It can be hard to know how to engage with others on difficult topics in the current digital landscape. While social media platforms are built for simple exchanges, some subjects โ especially those that involve inaccurate, complex, or contentious information, like vaccines or elections โ require more nuance. Finding the right approach to discuss these issues can be draining, and doubly so if they backfire.
But having these conversations is more important than ever. To help navigate them, the Analysis and Response Toolkit for Trust (ARTT) project, now part of Discourse Labs, has developed a framework of evidence-based, goal-oriented interventions, sourced from researchers in public health, psychology, conflict resolution, media literacy, and other fields.
The goal of the ARTT project is to promote trust-building conversation and empower local communicators. Its findings are especially relevant for those in public health, education, politics, and civil society, but it can be applied by anyone who seeks to keep their local or digital community โ however large or small โ informed with reliable resources.
The ARTT framework is made up of four groups and ten guided response modes, including:
- Understand: Listen, empathize, and take perspective;
- Inform: Correct, co-verify, and encourage healthy inquiry;
- Connect: Share, invite, and de-escalate; and
- Also consider: Do not respond.
The following review provides a summary of these guided responses, as well as what existing research recommends about when and how to apply them in difficult online conversations. It takes a condensed snapshot of the ARTT Catalog, a living, collaborative database of peer-reviewed insights broadly related to the ARTT mission of healthy online communication; this research was compiled by SSRC in support of this project.ย The second version of the ARTT catalog is at this link. The catalog is the basis for theย ARTT Guide, a forthcoming Web-based software assistant to help identify specific recommendations, and theย Curriculum, which seeks to offer practical support for local election officials.
1. Understand: Listen, Empathize, Take Perspective
To understand is a response type that aims to comprehend and consider the other person. This is an acceptance of peoplesโ emotions โ by listening, empathizing, and taking perspective โ even when they are contrary to fact, as a starting point for further discussion.
1.1. Listen
Listening may not seem like much of a response โ which is exactly what makes it an important place to begin. In polarized environments, there can be a tendency to assume what another personโs thoughts, feelings, or concerns are about a particular issue, which may or may not be accurate; similarly, both sides often default to waiting for their turn to respond, thinking of counter-arguments while the other side is still speaking (Itzchakov et al. 2023).
Listening helps reframe the conversation from an argument to โwinโ to an opportunity to engage. Current research emphasizes listening as a critical part of trust-building exchanges (Santoro & Broockman 2022), especially in terms of fostering possibilities for longer term dialogue (Lederach 2003; Bojer et al. 2006; Dorjee & Ting-Toomey 2020) or engagement outside the immediate topic of discussion (Yeomans et al. 2020; Hartman et al. 2022).
โHigh qualityโ listening that is is attentive, understanding, and well-intentioned has demonstrated strengths in terms of conflict resolution (Itzchakov et al. 2017; Itzchakov et al. 2020b; Collins 2022; Itzchakov et al. 2023) and affective polarization (Santoro & Broockman 2022). Because it centers empathy and non-judgement, it reduces speakers’ social anxiety and feelings of defensiveness (Itzchakov et al. 2017). High-quality listening also decreases perceived polarization and attitude extremity by increasing positivity resonance (like “shar[ed] positive affect” and “mutual care and concern”) and self-insight (by “motivat[ing] exploration of both the issue at hand and oneself, including one’s possible biases concerning the topic”) (Itzchakov et al. 2023, 3). It can lead to a domino effect of meaningful exchange โ according to Kluger et al. (2021), respondents who feel listened to are more open to listening in return.
These effects can be maximized in a few ways. Listening training can help listeners feel less anxious and more likely to take perspective over the course of the conversation (Itzchakov 2020a). Journalists or other communicators with a large audience have the ability to improve societal listening by reducing the partisan cues that make people less willing to engage with the other side (Arendt et al. 2023). For highly contentious on- or offline community debates, participatory interventions like horizontal listening โ or active, opening listening between fellow citizens in the public sphere โ can make vertical exchanges (with politicians or corporations) more effective (Hendriks et al. 2019).
These benefits rely on 1) letting the other person know you’re listening, and 2) making them feel genuinely heard. That effect can be difficult to achieve in online spaces, and the stakes of perceived poor listening are high. Portlandโs Restorative Listening Project (RLP) seeks to use dialogue as a strategy for community formation; in one early study, the project backfired when white participants had obvious difficulty listening to Black participantsโ concerns, resulting in worse intergroup relations than before (Drew 2012; for more on safe spaces for expression and listening among marginalized communities, see Mansbridge & Latura (2016)).
But genuine listening can occur, even virtually. โActive listeningโ involves restating or paraphrasing the speaker’s โ or, in this case, user’s โ words to confirm what was heard and what was meant, as a way to convey that sense of attention (Rogers & Farson 1957). Collins (2022) emphasizes the value of these explicit confirmations. For in-person communication, implicit cues like nodding or making eye contact can give the impression of listening without any real cognitive engagement (ibid). This approach has demonstrated effectiveness online: in a study of posts written by Wikipedia editors, Yeomans et al. (2020) explore how such “explicit acknowledgements of understanding” are part of the “receptiveness recipe” that forestalls conflict escalation and reduces personal attacks online (p. 140).
1.2. Empathize
Empathy is the ability to recognize, understand, and share the thoughts and feelings of another โ to identify with someone else on an emotional level. Existing research describes the affective (i.e., the ability to experience the emotions of others, as described above) and cognitive (i.e., the ability to adopt the perspectives of others) components of empathy. For the sake of clarity, this framework separates the latter into its own response mode (see 1.3. (Take Perspective), below; for further disambiguation of “empathy” as a concept, see Klimecki (2019) and Batson & Ahmad (2009)).
Empathizing is a useful strategy for exchanges 1) about emotionally-driven conflict, 2) where the goal is to improve the relationship between involved parties. It often applies to topics like vaccine hesitancy and medical mistrust (Gesser-Edelsburg et al. 2018; Gagneur 2020), partisan affective polarization (Saveski et al. 2021; Garrett et al. 2014; Wojcieszak & Warner 2020), hate speech (Hangartner et al. 2021), intergroup contact (Johnston & Glasford 2018), and attitudes towards immigration and racial or ethnic out-groups (Klimecki et al. 2020; Sirin et al. 2016), which often involve feelings of fear, anger, anxiety, or resentment.
Empathy can be more productive than trying to push through fact or reason alone; in the case of online hate speech, Hangartner et al. (2021) find that empathy-based counterspeech messages increase the retrospective deletion of xenophobic posts and reduce the prospective creation of new posts, even after a four-week follow-up period. By comparison, treatments based on warning of consequences had no consistent effect. Similarly, Gesser-Edelsburg et al. (2018) and Gagneur (2020) show how engaging with emotions like fear and concern for loved ones while addressing misinformation is more effective than fact-based correction alone.
There are important limitations to note. Just as much as empathy can โmotivate prosocial behavior,โ it can also โmotivate cruelty and aggression,โ or โlead to burnout and exhaustionโ by taking an emotional toll (Bloom 2017). Negative intergroup interactions may further โexacerbateโฆ hostility by enhancing anxiety and reducing empathyโ (Wojcieszak & Warner 2020, 789). For recommendations on addressing antisocial reactions to empathy, see 3.1 (De-Escalate), 3.2 (Invite Sociability), and 4.0 (Also Consider/Do Not Respond).
1.3. Take Perspective
Empathize and Take Perspective are related strategies, but they differ in terms of focus. As noted above, while empathizing involves sharing and understanding others’ emotions, perspective-taking helps identify their intentions, needs, reactions, and behaviors. It is the act of putting yourself in someone else’s shoes and trying to view the situation the way they do, even if you do not agree with them.
This sense of perspective has a wealth of benefits for in-group/out-group dynamics and democratic societies. It reduces exclusionary attitudes (Kalla & Broockman 2021), negative stereotypes and biases (Galinsky & Moskowitz 2000), and intergroup anxiety (Aberson & Haag 2007), while increasing positive attitudes and stereotypes, depolarization, and the likelihood of positive future interactions (ibid; Marchal 2022). Adida et al. (2018) show that a short, interactive perspective-taking exercise โ asking subjects to imagine themselves in the shoes of a refugee โ increases support for refugees in the United States on a bipartisan level. These exercises can also help maintain a healthy deliberative democracy: Muradova (2021) argues that โseeing the other sideโ results in deeper, more reflective citizen deliberations.
Importantly, this response mode only works if it is well-informed (Eyal et al. Epley 2018). Simply imagining someoneโs perspective may not be accurate. โPerspective-getting,โ or perspective-taking combined with 1) good interpersonal communication and 2) listening to how the other person describes their situation, is needed to achieve these positive benefits (ibid). Longmire & Harrison (2018) further emphasize that whether this approach is appropriate depends on the goal and underlying dynamics of the exchange. Where empathy-based interventions have a โconsistently stronger impact than perspective-taking on strengthening social bonds,โ the latter โallows actors to attain resource-focused goals in strategic interactionsโ (ibid, 908). That understanding of social vs. material concerns can help avoid making the situation worse: in the case of Klimecki et al. Sander (2020), perspective-taking exercises made anti-immigration opponents less willing to engage with their pro-immigration counterparts, due to how it increased perceived resource competition (see Johnston & Glasford (2018), Wojcieszak & Warner (2020), and Igartua et al. (2019) for situational drivers of intergroup contact and realistic conflict theory).
2. Inform: Correct, Co-Verify, Encourage Healthy Inquiry
As a response group, informing focuses on evaluating the quality of information. It seeks to provide or explain complex information, complicated knowledge, empirical information, evidence-based knowledge/information, and trustworthy competent knowledge โ on one’s own, or in partnership with others. This group encompasses modes of correction, co-verification, and encouraging healthy inquiry.
2.1. Correct
To correct someone is to show or tell them what is wrong, and instead explain what is accurate. The goal of this response mode can vary: it might aim to equip the speaker with skills to identify misinformation, or provide facts about important issues like vaccination or climate change. It can also make sure that others listening in on the conversation have access to accurate information.
This response mode can be especially difficult to navigate. People tend to โreject information corrections that contradict their attitudes [and] share content that is consistent with their own narratives,โ without verifying its accuracy (Gesser-Edelsburg et al. 2018). Questions of who, when, where, how, and what are determining factors of what makes effective โ or ineffective โ correction.
Existing research suggests that anyone can correct misinformation as long as they either:
- Are perceived as a credible expert on the subject (i.e., healthcare providers or public health organizations for medical information) (Cook et al. 2017; Vraga & Bode 2017), or
- Cite sources that are perceived as credible. For example, Seo et al. (2022) determine that individuals and organizations alike can effectively correct health misinformation โas long as the correction contains a reliable sourceโ (896).
This literature supports a โwhen you see something, say somethingโ approach to non-expert correction.
Tully et al. (2020) find that social media users can effectively push back against and halt the spread of misinformation online, but they are unlikely to do so โ preferring not to engage, and therefore allowing false information to continue to spread. Notably, the chances of user-initiated correction were increased by the presence of other corrections that were civil in tone (ibid). Like listening (1.1), one well-done correction can trigger a domino effect of accurate information.
Corrections should be able to account for why people believe false information in the first place (see 1.2 (Empathize) and 1.3 (Take Perspective), above). Where framing false claims as โmythsโ can come across as dismissive (and result in โbackfire effectโ), Gesser-Edelsburg et al. (2018) point to corrections based on โintegrative decision-making,โ transparency, and empathy. Bautista et al. (2021) illustrate a careful multi-step approach used by healthcare professionals: false information is identified through internal and external authentication, and corrected by preparation (broken down into โreflect,โ โreveal,โ โrelate,โ and โrespectโ) and dissemination (public and private priming and rebuttal).
This distinction between public and private is tricky, especially online. As noted above (Tully et al. 2020), public interventions encourage others to correct misinformation, which can slow or even stop the resharing of false content. But they can also put the receiver on the defensive. Mosleh et al. (2021) show how publicly replying with fact-checked reports increases the toxicity of language used on social media. Such cases may require more one-on-one communication, like through direct messaging.
The timing of corrections โ before (also known as prebunking, inoculation, or pre-emptive correction (Cook et al. 2017; Zerback et al. 2020)), during (Lee et al. 2023), or after exposure to false information โ is the subject of ongoing research. Pre-emptive and mid-exposure corrections are key to stopping the spread of false narratives, while some experimental research suggests that debunking has comparatively higher longevity in terms of remembering and retaining corrected information (Brashier et al. 2021). For social media platforms, pre- and mid-exposure corrections often take the form of fact-checking labels. For individual communicators, that may look more like amplifying accurate information, intervening when they see false narratives being shared, or ensuring access to reliable sources in their communities (see 2.2 (Co-Verify) and 2.3 (Encourage Healthy Inquiry), below).
While we often think about corrections in terms of topics or objects (i.e., vaccines or climate change), corrections about people can be especially important for a healthy, peaceful democratic society. The concept of โmeta-perceptionsโ refers to what you believe about how others view you.
In a divided political context, people tend to have negative and inaccurate partisan meta-perceptions โ because they are more likely to believe believe that members of the opposing political party views them with hostility, dehumanization, and support violence against them, they feel more justified holding the same attitudes in return (Lees & Cikara 2020; Mernyk et al. 2022; Landry et al. 2022). The resulting cycle facilitates harm and increases support for undemocratic practices. Correcting these metaperceptions by informing people what out-groups actually think of them (i.e., with survey data) is essential to slowing or reversing this cycle (ibid). Druckman (2023) and Druckman et al. (2023) examine how these out-partisan corrections work for ordinary citizens and legislators in real-world settings, especially in the presence of competing information.
2.2. Co-Verify
Co-verification involves fact-checking and evaluating sources with the help of a relevant expert โ or, as an actionable step, when a trusted community member offers to verify a piece of information with another person (Murthy 2021). It acts as the โphone a friendโ of response modes; where correction is about sorting the accurate from the inaccurate, co-verification is the process of assessing accuracy, with the benefit of trust, credibility, and interpersonal dynamics. This combination of fact-checking with trusted social connections increases the acceptance of corrected information (Walter et al. 2020), even across different political ideologies (van der Linden et al. 2018).
In practice, co-verification builds onto existing โmedia, science, digital, data, and health literacyโ programs (Murthy 2021). It might involve a demonstration of โclick restraintโ (the need to look beyond the first results suggested by a search engine (Panizza et al. 2022)) as well as โlateral readingโ (or โleaving the original content to investigate other information sourcesโ โ for example, opening a new tab to double-check the claims on a social media post (Axelsson et al. 2021)). Co-verification has been proven to be an effective approach to in-school digital literacy curricula for middle school to college-aged students. Those who learn literacy tools from (or with) a teacher, professor, or their peers have an improved ability to assess credible sources and detect bias, and show greater nuance and critical judgement when interacting with media (Kohnen et al. 2020; McGrew 2020; Axelsson et al. 2021; Breakstone et al. 2021; Brodsky et al. 2022).
2.3. Encourage Healthy Inquiry
This response mode is about inspiring and enabling critical thinking. To encourage healthy inquiry is to help others know how to question the information they are reading โ for example, โWhat do other sources say?โ or โWhat evidence does it present?โ (National Academies of Sciences, Engineering, and Medicine 2017; Murthy 2021). โHealthyโ inquiry is an important keyword here because the goal is not to encourage skepticism in all information. Rather, it focuses on being able to critically evaluate information by not immediately believing new claims.
Encouraging healthy inquiry can involve some of the same information literacy interventions as co-verification (i.e., lateral reading; see Wineburg & McGrew 2017, Brodsky et al. 2021), with an important distinction. Instead of assessing information with someone, this mode seeks to provide the toolkit, opportunity, and motivation to make an assessment on their own. A โhealthy inquiryโ-based approach to lateral reading would advise the audience to consider context clues (i.e., information about the organization or individual who posted it) in addition to direct in-text claims (Brodsky et al. 2022).
Current research suggests that such active, self-led engagement โ finding and evaluating information on one’s own โ can be more effective than having it provided to you (see 2.1 (Correct)). Banerjee & Greene (2006) show that students tasked with creating their own anti-smoking ads, which involves locating and assessing the information to include, results in greater behavioral and attitudinal changes than students who analyze existing ads.
Encouragement can come from organizations or individuals, and it can take place over the short- or long-term. Case-by-case โnudgesโ that remind users to verify the accuracy and credibility of online content have been shown to improve headline truth discernment and reduce the sharing of misinformation (Pennycook et al. 2020, Jahanbakhsh et al. 2021), and can include accuracy prompts (Pennycook & Rand 2022), and warning labels about the credibility rating (Aslett et al. 2022) or political affiliation of the source (see Nassetta & Gross (2020) for how these labels apply to content posted by state-controlled media on digital video platforms). Newsroom-style games can also encourage inquiry by helping users interrogate information sources and apply those skills going forward (Vicol 2020). Long-term intervention can include a variety of digital, informational, and media education training programs (Bergsma & Carney 2008; Jones-Jang et al. 2019; Seo et al. 2019). Jeong et al. (2012) note that multi-session training programs are more effective at guiding healthy inquiry over time as compared to single-session programs. These programs can also be tailored to the needs and concerns of different populations see Seo et al. (2019) for digital literacy training programs in older Black communities, and Kenzig & Mumford (2022) for targeted reminders encouraging skepticism among the vaccine-hesitant).
This response mode is an especially broad part of the ARTT framework because it involves skills that can โ and should โ apply beyond any one topic. McGrew & Breakstone (2022) make the case that โgiven the current threat posed by toxic digital contentโฆ evaluat[ing] online sources cannot be relegated to a single subject area,โ and that for students, must be directly embedded โacross the curricula.โ As part of their study, ninth grade biology and world geography teachers wove principles of civic online reasoning and digital literacy into existing lesson plans. Students demonstrated a significant increase in their ability to evaluate online content.
Encouraging healthy inquiry can also be a way to ease the mental burden on those charged with correcting misinformation. Over the course of the COVID-19 pandemic, local health departments (LHD) in the midwestern United States often faced conflict, public rebuttals, and harassment from trolls when they attempted to directly intervene in false claims on Facebook (Ittefaq 2023). Less direct engagement โ like giving people the tools to interrogate information through FAQs โ reduced the opportunity for conflict while still promoting accurate information spread (ibid).
3. Connect: De-Escalate, Invite Sociability, Share
This response group involves tactfully joining a conversation with the goal of reducing tensions and strengthening (or restoring) a sense of human connection to difficult exchanges. It includes guided responses for de-escalation, inviting sociability, and sharing personal stories or narratives.
3.1. De-Escalate
De-escalation focuses on reducing hostilities between individuals or groups. It can be especially useful for getting a conversation back to a place where it can be productive, or for removing barriers so that conversation can begin.
Common de-escalation strategies include appeals to common values (also known as โmoral suasionโ) (Munger 2020), a superordinate identity (i.e., โAmericans, not partisansโ) (quoted in Levendusky 2018; see also Voelkel et al. 2023), or common interests and goals (Dorjee & Ting-Toomey 2020; Rajadesingan et al. 2021). De-escalation may also include humanizing a conflict through mutual respect (see 3.2 – Invite Sociability), listening (see 1.1 – Listen), empathizing (see 1.2 – Empathize), positive intergroup contact (Wojcieszak & Warner 2020; Voelkel et al. 2023), and/or the sharing of personal narratives (see 3.3 – Share). A detailed overview of dialogue-based de-escalation strategies from intergroup conflict research can be found in Dorjee & Ting-Toomey (2020). Key recommendations point to approaches like โmiddle-way,โ “transcendent,โ โidentity-sensitive,โ or โpeace-makingโ dialogue, which involve principles of โmutually beneficial reconciliation,โ an open-minded or judgement-free exchange of ideas, the rejection of a โbinary win-lose stance,โ and an awareness of sociocultural differences or power imbalances (ibid).
If an interaction is likely to result in conflict, Yeomans et al. (2020) suggest a preventative approach: indicating oneโs interest and engagement in hearing what the other person has to say at the beginning of a conversation (what the authors refer to as โearly conversational receptivenessโ) can help keep the rest of the conversation civil, and prevent escalation before it happens. This โearly de-escalationโ is especially useful for intractable conflicts, which lock people and communities into โdestructive spirals of enmityโ (Kugler & Coleman 2020). Intractability is often the result of clashes over โimportant moral differencesโ (ibid; see also Dorjee & Ting-Toomey 2020) like โ[the allocation of] critical resources, identity, meaning, justice, [or] powerโ (Coleman 2003). These kinds of disputes go beyond an โagree to disagreeโ mindset; left to fester, they may lead to increased support for partisan violence and undemocratic practices (Voelkel et al. 2023; Druckman 2023).
In a similar vein, one’s choice of de-escalation strategy must be informed by why tensions escalated in the first place (Dorjee & Ting-Toomey 2020). Existing research shows that โ while fact checks help counter misinformation โ they fail to reduce affective polarization, which is driven more by emotion than by fact (Druckman 2023; Boukes & Hameleers 2023). But it also shows how adaptive de-escalation can fill that gap: Munger (2020) finds that messages that appeal to Republican or Democratic values are more effective at reducing partisan incivility on Twitter than messages with no moral content. Similarly, Huddy & Yair (2021) demonstrate that warm or friendly behavior interactions between leaders eased affective polarization, whereas policy compromise did not.
Adaptive de-escalation is critical for tailoring interventions to online vs. offline spaces. In their analysis of cross-partisan interaction on Reddit, Rajadesingan et al. (2021) discuss how, in offline settings, โknowing more about out-partisan interlocutors help[s] manage disagreementsโ by adding an element of context and empathy. The same can backfire in online spaces, where personal information (i.e., other subreddits a user participates in or past comments they have made) can raise โconcerns around privacy and misuse of that information for personal attacks[,] especially among women and minority groupsโ (ibid). The Redditors in their study instead preferred โestablishing common ground, complimenting, and remaining dispassionate in their interactionsโ as a way to de-escalate cross-partisan conversations (ibid; for further analysis of digital de-escalation, see Hangartner et al. (2021) on the use of empathy-based counterspeech to reduce racist hate speech on social media, and Munger (2020), discussed above).
3.2. Invite Sociability
Reminders of the ways we’re connected to one another can have a powerful impact on communication. Inviting sociability โ or an emphasis of shared norms and values โ acts as an opportunity to reflect on the bonds that tie us together, which increases trust, civility, and open-mindedness.
There are two broad conversational approaches to invite sociability: first, by appeals to โwho we areโ in the sense of a common, superordinate identity; and second, by appeals to โhow we behave,โ through reminders of prosocial behavioral norms and expectations. Some of these strategies overlap with the research examined in the above response mode (see 3.1. (De-Escalate)).
People often use identity as a shortcut to know who to trust and how to communicate. This is especially true for polarized, fast-paced, or overloaded digital information environments, where โtrust, not knowledgeโ may be required to overcome issues like COVID-19 vaccine hesitancy (Ledford et al. 2022; see Seo et al. (2022), Magee (2022), and Heiman et al. (2022) for further analysis of identity-based approaches to vaccine hesitancy in migrant minority communities). In an analysis of Latino and Latina communities on Facebook, Rivera et al. (2022) find that usersโ personal relationship with the author of a post leads to greater engagement, information-seeking, discussing, discussing content with others, and changing health behaviors than simple exposure to evidence-based health communication.
But identity is rarely fixed, and existing research shows the value in purposefully shifting who we perceive as being โlike us.โ Greenaway et al. (2015) find that people are more likely to follow instructions and have better communication with perceived in-group members than with out-group members. That difference disappears when participants are made aware of a common identity โ when the boundaries of group identity were redrawn to include all participants. Further research shows that this framing can more successfully improve intergroup relations than contact and interaction (Martinez-Ebers et al. 2021). This sense of โweโ can even bridge deeply entrenched, partisan divides; drawing on large-scale survey and experimental data, Levendusky (2023) examines how priming commonalities like shared identities outside of politics, cross-party friendships, and common issue positions lessens animosity between Republicans and Democrats.
Prosocial “nudges,” or reminders of behavioral norms and socially-defined best practices, are another important form of inviting sociability (Goldstein et al. 2008; Andi & Akesson 2021; Pennycook et al. 2020). In an experiment of hotel guests, Goldstein et al. (2008) find that people are more likely to change their behavior when given reminders that “the majority of [hotel] guests reuse their towels” compared to โcommon goodโ-based reminders about environmental protection or conserving water. These cues are most effective when the norms being described closely match the audience’s environment (in the case of Goldstein et al. 2008, “the majority of guests reuse their towels” is most likely to change behavior in a hotel, not necessarily in someone’s home), or when they are given by a perceived in-group member (Gรณmez et al. 2013; Munger 2017). Munger (2017) applies this approach to the context of racist online harassment: white male Twitter users lessened their use of anti-Black slurs when sanctioned by an account that appeared to be a high-follower white male.
3.3. Share
To share is to bring something personal into a discussion โ specifically, sharing one’s own story can be an important way that people explain their thought process or personal experience of navigating a difficult decision.
The strength of this response mode is its ability to humanize, which is an important counterbalance to the โfacelessโ anonymizing effect of social media. Narratives that are based on personal experience, and especially those that involve a sense of vulnerability, can bridge ideological divides, encourage empathy, and make people appear more trustworthy (Hagmann et al. 2020; Bojer et al. 2006). In data-driven information environments, these stories are seen as more authentic, and therefore more durably persuasive, than non-narrative messages (ibid; Fiske & Dupree 2014; Oschatz & Marker 2020). Because stories inherently lead to some degree of identity negotiation and perspective-taking (see 1.3, Take Perspective), Black (2008a, 2008b) argues that storytelling can aid deliberative democracy.
Recent research points to stories as a way of overcoming partisan affective polarization (Voelkel et al. 2023), delivering health or science information (Haigh & Hardy 2011; Massey et al. 2020; Academies of Sciences, Engineering, and Medicine 2017; Le et al. 2023), and reducing bias between racial or cultural outgroups (Gaertner & Dovidio 2000; Wojcieszak & Kim 2016). While evidence suggests at least some impact from both first- and third-person narratives, Kim & Lim (2022) find that first-person storytelling is comparatively more persuasive because of the way it fosters a sense of โdirect interaction with a narrative character.โ This dynamic is supported by Igartua et al. (2019), who find that first-person narratives featuring stigmatized immigrants can work as a sort of โimagined contact,โ improving outgroup attitudes and leading to actual intergroup contact among prejudiced individuals. Again, such โimagined contactโ is uniquely important for digital spaces, where it can be all-too-easy to forget that real people are on the receiving end of unkind or hateful messages.
As noted above, storytelling tends to be more persuasive than statistics alone, especially for emotionally-driven issue areas (Wojcieszak & Kim 2016; Gaertner & Dovidio 2000). Yet this approach may be less โand/or,โ and more โbothโ: Shelby & Ernst (2013) explore how personal narratives can effectively supplement statistics to deliver vaccine-based health information.
4. Also consider: Do Not Respond
As a final note, it’s important to remember that sometimes, the best response might be none at all. Blocking and reporting a user is appropriate in cases where there is a clear violation of platform rules, or when continuing the conversation poses any risk of danger to yourself or others. Refusing to engage is also appropriate if a user or message is in bad faith, created by bots, or harmful to your mental health โ research indicates that responding to trolls or hostile discussions can exacerbate negative interactions and lead to psychological distress (Buckels et al. 2014; Adams et al. 2006).
While this response mode may feel unsatisfying (or not enough of a โrealโ response), it can have important benefits.
First, refusing to respond can still lead to a net decrease in online incivility, the amplification of harmful content, and the spread of false information. For social media trolls driven by antisocial personality traits or a desire for negative social awards, attention is the point. Any response might only encourage more trolling (Buckels et al. 2014; Craker & March 2016). Constant engagement can also lead to โsocial media fatigue,โ a phenomenon linked to increased misinformation-sharing (Islam et al. 2020).
Second, โdeliberate ignoranceโ may not be bliss (Hertwig & Engel 2016), but it is at least a useful strategy that allows individuals to maintain their well-being. This can be critical for social workers, care professionals, or community leaders, who are at high risk of โcompassion fatigueโ (Adams et al. 2006). In a broader sense, โsocial media fatigueโ can result in discontinued use of social media (Ou et al. 2023) โ and, as a result, fewer people to correct, co-verify, or enact any of the above response modes to promote a healthy and accurate digital information ecosystem.
Conclusion
In 2021, the Office of the U.S. Surgeon General urged that โtogether, we have the power to build a healthier information environmentโฆ. But there is much to be done, and each of us has a role to playโ (Murthy 2021, 6).
That guidance has only grown more relevant. As major tech companies scale back their content moderation and fact-checking policies for the U.S. market, the responsibility of ensuring accurate information spread falls increasingly to people, not platforms. Communities โ and especially educators, journalists, public health officials, mutual aid organizers, and civil society leaders โ will decide the next chapter of what our digital spaces look like, and how we communicate within them.
Further, while social media is rightly blamed for many of the fractured, toxic elements of our social and political landscape, it also provides the opportunity for repair. The ARTT framework is designed to help public communicators seize that opportunity. Each of its guided responses are grounded in an empathetic understanding of where people are coming from and evidence-based solutions of how to ideally engage. There is no easy reset button for the problems of the current digital environment. But โ with the right tools โ healthier, better-informed online communities are possible, one conversation at a time.
Acknowledgements
The Analysis and Response Toolkit for Trust (ARTT) is part of Discourse Labs. a project of Hacks/Hackers and the Paul G. Allen School of Computer Science & Engineering at the University of Washington. Connie Moon Sehat (Hacks/Hackers Researcher at Large) is the Principal Investigator (PI) for the ARTT project. Amy X. Zhang (Assistant Professor at University of Washingtonโs Allen School) and Franziska Roesner (Associate Professor, Allen School) serve as co-Principal Investigators (co-PIs).
More about the ARTT project can be found on its website at artt.cs.washington.edu.
This review is written by Kimberly Tower (MediaWell), based on a prior review by Kristin M. Miller (ARTT Research Consultant)โs work with the ARTT Catalog and literature suggestions from external scholars. The prior review was edited by Connie Moon Sehat, Molly Laas (Program Director, Social Science Research Council), and Endalkachew Chala (ARTT Researcher).
This work was supported by the National Science Foundationโs Convergence Accelerator program under Award No. 49100421C0037.
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