Abstract

Building on previous descriptive research, this study investigated the impact of three microstream attributes—scriptedness, production value, and stagedness—on the perceived authenticity and enjoyment of viewing microstreaming gameplay videos. Through an experimental design, N = 403 participants viewed bespoke microstreams and were asked about their perceptions of authenticity and enjoyment. Perceptions of scriptedness, production value, and stagedness served as independent variables in parallel mediation analyses across five authenticity factors (sincerity, truthfulness, visibility, expertise, and uniqueness), with enjoyment as the outcome. While the manipulations of microstream attributes did not notably alter content perceptions, variance in perceptions directly and indirectly impacts enjoyment, mediated by dimensions of authenticity. Content that appeared unscripted and unstaged was linked to enhanced sincerity and overall enjoyment, whereas content viewed as scripted and produced was associated with greater expertise and visibility, leading to increased enjoyment. These insights extend our understanding of perceived authenticity and its nuanced impact on viewer enjoyment for streaming content, offering implications for both content creators and the broader landscape of user-generated content.

Keywords: microstreamers, game streaming, authenticity, experimental design, enjoyment

Disclosures: The Authors have no funding information to report or conflict of interest to disclose.

Data Availability: Data and stimuli for this project are available online at https:// osf.io/2rc4h/. Data from this project have not been used for any prior research.

Open Science Disclosures: The data are available at https://osf.io/2rc4h/. The experimental materials are available at https://osf.io/2rc4h/.

Open Access License: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND). This license permits copying and redistributing the work in any medium or format for noncommercial use provided the original authors and source are credited and a link to the license is included in attribution. No derivative works are permitted under this license.

Correspondence concerning this article should be addressed to Nicholas David Bowman, S.I. Newhouse School of Public Communications, Syracuse University, 215 University Place, Syracuse, NY 13244, United States. Email: [email protected]

Imagine a college student in their room playing Valorant while streaming live on Twitch, surrounded by the chaos of a typical college dorm—a small living quarters where their personal life is on display, and interlopers linger in the background. The player is mostly silent and focused on gameplay, offering only occasional notes as the game unfolds. The viewer count stands at zero, but the stream goes on. One way to understand this scenario is through the lens of microstreaming. Such content usually features hobbyist or leisure streams of people sharing their interests and passions with the world (A. Phelps, Bowman, et al., 2022), often driven by nonfinancial motives and with few to no regular followers (Consalvo et al., 2020).

Of course, game streaming has become a dynamic and influential phenomenon, attracting millions of viewers globally and transforming video game engagement. Since 2020, Twitch has consistently recorded over 2 million concurrent viewers across a vast array of channels, with approximately 7 million streamers contributing to this vibrant ecosystem (TwitchTracker, n.d.). Existing scholarship has extensively examined the motivations behind viewing game streams (Kim & Kim, 2023), streamers’ monetization strategies (Houssard et al., 2023), critiques of labor structures (Woodcock & Johnson, 2019), and the issues within toxic streaming cultures (Groen, 2020). Research has also delved into the relationship between streaming, spectatorship, and esports (Taylor, 2018).

Meanwhile, changes in streaming culture—driven by a shift in cultural norms around content sharing (Jenkins, 2009, 2018; Vorderer et al., 2017) and the seamless integration of streaming technologies into gaming platforms (Church & Thambusamy, 2022)—have led to an increase in the number of microstreamers such as those at the start of our introduction. At least one reason why microstreamers could be especially compelling is that they are perceived as authentically engaging in game content. Prior descriptive research has suggested that unique features of microstreams, such as their seemingly unscripted nature, lower production quality, and sharing of unstaged and uncurated environments (Consalvo et al., 2020; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022), contribute to making the content more natural, approachable, and thus authentic. Our goal is to elucidate the attributes that contribute to authenticity in microstreams and to critically assess how authenticity influences the enjoyment of the content—a relevant concern given the entertainment context of gaming and streaming. This research employs an experimental design to manipulate the identified characteristics within simulated microstreaming content, aiming to gauge their impact on perceived authenticity and the enjoyment of the viewers.

From Streaming to Microstreaming

Microstreaming, as defined by A. M. Phelps et al. (2021), involves live streaming to a relatively small audience by individuals who do not rely on streaming as their primary source of income. While microstreamers can aspire to turn streaming into a full-time career, they find fulfillment in treating it as a dedicated hobby, persisting even with a small audience with few to no consistent followers or subscribers (Consalvo et al., 2020). Microstreamers exhibit distinct characteristics useful in distinguishing them from professional streams. For example, their streams can often appear as more impromptu without prior rehearsal or scheduling, often including unintended content such as disruptions from others (such as family and roommates), gameplay failures and breakdowns, and unregulated emotional reactions (Consalvo et al., 2020). Their streaming environment can be marked by unstaged and cluttered space, and they often make use of no- or low-cost production equipment and software (Consalvo et al., 2020; A. Phelps, Bowman, et al., 2022). However, these features are likely the very elements of microstreaming that contribute to a perceived authenticity and a sense of intimacy between microstreamers and their audiences.

Moreover, microstreaming can also be understood through the lens of participatory culture, characterized by low barriers to artistic expression, active engagement, informal mentorship, and involves fans creating alternative interpretations through unauthorized cultural productions (Jenkins, 2009, 2018). Game streaming, once considered secondary to gaming, is now recognized as a robust and legitimate participatory culture. It offers technological, financial, and social affordances, aligning with participatory culture’s key features (Sjöblom et al., 2019). This dynamic not only nurtures gaming communities but also redefines the bond between streamers and fans, with streaming content itself becoming a creative production for the audiences (Brown & Moberly, 2020).

To some extent, microstreamers could be seen as an antithesis to the rise of social and digital media influencers or professional streamers as highlighted by Khamis et al. (2017). Consalvo et al. (2020) noted that “many [were] happy with the current state of their channels, viewers and practices, and are not striving to ‘make it big on Twitch’” (para. 6). Rather than being driven by the allure of wealth and fame that follows from self-branding and engaging in streaming as a means to monetized streaming (A. M. Phelps et al., 2021), microstreamers seem more driven toward the affordances associated with social interaction (Evans et al., 2017) and the relationships that form as a result (Leith, 2021), as well as transforming their gameplay into a creative expression (Taylor, 2018). Indeed, common factors influencing streaming participation broadly include social integration, personal integration, and a need for affection (Li et al., 2020). Similar to professionalized streamers, some microstreamers actively engage with their audiences (Consalvo et al., 2020; A. Phelps & Consalvo, 2020). In some cases, microstreaming is also motivated by self-exploration (Chan & Gray, 2020).

On the audience side, motivations for watching game-streaming videos vary, including cognitive engagement, emotional connection, personal integration, social integration, and stress relief (Sjöblom & Hamari, 2017). In particular, social integrative motivations—which encompass the relationship between the audience and the streamer, values alignment with the audience group, and the perceived connection between the streamer and the audience—are key predictors of subscription behavior (Li et al., 2020). For microstreamers, the community formed around the gaming site provides mutual support and interaction (Speed et al., 2023). At least part of this perception is the suggestion that microstreamers—because they are more intrinsically motivated (compared to extrinsic financial motivations)—could be perceived as more authentic, which contributes to a sense of intimacy and trustworthiness (A. Phelps, Consalvo, et al., 2022). This question of perceived authenticity in microstreams is the core focus of the present study.

Perceived Authenticity

Perceptions of authenticity hold particular significance in online communication, especially within computer-mediated communication, where interactions can become hyperpersonal, allowing for strategic (and potentially inauthentic) self-presentation (Walther, 1996, 2007). This emphasis on authenticity and honesty becomes paramount when influencers engage in strategic communication and marketing on behalf of numerous sponsors for financial gain (Lee & Eastin, 2021). Goffman (1959) contended that authenticity involves the candid portrayal of one’s unvarnished personality, behaviors, and beliefs, typically reserved for private or trusted interactions. This involves disclosing inner experiences, interests, challenges, and vulnerabilities and engaging in other behaviors typically reserved for close relational others (Lee & Eastin, 2021; Trilling, 2009).

In the context of social media influencers, Lee and Eastin (2021) argued that perceived authenticity was related to feeling as if the online persona was relatable and accessible rather than a manufactured media image created by industry professionals (or individuals with expertise in professional online self-presentation). Their five-factor model of perceived authenticity encompasses various factors, including sincerity (portraying an “unedited persona”; Marwick & boyd, 2011, p. 149), truthfulness (sharing content driven by intrinsic motivation or as an extension of one’s interests; Audrezet et al., 2020), visibility (being open and transparent, “putting themselves out there”; Lee & Eastin, 2021), expertise (demonstrating competence in a particular domain, validating one’s influencer status among the audience; Moulard et al., 2014), and uniqueness (being perceived as a creator of novel and original content rather than a copy or imitation of others; Grayson & Martinec, 2004).

Streamers, just like influencers, are expected to maintain some level of authenticity in their content (and indeed have been framed as influencers; Woodcock & Johnson, 2021). As they utilize various digital platforms, they engage with audiences ranging from highly intimate connections to more mass-produced, less personalized content (O’Sullivan & Carr, 2018; see also Evans et al., 2017, for a comprehensive discussion of platform features and social affordances). Moreover, authenticity poses a distinct challenge for professional game streamers, who might be seen as trying to sell games rather than genuinely enjoying them, which can lead to perceptions of inauthenticity (Woodcock and Johnson, 2019). The significance of social integrative motivations among viewers, as highlighted by Sjöblom and Hamari (2017) and Wohn et al. (2018), additionally underscores the high expectations of authenticity held by fans of various streamers.

The more amateur and hobbyist nature of microstreaming could be perceived as increasingly authentic in some of the dimensions noted by Lee and Eastin (2021). For example, game streamer Master Loti (https://www.twitch.tv/master_loti) discussed how their stream changed when shifting from a microstream to an affiliate (re: monetized) stream. Monetization (and, to some extent, the shift from microstreaming to professional streaming) brought with it extrinsic pressure to stream (paraphrasing) “primarily to create content, rather than out of a genuine enjoyment of the game” (personal communication, May 12, 2023; January 14, 2024)—this could be highly relevant to perceptions of sincerity and truthfulness. The rush to “create content” also led to feelings that the stream was becoming less unique, as popular streams tend to cluster around a small set of highly popular video games (e.g., Deng et al., 2015); by contrast, Master Loti’s earlier (micro)streams were appreciated by audiences because they uniquely showcased expertise with mobile games. Loti noted that audiences did not seem to engage the same way, suggesting potentially that the professionalized stream was losing many of the elements of perceived authenticity that made it initially enjoyable (for the streamer and the audience).

Factors Influencing Perceived Authenticity in Microstreaming

In descriptive research, Consalvo et al. (2020) identified various observable elements that likely contribute to the perceived authenticity of microstreams, categorized into intentional and unintentional. Intentional performances encompass sharing personal life details, adhering to a regular streaming schedule, and engaging with their community both on and off-stream. Unintentional performances involve moments when streamers become overwhelmed by emotions, experience gameplay failures, break the fourth wall, encounter technical difficulties, or address issues related to abuse and harassment. A. Phelps, Consalvo, et al. (2022) further described these traits of microstreamers by noting their ability to blur the lines between the frontstage and backstage aspects of their efforts (see Goffman, 1959). In doing so, microstreamers effectively involve their audience in the messy, unscripted aspects of life. Subsequent studies (A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022) proposed three key elements commonly associated with the physical environment of microstreamers: scriptedness, production value, and staging. Although we do not challenge that these are relevant elements for live streaming broadly (games and otherwise), below we define and highlight their unique importance in microstreaming.

The first element is the relative unscriptedness that microstreams engage, which tends to result in mostly extemporaneous dialogue and situated responses on behalf of the streamers. This reflects the natural and unfiltered way in which microstreamers engage with their content, often deviating from a structured host-like role that explains every step of their in-game actions to an audience. Instead, they stream as a byproduct of interest in a given game, focusing on sharing their experience, which is sometimes manifested through the mere sharing of their game screen. By contrast, professional streams have a comparatively more scripted (or at least, orchestrated) feel to them, akin to reality television shows in which dialogue and scenarios are left open for live action but are contrived with a keen eye toward entertaining audiences (see Hall, 2006, 2009; Nabi et al., 2003). The unscripted nature of microstreams also involves unplanned interruptions, such as family and friends walking into the room during the livestream, somewhat reflecting their often unplanned and impromptu nature (A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022).

The second element revolves around comparatively low production values. Microstreamers typically adopt a “pick up and play” style of content and lack the resources or technical expertise to emulate higher production standards—for example, microstreamers typically do not use gaming headsets or backlighting and often do not include elements such as graphical overlays in their streams (as observed in prior descriptive studies; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022).

Finally, the third element found in prior observational work was streaming from a comparatively unstaged environment. Microstreams were often broadcast from otherwise private spaces not otherwise curated for public consumption—this contrasts with professional streams that might make use of either wholly staged environments (such as studios) or, at least, make use of staging and product placement within a more intimate environment. Microstreaming spaces, by contrast, were often shared with roommates or family members (who would often interrupt the streams), and at times, the spaces themselves were not groomed with a public audience in mind (such as having clothing or personal items in the background; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022).1 Collectively, these elements contribute to the creation of perceived authenticity among microstreamers, a sense that we are peering into their natural environment rather than viewing a produced and groomed presentation.

The Present Study

Although there has been robust growth in scholarship on game streaming, there is a paucity of work that specifically considers microstreamers. Informed by initial descriptive work (Consalvo et al., 2020; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022), the present study uses an experimental design to replicate and extend this prior work on several key dimensions. First, we used bespoke microstreaming videos that isolate three features of microstreaming (scriptedness, production value, and staged environments) while controlling for confounding elements such as variance in microstreamer demographics and personalities, games played, success while gaming, and myriad other elements. Second, we directly examine audiences’ perceived authenticity by sampling from a group of engaged gamers, polling them immediately after viewing the video. Using this approach, the present study allows us to empirically examine earlier assertions about how features of microstreams influence perceived enjoyment. Accordingly, we propose the following research questions:

Research Question 1: Is there a relationship between perceived authenticity and the unscripted (vs. scripted) nature of a microstreamer’s interactions?

Research Question 2: Is there a relationship between perceived authenticity and the presence (vs. absence) of on-screen production elements in a microstream?

Research Question 3: Is there a relationship between perceived authenticity and the staged (vs. unstaged) nature of the background of a microstream?

Finally, as a practical extension of these questions, we also examine the potential influence of increased perceived authenticity on the audience’s enjoyment of the microstreams. Here, two more research questions are formalized:

Research Question 4: Does perceived authenticity correlate with increased enjoyment of that content?

Research Question 5: Does perceived authenticity mediate the relationship between (a) unscripted, (b) production value, and (c) unstaged streaming content and enjoyment of that content?

Method

Participants were recruited through https://Prolific.com and invited to participate in a study “about how people respond to video game streaming videos.” They were paid $4 USD for participating in the study, which took 15–20 min to complete. Surveys, stimuli, and data files are shared online at https://osf.io/2rc4h.

Participants

A total of N = 403 participants completed the survey, with n = 385 willing to share at least some demographic information when prompted. Participants had an average age of M = 39.67, SD = 11.5, ranging from 19 to 73, with a majority identifying as female (n = 192) or male (n = 187). Median household income was just under $47,000 USD. Most participants identified their nationality as U.S./American (n = 362), and prevalent ethnicities included White/Caucasian (n = 266) and Black/African American (n = 57). The most common education level was having a 4-year degree (n = 143), with more respondents below (n = 117) than above level (n = 56). Participants reported an intermediate level of video gaming experience (n = 180) and playing just under 10 hr weekly (9:59:34), with either no (n = 219) or novice (n = 104) experience with game streaming. They viewed game streams a bit less than 3 hr weekly (2:48:53) and streamed themselves less than 1 hr weekly (0:46:14). Complete demographics are reported in the shared Open Science Framework documentation.

Procedure

We implemented an online survey experiment wherein participants were assigned randomly to one of the eight distinct conditions created by the combination of three factors: scriptedness (scripted vs. unscripted), production value (high vs. low), and staging (staged vs. unstaged; see Table 1). Random assignment to conditions was successful, χ²(7) = 0.43, p = .999. After random assignment, the participants watched an approximately 9-min video and answered questions on perceived authenticity and enjoyment.

Stimulus

To generate the research stimuli, we employed a confederate design in which one of our team members with experience in gaming and streaming (but not an active streamer) created microstreaming content for the study. We had the confederate play Valorant for approximately 9 min—we chose this game due to its overall popularity on Twitch (i.e., as the fourth-most watched video game for streaming, Esports Charts, n.d.). We stored this single game session as a separate video file and then used OBS Studio to record over that game session with one of eight different microstreamers videos, combining the elements below as different layers (see Open Science Framework for stimuli and supporting documentation at https://osf.io/2rc4h; Bowman et al., 2023). This procedure allowed us to keep gameplay constant in all sessions.

To manipulate scriptedness, the confederate regularly interacted with possible viewers, suggesting an awareness to engage with others during the stream (a higher level of scriptedness). For the unscripted videos, the confederate was generally unaware of any need to talk with viewers, mostly speaking to themselves. At two points, the stream was interrupted by another person. For scripted videos, the confederate was instructed to be mindful and aware of potential audiences watching the content and act accordingly—for example, offering extended commentary on game elements or talking through decision making while playing; this stream was never interrupted by others. To manipulate high production value, the confederate used a professional-style overlay displayed around the borders of their webcam while wearing gaming headphones and using backlighting. For low production value, the microstream did not use any overlays, and the streamer did not use headphones, an external microphone, or any backlighting. To manipulate staging, the confederate streamed from a clean and tidy dormitory room with several video game and pop cultural artifacts carefully placed around their dormitory room, creating a highly staged condition. In the unstaged condition, the dormitory room was unkempt and messy, with no such placement of gaming or pop culture artifacts. These manipulations were informed by prior observational research (A. M. Phelps et al., 2021; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022).

Measures

Authenticity

A five-factor model of perceived streamer authenticity borrowed from Lee and Eastin’s (2021) study was used in the present study, with four items for assessing sincerity (M = 4.88, SD = 1.25, Cronbach’s α = .88), four for measuring truthfulness (M = 4.52, SD = 1.14, Cronbach’s α = .74), four for visibility (M = 3.30, SD = 1.33, α = .81), three for expertise (M = 4.34, SD = 1.33, α = .88), and three for uniqueness (M = 4.25, SD = 1.34, α = .76). Participants were asked to indicate their level of agreement with statements on a 7-point Likert scale ranging from strongly disagree to strongly agree. A confirmatory factor analysis on the scale was performed given that the scale was amended to fit a microstreaming context, and the five-factor structure was supported: χ²(125) = 189.77, p < .001, comparative fit index = .928, Tucker–Lewis index = .912, standardized root-mean-square residual = .049 (see Bowman & Goodboy, 2020; also shared online at https://osf.io/t4e2r).

Enjoyment

Six items measuring perceived enjoyment of the stream adapted from Bowman et al. (2023) were used in the present study, M = 4.88, SD = 1.25, α = (.98), and this score was significantly higher than the scale neutral point of 4.00, t(402) = 14.1, p < .001, Cohen’s d = 0.7. Participants were asked to indicate their level of agreement with statements on a 7-point Likert scale ranging from strongly disagree to strongly agree.

Manipulation Check

To assess the conditions of the video, participants were requested to gauge the extent to which the video appeared scripted, exhibited production value, and appeared staged, on a scale ranging from 0 (indicating “not at all” or “lowest”) to 10 (indicating “completely” or “highest”). For all three variables, the scores were significantly lower than the neutral point. Specifically, participants rated the video as significantly less “scripted” than the scale midpoint, M = 2.20 (SD = 2.73), t(400) = −24.22, p < .001. Similarly, the video’s perceived “staged” quality received a significantly lower score midpoint, with M = 2.43, SD = 2.85, t(400) = −21.54, p < .001. In the case of “production value,” the scores were also significantly lower than the midpoint, M = 3.84 (SD = 2.57), t(400) = −12.89, p < .001.

Results

Manipulation Checks

Prior to data analyses, participants’ perceptions of scriptedness, production value, and staging of all videos were compared across conditions to see if our intended manipulations were successful at inducing variance in these perceptions. For perceptions of scripting, there were no significant differences across conditions, F(7, 393) = 1.13, p = .393. Likewise, for perceptions of production value, scores did not differ significantly across conditions, F(7, 393) = 0.937, p = .478. Finally, for staging, scores did not differ significantly across conditions, F(7, 393) = 0.976, p = .448. Such scores are unsurprising when we consider the generally low scores on these perceptions at the descriptive level, and overall, these data suggest that participants generally saw the videos as somewhat amateur regardless of experimental conditions. Put another way, all videos were viewed as equally unscripted, unproduced, and unstaged.2

Primary Analysis

Given that our focal manipulations did not systematically vary viewer perceptions of key variables, we instead used perception scores for scripted, produced, and staged as separate independent variables in three separate mediation analyses, with the five perceived authenticity factors (sincerity, truthfulness, visibility, expertise, and uniqueness) as parallel mediators and enjoyment as the dependent variable. These tests were performed using PROCESS 3.4.1 (Hayes, 2022), Model 4, with 10,000 bootstrapped samples.

Regarding perceptions of scriptedness, the standardized indirect effects of three of our five mediators were statistically significant, indicating a mediation effect of sincerity (−0.056, 95% CI [−0.104, −0.018]), visibility (0.013, 95% CI [0.001, 0.032]), and expertise (0.018, 95% CI [0.001, 0.042]). Full results are presented in Figure 1 (full output shared via Open Science Framework).

Regarding perceptions of production value, the standardized indirect effects of four of our five mediators were statistically significant, indicating a mediation effect of sincerity (0.092, 95% CI [0.055, 0.133]), visibility (0.035, 95% CI [0.008, 0.068]), expertise (0.059, 95% CI [0.021, 0.099]), and uniqueness (0.076, 95% CI [0.036, 0.119]); see Figure 2.

Finally, regarding perceptions of stagedness, the standardized indirect effects of three of our five mediators were statistically significant, indicating a mediation effect of sincerity (−0.056, 95% CI [−0.103, −0.017]), visibility (0.015, 95% CI [0.001, 0.034]), and expertise (0.018, 95% CI [0.001, 0.041]); see Figure 3.

Discussion

The present study extended descriptive research (A. M. Phelps et al., 2021; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022) to see if three features of a microstream—scriptedness, production value, and stagedness—could be manipulated to influence the perceived authenticity and subsequent enjoyment of microstreaming content. We sampled adults with substantial playing video games (∼10 hr per week) and watching game streams (∼3 hr per week) and who were infrequent streamers (less than 1 hr per week). Although our experimental manipulations were not strong enough to reliably manipulate perceptions of the microstreaming content itself, we did find that variance in perceived scriptedness, production value, and stagedness had a direct causal influence on enjoyment and (b) indirect effects on enjoyment as a function of some (but not all) perceived authenticity scores. We also found direct positive causal relationships between perceived authenticity and enjoyment for four of the five dimensions of perceived authenticity (all but “truthfulness”). These findings provide insights into how and why audiences might enjoy microstreaming videos.

(Un)Scriptedness, (Un)Stagedness, Sincerity, and Enjoyment

A key finding that largely aligned with prior work (A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022) was that when content was perceived as being more unscripted and unstaged, it was also seen as more sincere, which in turn increased overall enjoyment of the content. This finding reinforced the idea that the unpolished nature of microstreaming videos causes audiences to see the microstreamer as increasingly “kind and good-hearted,” “sincere,” “genuine,” and “down-to-Earth” in quoting the items from Lee and Eastin (2021). Most impressive was that as perceptions of sincerity increased, the resultant effect on enjoyment was strong; in all analyses, the effect represented nearly ∼0.400 to 0.500 unit increase in enjoyment when controlling for all other authenticity measures (or about half of a scale point). These findings collaborate with prior work suggesting that even among videos that were universally seen as rather unscripted and unstaged regardless of manipulation, audiences who viewed the videos as extremely unscripted and unstaged saw the microstreamer as more sincere and enjoyed the content as a result. Such a finding relates to prior research into influencer marketing (Lee & Eastin, 2020) and adds credence to the notion that hobbyist microstreamer content could be uniquely enjoyable because it is viewed as sincere and genuine.

Visibility, Expertise, Authenticity, and Increased Enjoyment

In contrast to the findings above for sincerity, in all other cases of statistically significant mediation, videos seen as comparatively more scripted, produced, and staged were seen as more authentic, which also boosted enjoyment scores. This would somewhat break from prior work suggesting that microstreaming content is more authentic because it is more hobbyist and amateur (A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022). That said, we can see a few arguments supporting the data patterns observed here. One is that the overall positive skew of perception scores is such that even higher ratings represent perception scores falling under the midpoint; that is, while some authenticity dimensions were higher when scriptedness, production value, and stagedness increased, this could still represent scenarios in which the videos were viewed as overall lower on all three dimensions. This would be a question for future research that might either/both (a) create more dramatic distinctions on all three features or/and (b) consider comparing microstreaming content to professionally streamed content directly. That said, the nature of some perceived authenticity dimensions might also explain some of these findings, especially regarding the positive mediating effects of visibility and expertise, as explained in the following section.

Visibility and Microstreaming

Via Lee and Eastin (2021), visibility is related to how the streamer communicates about themselves in ways that are “open and transparent” (p. 826). In this case, higher visibility is thought to facilitate feelings of friendship and perceived relational closeness (also see research into parasocial relationships and streaming; e.g., Leith, 2021). However, visibility seems to be less related to a single piece of content and more about consistent patterns of content (i.e., in a microstreaming channel)—items such as “not only posts about the good in their life but also about hardships,” “talks about real-life issues going on in their life,” and “talks about their flaws and is not ashamed of showing them to the public.” As audiences only saw a single piece of content, it is possible that viewers were unsure how to answer these questions. Indeed, the overall mean for visibility was the lowest of all perceived authenticity dimensions and the only one consistently under the scale neutral point (M = 3.30, SD = 1.33, Cronbach’s α = .81), one-sample t(402) = −10.57, p < .001, Cohen’s d = 0.53. This might also explain why the unstandardized β-weights for the causal relationship between visibility and enjoyment were consistently the lowest, contributing less than 1/5 of a scale point increase. Future research might consider prolonged exposure to content in which microstreamers discuss themselves beyond the context of game content itself (as seen in microstreaming of art content; A. Phelps & Consalvo, 2020). Consalvo et al. (2020) argued that, like professional streamers, microstreamers tend to build channels that are representative of themselves over time, and likewise, audiences are drawn to streamers that share similar perspectives and values (Li et al., 2020). Especially given that viewers in our study were not members of the microstreamers’ community, future work might need to replicate feature and authenticity perceptions within existing microstreaming feeds, channels, and groups.

Expertise and Microstreaming

Microstreamers were perceived as having more expertise when they were perceived as sharing videos that were increasingly scripted, produced, and staged. Via Lee and Eastin (2021), expertise is understood as a “natural ability” in which “content comes as genuine and effortless, rather than extrinsically motivated” (p. 826). Items asked about the microstreamer being “skilled” and “very knowledgeable” with “natural ability” with playing video games. We explicitly did not manipulate how well the microstreamer played Valorant during their session to remove the potential influence of actual gameplay performance variance, as we wanted to see the direct impact of features of the microstreaming video itself on these perceptions. However, it is possible that as audience perceptions of stream features increased, they corresponded to this innate sense of microstreaming skill to also transfer to gaming skills, a useful and compelling area of future research (especially given open questions about the influence of audience presence on gameplay; see Bowman et al., 2013).

Other Interpretations and Implications

Across all videos, perceived production quality was higher and closer to the scale midrange than perceived scriptedness and stagedness. Especially interesting here is that for production quality, increased production quality was a significant positive predictor of all other perceived authenticity scores, with effects that were three to four times as strong (in terms of unit increase). This might further reinforce the notion that videos viewed as having at least moderate production value were viewed as an overall positive indicator of the microstreamer’s abilities (Anderson, 2017)—both as a streamer and as a gamer—possibly engaging a “halo effect” of sorts (see Nisbett & Wilson, 1977) in which a higher quality stream was presumed to correspond with a streamer that is more sincere, honest, visible, expert, and unique.

It is possible that sincerity is a feature of being seen as more amateur, but being seen as more amateur could diminish other perceptions (such as honesty, visibility, expertise, and uniqueness). For example, it could be the case that microstreamers are seen not only as amateur streamers but also as amateur and casual gamers, which could reinforce a “hardcore versus casual” gamer distinction. In their work, casual players were famed as less authentic because they were viewed as having not invested the necessary time, money, and self-involvement into the gamer space broadly (i.e., they lack social capital; Consalvo, 2007). Although casual players tend to be associated with specific genres, having microstreamer status could also be seen as an indicator that one is not invested or participating in game culture broadly.

One reason that the direct and objective manipulation of microstreaming features did not work as expected could be that the features alone cannot be so easily separated from the microstreamer themselves. It could be the case that there are intricate interactions between a microstreamer’s personality and self-presentation that directly interact with the framing and features of the microstream—certain microstreamers might have more semantic affinity with variable scripted, produced, or staged environments. The present study examines more technical elements of (micro)streaming, but it could be that there is a more sociotechnical relationship between the microstreamer and their content that is responsible for perceived authenticity and enjoyment (Li et al., 2021; Shen, 2021). Somewhat related to this, yet another reason for invariance in our intended manipulations could be from more heuristic processing of the content—viewers quickly realized that they did not recognize this streamer, that their channel was not a “known quantity,” and that the overall aesthetic of the videos was not on par with popular monetized streams. As such, it is possible that once content is seen as microstreaming (or at least, seen as not from a professional stream), there is an overall suppression effect—it is presumed to be unstaged and unscripted (scores quite low in our study) and having only moderate production value. Such is an assertion that could be tested in future research. That said, this assertion would not invalidate the findings of the present study: Variance in perceived scriptedness, production, and staging still had significant and meaningful impacts on perceived authenticity and enjoyment.

Finally, we observed that the overall explained variance in enjoyment of these streams is quite high. These data suggest a strong association between perceived authenticity and enjoyment of microstreaming content, which fits the broad suggestions from prior research that such content is enjoyable because it is viewed as authentic (Consalvo et al., 2020; A. Phelps, Bowman, et al., 2022; A. Phelps, Consalvo, et al., 2022). That said, future research would want to directly test for these associations in other types of game streaming content, such as content from professional streamers. Comparing the strength of those relationships between microstreamers and professional streamers would help us better understand (a) overall patterns of perceived authenticity as a function of amateur or professional status and (b) if perceived authenticity benefits enjoyment regardless of amateur or professional status (also see Lee & Eastin, 2020, 2021). Given that Lee and Eastin’s (2021) perceived authenticity metric was validated in the present study, future research might consider using this metric for making these comparisons.

Limitations and Future Research Directions

As an experimental design for which internal validity is a key focus (i.e., ensuring that content manipulation is clear and distinct from each other and that content does not vary in other dimensions), our study necessarily required us to create our own game streaming videos and show those in an archived rather than livestream format. Moreover, the manipulation of the videos in this study—focusing on scriptedness, production value, and stagedness—highlighted characteristics attributed to microstreamers in prior observational research of existing microstreaming content. That said, our manipulation checks did not suggest that the videos were seen as varying on these dimensions. Such a limitation suggests that more research is needed to gain a better understanding of both (a) the various ways in which scriptedness, production value, and staging might manifest across a broader selection of microstreaming content (such as more observational work and content analysis) and (b) a more nuanced understanding of the features of microstreaming that audiences might see as being more or less reflective of these concepts (i.e., more survey and interview research with microstreaming fans and consumers). Notably, the present study does suggest the importance of perceptions of these three features, suggesting potential for this line of inquiry. That said, it is also possible that there was a mismatch between the terms used to describe our manipulation and how participants understood them. For example, “stagedness” for us was a focus on an organized environment with gaming elements, suggesting that the streamer was actively curating for the audience (i.e., to reinforce a gamer identity). Yet, it is just as plausible that participants saw this as a rather typical space for gaming, and thus, it did not seem “staged” in an artificial way. In a sense, such an interpretation would add credence to microstreaming authenticity, and indeed, such a finding was revealed in our post hoc data analysis.

Related to the point above and noting that our perceived authenticity scale performed overall quite well in the present study, it is possible that authenticity is more idiosyncratic and interacts with the audience’s own identity in ways that we did not capture—a notable area of future research. Our metric was modified from influencer marketing scholarship (Lee & Eastin, 2020, 2021), and while the subdimensions of the scale—sincerity, truthfulness, visibility, expertise, and uniqueness—were deemed contextually relevant for microstreamers as well, it is plausible that there are other dimensions of perceived authenticity not captured in this measure.

Moreover, although game streaming does prominently feature and include prerecorded and curated footage (see Lin et al., 2019), a compelling replication and extension of this research would be to see if and how microstreamer content is perceived when consumed in situ—both in terms of the authenticity of the streamers and enjoyment of the content. Notably, none of our videos were viewed as inauthentic or “fake,” and thus, (a) audiences did not perceive this content as overly contrived (i.e., as part of a research project), and (b) the videos were perceived to be similar from what we would expect from other microstreamers “in the wild.” Likewise, it might be useful to directly engage cross-sectional scholarship that asks audiences to recall (or perhaps even select) microstreaming content and assess the features of that content that seem to make the content more or less authentic.

In our videos, the female streamer was featured in all eight conditions, and scholarship has examined the gender dynamics within gaming and game streaming cultures. Specifically, research indicates that female streamers often experience objectification (Nakandala et al., 2017), with their success being perceived as more closely linked to their personality or appearance rather than their gaming skills (Uszkoreit, 2018), and future research could directly investigate potential gender identity effects. Finally, the limited viewing time by the participants (9-min microstreams) may not have allowed for deeper engagement, leading the participants to perceive authenticity; instead, it may have led to quick, first-impression judgments.

Finally, we note that the respondents to our study were unique in that they were older (with an average age in the late 30s) and frequent gameplayers (just under 10 hr weekly), with some experience viewing game streams (under 3 hr weekly). These demographics likely skewed older and with slightly less experience streaming than gamer audiences with a more focal interest in game streaming (see Cabeza-Ramírez et al., 2021). Our data are notable in that they tap an older and engaged gaming audience not commonly included in gaming research, but future research should more specifically target other audiences with more direct experience engaging with game streaming videos—both as audiences and as streamers themselves through various revenues. That said, we would argue that more casual gaming content (such as microstreaming) might well appeal to nontraditional gaming audiences or those who are less invested with or engaged with game streaming services. Some of this argument mirrors other long-tail distributions of streaming content that appeal to nuanced interests, such as art streamers (A. Phelps & Consalvo, 2020).

Conclusion

This study investigated the perceived authenticity and enjoyment of viewing microstreaming content by manipulating three characteristics from prior descriptive research: scriptedness, production value, and stagedness. Although these manipulations did not yield expected outcomes, audiences’ perceptions of those characteristics had several notable effects. Content that was perceived as more unscripted and unstaged was associated with increased sincerity, resulting in higher overall enjoyment. Videos perceived as more scripted, produced, and staged were linked to greater perceived expertise and visibility within the subdimensions of authenticity, leading to enhanced enjoyment scores. Additionally, we provided a validation of perceived authenticity measures appropriate for studying streaming content. Overall, findings help advance research into microstreaming—data help us better understand how authenticity affects viewer enjoyment in streaming content, with implications for content creators and user-generated content broadly.

Supplemental Materials

https://doi.org/10.1037/tmb0000134.supp

Copyright © The Author(s) 2024

Received November 1, 2023
Revision received April 11, 2024
Accepted April 12, 2024