology and worldview (e.g., critical consciousness). We considered the possibility that individuals with more liberal political views might be more likely to report experiences of online racism (Pew Research Center, 2024), where as individuals with more conservative political views may not necessarily see racism as a major problem and may be less likely to endorse any experiences. An important part of the research process is to understand the channels and accounts that people follow, which could provide insight into their political orientation, but also their likelihood of encountering racist online content. Research studies may aim to recruit a wide cross section of people who use different platforms and frequent various websites, including conservative platforms (e.g., Truth Social) and platforms with varying censorship policies (e.g., Telegram). Longitudinal data collection across extended periods would allow for greater refinement of the protocol.

Conclusion

As future research aims to understand the long-term psychological effects of exposure to online racism on marginalized communities, we have the opportunity to enhance this work through screenshots, where we can directly observe racial discrimination in online spaces. Screenshotting may also be useful when devising strategies to reduce the harm of online racial discrimination, such as strategies to reduce the spread of harmful content. By analyzing using screenshots, researchers can better understand how online racism manifests across different groups and develop targeted strategies to create more inclusive, equitable online environments.

Footnotes

ORCID iDs

Hans Oh

Caroline Sweeney

John Bunyi

Vanessa V. Volpe

Brian TaeHyuk Keum

Funding

The author received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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Screenshots to Document Online Racism

Abstract

Keywords

Background

Aims

Method

Justification of Method and Study Design

Recruitment and Participants

Protocol

Procedure

Greater Social Media and Internet Usage Allowed for More Occasions to Experience Online Racism

Reactions to Online Racism Varied Across Situations and Individuals

Micro-Contexts can Intensify or Mitigate the Impact of Online Racism

Using Multiple Platforms can Lead to Repeated Exposures

Historical Timing May Yield Different Results

Analysis Requires an Eclectic Use of Approaches

Ethical Considerations

Logistical Considerations

Discussion

Implications

Future Directions

Conclusion

Footnotes

ORCID iDs

Funding

Declaration of Conflicting Interests

References