Living at the Speed of Mobile: How Users Evaluate Social Media News Posts on Smartphones

Abstract

A growing body of research suggests that differences between smartphones and desktop computers influence information processing outcomes. A within-subjects (N = 64) smartphone eye-tracking experiment replicates a 2018 desktop-based study of users’ visual attention to and engagement with social media news posts. The results show that users spend less time viewing social media news posts on smartphones than desktop, and report lower levels of pleasure and arousal in response to the posts. However, the study found no significant difference between devices in intent to click to read the story and intent to share the post. The findings are discussed with regard to implications for the role of device and attention in communication theory, as well as practical implications for news organizations and other social media content producers.

Keywords

mobile emotion images attention social media

Recent surveys show that 81% of Americans own a smartphone, and that number rises to 96% among 18 to 29-year-olds (Pew, 2018). For those smartphone owners, the device serves as a conduit to news, with 86% reporting getting at least some news via their mobile devices (Shearer, 2021) and now more getting news on mobile versus desktop (Nelson & Lei, 2018; Walker, 2019). The most recent Pew research study to examine American news consumption shows that a full 57% of adults often get their news on mobile devices, and just 30% report getting their news often on a desktop or laptop computer (Walker, 2019). Research into how people evaluate content on mobile platforms is burgeoning. Existing research has looked into the shift to predominantly digital, and now mobile methods for reporting and publishing news and its adoption by both journalists and newsrooms (Hermida et al., 2012; Marchionni, 2013; Westlund, 2014). Other research has focused on the mobile apps created and initially designed mainly to generate revenue, but which have since become a way to synergize online and mobile access and create a positive user experience that leads to increased engagement (Westlund, 2014). This alignment with the user has brought tremendous growth; today, users on mobile spend 89% of their device time accessing social media applications such as Facebook, news and email apps (Chaffey, 2021). For the news industry, garnering attention to social media posts about news is critical, as just 28% of news consumers directly access news content, with the majority accessing news via “side door” points of entry (Newman et al., 2020). The most prominent single side door point of entry in 2020 was social media, accounting for 26% of traffic among all age groups and 38% of the coveted traffic among18 to 24-year-olds (Newman et al., 2020).

While these general trends about social media use on mobile devices have been well-established, little is known about how viewing content on mobile screens changes the processes consumers use to evaluate and select news content from social media feeds. While studies to date have shown that images in social media posts drive engagement (Guerini et al., 2013; Ulloa et al., 2015), just a handful of this research has differentiated between devices. Recent work that has built on the understanding of how users engage with mobile content explored video viewed on mobile (Dunaway & Soroka, 2021; Kim & Sundar, 2016), issues regarding trust of content viewed on mobile (Kim & Sundar, 2016), attention to actual news content on mobile and desktop (Dunaway et al., 2018) and differences in cognitive and physical access to mobile content (Dunaway & Soroka, 2021). Further, a culture of “snacking” on news content has been identified as users tend to visit multiple applications and scroll through content rather quickly, reading bits and pieces rather than full stories (Miller, 2007; Molyneux, 2018).

What we explore here builds on this past work by examining the role of images and emotion in how users view and engage with social media posts on mobile devices in comparison to desktop computers. This study replicates on mobile, a desktop study carried out by Keib et al. (2018). In this study, we utilized eye tracking on smartphone screens to explore how visual attention to social media posts promoting news stories varies based on two characteristics: the device on which the posts are consumed and the presence of emotion-inducing images. Attention times tell us how much visual attention a post garnered, an important measure, especially in considering the difference between desktop and mobile. In addition to looking at attention, we also sought to examine how device and image influence emotional response to the post, intention to click the post to read the full story, and intention to share the story with one’s social network peers. The findings of this research build on the growing body of work that examines attention on mobile devices and the psychological effects people experience when consuming content on mobile devices. The findings can help guide those creating news content for social media posts, and thus has the potential to drive news content traffic and increase consumers’ engagement with news in general.

Literature Review

Attention on Mobile

The process of selecting news content via posts in a social media stream requires the consumer to make judgments based on a limited and different set of cues than when accessing content directly from an organization’s website. Posts with news on Facebook, for example, can carry cues such as emoticons, comments, or endorsement-related cues from the friend or organization who shared the content. Over time, as consumers habituate to social media, these cues may be processed heuristically or automatically without much thought (Hilligoss & Rieh, 2008; Sundar, 2008), and as a result of this lack of thought, they may be misapplied when a website looks like a trusted site (Metzger, 2007). Thus, the entry point to content posted on social media—the post itself—carries great importance in consumers’ initial assessment of the value of the news material and may also influence further consumption and interaction choices.

Mobile content appears different from content accessed via desktop in several key ways. The screen size on mobile is smaller, the applications themselves have a different layout, and the context of consumption can be quite different. People also interact with content differently on the smaller screen used in mobile consumption. While people tend to read desktop content in an F-shaped pattern (Nielsen, 2006), reading on mobile devices does not follow this same pattern. Users on mobile employ several different styles of reading, identified by researchers using eye tracking as full screen, linewise, and blockwise (Biedert et al., 2012). These different reading patterns, coupled with the ability to scroll quickly through newsfeeds and pages, are unique features of mobile news reading. Facebook, when opened on a mobile device, displays only posts in the feed, omitting the desktop version’s account-specific information on the left and boxes regarding recent stories and friends on the right side of the screen. Mobile consumption, often taking place during interstitial spaces in time such as while commuting or during commercial breaks, also presents a different context (Westlund, 2014).

Despite an increase in average daily time spent on mobile, (Fedeli & Matsa, 2018) existing research suggests that both the time spent reading and the attention to online news were lower for mobile rather than desktop devices (Dunaway et al., 2018; Molyneux, 2018). In one study, participants self-reported spending slightly less time reading news on mobile devices compared to desktop computers (Molyneux, 2018). Other studies employing eye-tracking techniques yielded similar results. For instance, Dunaway et al. (2018) found that participants on mobile spent less time reading news content and fixated on links for a shorter amount of time than participants viewing content on a desktop.

This lower amount of time spent with and attention to content on mobile is largely attributed to what researchers call information seeking costs, which include physical barriers to content access that are not equivalent on desktop, such as connection type and the quality of the data connection; financial cost to connect (data usage limits); slow connection speeds due to network usage; and a decreased ability to save, store, and share documents on the mobile platform (Dunaway et al., 2018). Although these information-seeking costs are a factor in real-world consumption of mobile content, less is known about whether these constraints are also a salient aspect of mobile news consumption through social media applications—a gap that this study seeks to address.

In addition to information-seeking costs, researchers have also considered screen size differences between mobile and desktop as a potential reason why attention to content may vary between devices. Past work has shown that smaller screen sizes make completing tasks on mobile devices more difficult than on desktop computers and tablets (Chae & Kim, 2004; Dunaway & Soroka, 2021; Jones et al., 2003; Kim & Sundar, 2014). Due to the limited interface elements that can fit on smaller mobile screens, the effort it takes for users to navigate and process information may be increased (Lee et al., 2014). This is a burden because users in a mobile environment may already have lower cognitive resources available than those in a sedentary one, such as while viewing content on a desktop (Chan et al., 2002). Specific differences between mobile and desktop related to usability include presentation, what is seen and what is not seen on one but not on the other, text/reading, including the length of content lines, text breaks and scrolling, interaction, navigation, and design (Marcial, 2012). Thus, cues that users notice on desktop may be missed in a mobile environment, which impacts how content is processed and interpreted.

People have been shown to resort to the more taxing systematic processing to assess mobile content due to the screen size constraints (Kim & Sundar, 2016). Systematic processing involves allocation of greater cognitive resources and attention to message content (Sundar, 2008). However, more recent work has shown that people experience lower cognitive engagement with content viewed on mobile screens (Dunaway & Soroka, 2021). Sundar’s MAIN model of information processing explains that four structural features of digital media, modality, agency, interactivity, and navigability, cue users and lead to have a positive or negative experience with digital interfaces and content (Sundar, 2008). Each modality triggers a heuristic, which can lead to a judgment, or to deeper systematic processing before a decision is made (Sundar, 2008). Thus, the MAIN model of information processing (Sundar, 2008) suggests dual heuristic possibilities—both that the technological affordances of the mobile platform trigger a heuristic such as the realism heuristic and then heuristic processing but also that the absence of modality cues on the mobile platform, as might occur on a smaller mobile screen, would lead to systematic processing. Thus, we present the following research question:

RQ1: Do users who view social media posts on a mobile device pay more or less visual attention to the post content than users who view posts on a desktop computer.

Attention and Psychological Responses to Posts on Mobile

The factors that affect time spent on and attention to content on mobile devices mentioned so far can also shape psychological responses to content. Often, psychological response is defined as emotion, and it involves three dimensions—pleasure, arousal, and dominance (Russell & Mehrabian, 1977), although most studies focus on the arousal and pleasure dimensions. Arousal represents the level of excitement, while pleasure involves either the positive or negative valence of the response (Lang et al., 1996; Russell & Mehrabian, 1977). Users often put more emphasis on affective dimensions of mobile device usage, rather than utilitarian affordances (Kim & Sundar, 2014), highlighting the importance of understanding what triggers affective response on that medium. Additionally, high levels of arousal lead people to pay more attention to messages (An & Lee, 2017). Knowing that, as described previously, attention may be lower on mobile devices, how does the lower attention impact arousal and pleasure?

Existing research suggests that device screen size can impact the extent to which users experience emotional reaction to media. Indeed, screen size allows users to see content better and more fully, which, in turn, enables the affect experience (Kim & Sundar, 2014). The body of work in this area supports the premise that larger screen sizes equate positively with psychological responses such as arousal, presence, enjoyment, satisfaction, immersion, and realism (Detenber & Reeves, 1996; Dunaway & Soroka, 2021; Kim & Sundar, 2014). For example, a study conducted by Dunaway and Soroka (2021) in which participants watched a video either on a mobile or desktop device found that screen size not only impacted arousal, but cognitive engagement as well. Other studies have found similar results as well, specifically that higher levels of arousal can lead people to pay more attention to messages (An & Lee, 2017).

Arousal can be measured in more than one way. For example, in the Dunaway and Soroka (2021) study, arousal was measured through heart rate variability (HRV), meaning that an increase in heart rate indicates an increase in arousal. Related to screen size, their study found that HRV decreases with screen size. Another way to measure arousal is via self-report; this approach often employs the Self-Assessment Mannequin (SAM). One study that used the SAM to measure arousal as a function of screen size found that participants experienced higher levels of arousal when viewing larger images (Detenber & Reeves, 1996). Since these studies afford evidence that larger screen sizes are related to higher levels of arousal when viewing videos and images, we propose the following regarding social media:

H1: Users who view posts on a mobile device will report lower arousal than users who view the same posts on a desktop computer.

In addition to screen size, research has also found a relationship between emotion and time spent viewing images on mobile devices. Studies have shown that emotional content is a critical element to gaining attention—and keeping it. Content that incites pleasure is more likely to generate longer fixation and gain attention more quickly (Tao, 2010) as well as aid in recall (Bellman et al., 2009). This ability of content that incites emotion to attract people quickly is critically important on a platform on which people quickly scroll and “snack” on content (Miller, 2007; Molyneux, 2018). Specific to news on mobile, Molyneux found that people spend less time reading news on mobile devices than on desktop computers, and that this consumption on mobile is spread throughout the day in short bursts of time (Molyneux, 2018).

Rather than directing attention to utilitarian aspects of content consumed on mobile devices, users often put more emphasis on affective dimensions (Kim & Sundar, 2014). For example, participants reported a stronger reaction to pleasant images on larger screens versus smaller screens (Codispoti & De Cesarei, 2007). Images that participants rated as pleasant elicited a stronger emotional reaction than unpleasant images, but when the screen size was smaller, negative images elicited a stronger emotional response (Codispoti & De Cesarei, 2007). Bellman et al. (2009) found that people habituate to a level of emotional response based upon the screen size. Taken together, these studies suggest that while emotional content and images can drive user attention, the overall size of mobile devices and the transient/temporal news consumption patterns they afford may present a challenge for user enjoyment and pleasure. As such, we propose the following:

H2: Users who view posts on a mobile device will find images less pleasurable than users who view the same post on a desktop computer.

Psychological Response and Engagement

Exposure to news on social media also happens incidentally (Boczkowski et al., 2018; Fletcher et al., 2018). Users on social media receive stories shared by friends, which may not represent the views of the actual user themselves. In a study involving users of Facebook, YouTube, and Twitter in four different countries, findings showed that users did indeed engage with news that came to them incidentally and that the effect of exposure was stronger among those who were younger and less interested in news (Fletcher et al., 2018). Additional work has shown that people are not spending much time with content they come to via social media, and that they only click through to content sporadically (Boczkowski et al., 2018), thus the ability for content to capture the user’s attention is critical to engagement and emotion is a driver of engagement (Coviello et al., 2014; Keib et al., 2018).

A few studies have examined characteristics of social media news content that increases its likelihood of being shared and posted. Al-Rawi’s (2019) examination of 50 widely shared news stories showed that news consumers are more likely to share (by posting or reposting) or read news stories that are overwhelmingly positive in nature. Some evidence has shown that “soft” or editorialized news is more likely than hard news to be shared on Facebook and Twitter (Kalsnes & Larsson, 2018). One of the few experimental studies of social media news content and sharing behavior to date was conducted by Keib et al. (2018), who sampled news stories and paired each with images that had been previouslys evaluated for their likelihood of inducing positive or negative emotions. Their study found that participants who viewed the social posts on a desktop screen spent more time on, and experienced greater physiological arousal from, social media news posts when they contained an image than when the posts contained no image. Participants also indicated a greater willingness to share posts containing a positively valenced image than those containing no image at all (Keib et al., 2018).

In a study that manipulated the level of emotional arousal, then consequential social sharing and reaction to the content, participants who faced the highest levels of emotional content were most likely to experience cognitive effects and to share the experience (Berger, 2011); Luminet et al. (2000). In fact, regardless of the direction of valence, emotional content caused participants to share more frequently in multiple scenarios (Berger, 2011). On social media, content that provoked high levels of pleasure led to greater arousal and then greater social sharing of the content (An & Lee, 2017). When emotional content is encountered on a mobile device, the expected differences in attention and arousal we predict may lead to diluted willingness to share content.

Thus, we propose:

H3: Users who view content on a mobile device will be less likely to click on or share images than users who view content on a desktop computer.

Method

This study involves a mobile replication of the author’s recently published study conducted on desktop computers (Keib et al., 2018) and a comparison of the mobile and desktop results. Building on the original study, assignment to groups in the present mobile study followed that of the original study of participants on desktops (N = 60). Participants (N = 64) were randomly assigned to view 29 social media posts that each contained a news story link in the form of an image and accompanying text. For each participant, one-third of the posts viewed contained a negative image, a third contained a positive image, and a third contained no image. Eye-tracking data was collected while participants viewed each post, and scale measures (accompanied by thumbnail images for reference) were completed after participants had viewed all 29 posts.

Due to the additive nature of the design, where data on the mobile participants were collected as a separate comparison group, participants are not randomized into the mobile and desktop conditions. However, the student samples were drawn from the same pool, using the same processes and are well matched on all relevant observable characteristics. Specifically, our study sample closely matched the racial and gender composition and age of the original sample in mean age, gender, time spent on social media and time spent consuming news. The mean age for mobile was 20.4 years compared to 20.3 in the desktop study, gender in the mobile study was split 69% female, 31% male versus 76% female 24% male in the desktop study, and the racial ethnic categories were within 4% of each other. The participant pools were also closely matched on two self-report control variables we measured: time spent on social media (2.7 hours in mobile study vs. 2.5 desktop) and time spent consuming news (3.3 hours for mobile vs. 3.3 hours for desktop).

Participants

Participants were students enrolled at a large public university in the southeastern U.S. Mean participant age was 20.4 years (SD = 1.5). A majority of participants reported their race as White (74.5%), while 8.8% identified as Black or African American, 8.8% identified as Asian or Asian/Indian and 3.9% reported being Hispanic or Latino. The remainder of answers were limited to one respondent each, and four participants chose not to report a racial identity. Participants were able to report their participation in the study to earn extra credit in courses that offered such an opportunity.

Stimulus Materials

Social media posts were based on the 29 images included in the 2018 study by Keib et al. The posts were created based on actual news stories from a wide range of outlets (e.g., Washington Post, Vox, ABC News). News headlines were held constant, and either a positively valenced, negatively valenced or no picture was included in the post. Twenty-nine news stories were selected and for each news story, six versions of the post were created (positive, negative, no picture). In addition, a Facebook and Twitter version was created for each (see Figure 1 for examples).

Figure 1.

Examples of stimulus materials (News story #12 shown).

Dependent Measures

Visual attention to the news post

Visual attention was operationalized as the sum of participants’ total fixation duration within the perimeter of the social media post. Gaze location and duration was captured with a Tobii X2-60 eye-tracker, and processed through an I-VT fixation filter for noise reduction. The eye tracker recorded participant’s pupil fixations at a sampling rate of 60 Hz. Areas of interest spanning the boundaries of the area taking up the post on the phone screen were drawn within the video recording to calculate the fixation field. Each area spanned 720 px × 1,040 px with regard to the iPhone’s native resolution, equivalent to an effective resolution of 360 px × 520 px due to the phone’s 2× scaling factor. For each participant, the visual attention scores for individual posts were calculated and the means are presented and analyzed in the results section.

In order to capture eye-tracking data on the smartphone, we utilized a mobile device stand developed by Tobii. The X2-60 eye tracker was mounted directly to the stand, and the iPhone was placed on a reusable sticky pad within the stand, which allowed participants to rotate and handle the phone in most directions. The stand featured an overhead-mounted camera that recorded the entirety of the area of the phone plus added spatial buffer on all four sides. Prior to beginning each study, the eye-tracker was calibrated for each participant using a 5-point calibration plate that was positioned over the phone itself.

Intention to click

Participants answered the following question using a 7-point semantic differential scale ranging from very unlikely to very likely: “How likely would you be to click through and read this story?” (Shamdasani et al., 2001). As was done for visual attention, the mean scores were calculated and are presented and analyzed in the results section.

Intention to share

Participants utilized a 7 -point scale ranging from very unlikely to very likely to answer the question, “How likely would you be to share this story by clicking the “share” button? (Twitter question would say by retweeting this post?)” (Wojdynski & Evans, 2016). The addition of the option, “I don’t have sufficient information to decide” was added. Again, mean intention to click scores were calculated for each participant and the means are presented and analyzed in the results section.

Pleasure

Pleasure was measured using the scale from the SAM (Rodgers & Thorson, 2012). Participants saw a news post, then were asked to rate the image using the scale containing 9 points. The levels for emotion ranged from unpleasant (1) to pleasant (9). Five manikin images were used between the poles of the scale (at the 1, 3, 5, 7, and 9 markers) in order to depict various levels of emotion. The mean scores are presented and analyzed in the results section.

Arousal level

Arousal was measured using the SAM arousal scale (Rodgers & Thorson, 2012). Participants each viewed the news post, then rated the image using the 9-point scale, with levels for arousal ranging from “calm” (1) to “exciting” (9). As was done for pleasure, the five manikin images at the (1, 3, 5, 7, and 9 markers) were used to depict different levels of arousal. Mean scores are presented and analyzed in the results section.

Procedure

Participants visited a campus computer lab designed for eye-tracking research and completed an informed consent document. Participants in the desktop condition viewed the social media posts on an 18-inch Dell desktop computer monitor, on which the eye-tracker was mounted at the bottom edge of the screen. Participants in the mobile condition viewed content on an iPhone 6 that was attached to a mobile device stand that held both the eye-tracker and a scene camera to capture the user’s screen. Both desktop and mobile participants were also randomly assigned to one of three permutations of the stimulus materials, each of which paired a third of the stories with a negative image, a third with a positive image, and a third with no image.

Each participant viewed 29 social media posts described above, with the originating website’s logo displayed within each social media post. Throughout the time during which participants viewed the images, visual attention to areas on their device screen were captured by the eye-tracker.

Researchers instructed participants to advance to the next image by clicking a button at the bottom of each image screen after sufficient viewing of the current image. A Latin square design was used to vary image order, thus avoiding presentation order effects. After viewing all 29 images, participants completed a questionnaire consisting of a thumbnail image and four measures for each image: perceived emotional valence of the post, perceived arousal level of the post, likelihood to click through to read the story and likelihood of sharing the story.

Results

Before beginning the tests of hypotheses, we wanted to ensure that the three between-subjects conditions pairing different stories with different valences pairings did not have a significant impact on results. To test this, a MANOVA was conducted with condition as the fixed factor, and all 15 dependent measures included (visual attention, pleasure, arousal, intention to click, and intention to share, each averaged for the positive, negative, and neutral images participants viewed). The results showed that there were no significant differences for condition on any of the 15 variables (Fs (2, 98) ranged from: 0.24 to 2.42).

Our initial research question explored whether people who view content on a mobile device would spend more or less time with the social media posts on the mobile device in comparison to the original desktop-based study. To test the research question, an independent-samples t-test compared the mean attention time for each post across the two device conditions. The results showed that mobile users spent less than half the total time (M = 1.07 seconds, SD = 0.93) viewing the images in the posts than desktop users (M = 2.21 seconds, SD = 1.54), t(112) = 4.71, p = .001.

H1 predicted that viewers’ arousal ratings would be lower for mobile users than for the desktop users in Keib et al. (2018). An independent-samples t-test was used to compare the two device groups’ arousal ratings. The results showed that arousal for images viewed on mobile was significantly lower (M = 3.68, SD = 1.14) than for images viewed on desktop (M = 4.09, SD = 1.09), t(122) = 2.05, p = .042. Thus, H1 was supported.

H2 predicted that viewers’ mean ratings of pleasure experienced for the images would be lower for mobile users than for the desktop users. An independent-samples t-test was used to compare the two device groups’ arousal ratings. The results showed that pleasure for images viewed on mobile was significantly lower (M = 4.59, SD = 0.64) than for images viewed on desktop (M = 4.89, SD = 0.80), t(122) = 2.34, p = .021. Thus, H2 was supported.

H3 predicted that mobile viewers would have lower intent to click and intent to share stories on mobile than desktop. Independent-samples t-tests showed no significant difference for device on intent to click, t(122) = −0.23, or on intent to share, t(109) = 0.30. Thus, H3 was not supported.

Discussion

In examining how some social media news posts drive attention and engagement on mobile devices in contrast with desktop computers, this study has presented a novel test for the effect of emotion-laden images and means of exposure on audience engagement. Indeed, this study provides a clear picture of differences between desktop and smartphone viewing as the exact same stimulus was used and procedure followed in examining content on these platforms. Considering how people examine and engage with social media posts on mobile vs. desktop devices, this study revealed several important results.

First, the results showed that users pay significantly less attention to social media posts on mobile than they do on desktop computers. The existing body of literature provided opposing predictions for how people attend to content and images on mobile devices. Our study shows support for research indicating that people spend less time with content on mobile devices (Dunaway et al., 2018; Molyneux, 2018). Reasons suggested for shortened attention include information seeking costs (Dunaway et al., 2018), inhibited cognitive resources (Chan et al., 2002) and the smaller screen size (Chae & Kim, 2004; Dunaway & Soroka, 2021; Jones et al., 2003; Kim & Sundar, 2014). When it comes to information seeking costs, our study removed the barrier of internet connection speed, cost of and quality of the data connection. Cognitive attention generally means that attention is split on mobile due to other peripheral tasks being attended to (Chan et al., 2002). Therefore, the smaller screen size and effort it takes for users to scroll and move through content on mobile is most likely the reason for lower attention compared to desktop.

Another potential reason for lower attention could be tied to our second and third hypotheses, considering arousal and pleasure levels when viewing mobile content. Users in our study reported lower arousal and pleasure when viewing posts on mobile devices vs the same post on a desktop computer. Prior research has indicated that users often emphasize affective rather than utilitarian affordances when using mobile devices to view content (Kim & Sundar, 2014) and that higher arousal leads to great attention to mobile content (An & Lee, 2017). Thus, the lower psychological response could well be tied to the lower attention, indicating a twin challenge for creators of content destined to be viewed via social media posts on mobile devices. Features of the devices themselves, the usability features and screen size primarily, challenge social media managers and content creators to capture attention and drive strong emotional response via their posts. Keeping in mind that news organizations get only 28% of traffic directly to websites and apps combined, and 26% of traffic over all (38% for 18–24 year olds) directly from social media, (Newman et al., 2020), it is critical that news organizations get the attention of their potential audiences quickly and with strong psychological reaction, that is, emotional response. While small-screen mobile traffic from social media may be an important stream of inbound traffic, news organizations may also benefit from seeking to engage users on larger screen devices, where the visual content can be more likely to affect their responses. While our study only examined social media posts, it’s possible a similar device or screen-size effect governs users’ browsing and evaluation of story links and thumbnails on publications’ own homepages and section pages.

Finally, users in our study were just as likely to engage with content on the mobile platform than those who encountered social media posts on the desktop computer. Considering the finding that users spend half as much time with content on mobile versus desktop, the willingness to click and share has ramifications for what content does end up getting shared. We see that people may not be carefully processing content on mobile because their attention, pleasure and arousal levels are lower than on desktop. Yet our findings show that they are just as likely to click and share as they are on desktop. Thus, the stakes are high and the situation is ripe for the sharing of misinformation on mobile. Indeed, past work has shown that people who consume news incidentally on social media view a wide variety of sources (Fletcher et al., 2018), thus potentially contributing to their misunderstanding of the source of content. When people jump from site to site, they often misremember the source of the content (Shearer & Gottfried, 2017). In a political and social environment where popular posts on social media are often false, to the point of being flagged by the social platforms themselves, quick, emotional decision making can have serious implications in society.

Limitations and Future Research

In today’s media landscape, understanding what motivates the prolific sharing of misinformation is an important topic. Although this study did not set out to explore that concept, the findings do paint a picture of how people end up sharing mistruths and fake news via social media on mobile. Future work could specifically study the cognitive processes involved in users’ sharing decisions, and examine whether different factors govern those decisions on mobile versus desktop. In addition, recent research (Nelson & Lei, 2018) has explored the difference in consumption on mobile news apps vs. mobile news browsers. Future research could explore design differences between mobile browsers and apps and utilize eye tracking to capture attention differences.

There are also a few limitations worth noting. The present study and the Keib et al. (2018) study showed content on different devices that differed in more ways than screen size; desktop computers also offer a different input modality than smartphones (mouse vs. touchscreen). These studies do not allow a way of examining what specific difference between the devices caused differences in dependent measures. Additionally, because viewers completed the dependent measures questionnaire on the device they used in the study, it’s possible that variation in device, screen width, and input modality may have affected their questionnaire responses. The study was conducted exclusively using an Apple iPhone 6 as the mobile device. Although this device is most commonly used by the population sampled here, future work should examine whether these mobile-to-desktop differences vary based on device and size, as different mobile devices have differing form and function. Also involving the device used, in conjunction with the eye tracking device, it is required that the iPhone be attached to a device stand. This of course is not the natural way in which people hold and engage with a mobile device. Two factors regarding the study population bear mentioning. The study population had a narrow age range, and was relatively homogenous in terms of race and education. Future studies should examine whether these findings hold with other populations, particularly older users, who may view and engage with smartphone social media content differently. However, the homogeneity of the study group in total lends credibility to the results, as 3 months passed between collection of the desktop data and collection of the comparison mobile data.

Conclusion

This study sheds some light on the differences in how people process content on mobile versus desktop screens and is among the first studies to compare visual attention to the same content by device. By comparing users’ eye-tracking data and self-report, we have a robust picture of the attention to, emotional response to and behavioral decisions about images viewed on both platforms. Knowing that users’ attention to content on mobile is shorter in duration than to that on desktop, practitioners can make careful decisions about how to maximize the short window of time allocated by the public. This work shows that including pictures, especially those that evoke emotion, can be a key determinant of engagement with the audience. Furthermore, knowing that users are as likely to click or share on either platform, publishers can make decisions about how best to use specific attributes of each in order to drive deeper engagement. Due to the rapid development of technology, and increasing adoption and use of mobile computing, this study provides a timely picture of mobile content consumption.

Supplemental Material

sj-pdf-1-crx-10.1177_00936502211018542 – Supplemental material for Living at the Speed of Mobile: How Users Evaluate Social Media News Posts on Smartphones

Supplemental material, sj-pdf-1-crx-10.1177_00936502211018542 for Living at the Speed of Mobile: How Users Evaluate Social Media News Posts on Smartphones by Kate Keib, Bartosz W. Wojdynski, Camila Espina, Jennifer Malson, Brittany Jefferson and Yen-I Lee in Communication Research

Supplemental Material

sj-pdf-2-crx-10.1177_00936502211018542 – Supplemental material for Living at the Speed of Mobile: How Users Evaluate Social Media News Posts on Smartphones

Supplemental material, sj-pdf-2-crx-10.1177_00936502211018542 for Living at the Speed of Mobile: How Users Evaluate Social Media News Posts on Smartphones by Kate Keib, Bartosz W. Wojdynski, Camila Espina, Jennifer Malson, Brittany Jefferson and Yen-I Lee in Communication Research

Footnotes

Declaration of Conflicting Interests

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

Funding

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

ORCID iD

Kate Keib

Bartosz W. Wojdynski

Supplemental Material

Supplemental material for this article is available online.

Author Biographies

Kate Keib is an assistant professor at Oglethorpe University in Atlanta. Her research focuses on the intersection between social media, Public Relations and news dissemination. Her work has been presented at national and international conferences, and has received three Top Paper awards from the Association for Education in Journalism and Mass Communication (AEJMC). Keib spent 15 years in television news and marketing, working to help audiences engage with content online and on air. Keib earned her PhD at Grady College of Journalism & Mass Communication at the University of Georgia and Master’s Degree at Point Park University in Pittsburgh, Pennsylvania.

Bartosz W. Wojdynski is Jim Kennedy professor of New Media and Director of the Digital Media Attention and Cognition (DMAC) Lab at the University of Georgia. His research measures the influence of digital message design on users’ visual attention and the consequent effects of visual attention on psychological outcomes, with particular emphases in the areas of digital news and advertising.

Camila Espina (PhD, University of Georgia) is a social research scientist in the Structures Group of the Materials and Structural Systems Division (MSSD) of the Engineering Laboratory (EL) at the National Institute of Standards and Technology (NIST). She is currently part of the NIST Hurricane Maria Program, specifically working on the National Construction Safety Team (NCST) project characterizing the performance of critical facilities, such as hospitals, schools and shelters. Her research interests include media effects, risk communication effectiveness, and social media use before, during and after disasters.

Jennifer Malson (PhD, University of Georgia) is a digital media scholar and educator. She has a bachelor’s degree in Advertising from the School of Journalism and Mass Communications at the University of Colorado, Boulder and a master’s degree in Marketing at the University of Colorado Denver Business School. Jennifer worked within these industries for over ten years, with a focus on digital media and marketing strategy, before moving on to earn her doctorate. Her research interests include digital media and society, platform governance, and algorithmic infrastructure. She has taught courses on technology and society, media industries, and website development.

Brittany Jefferson is a 4th year PhD student at the University of Georgia – Athens. Her research focuses on information processing, social influence and behavioral outcomes in the context of strategic and persuasive communication.

Yen-I Lee (PhD, University of Georgia) is an Assistant Professor of Strategic Communication in the Edward R. Murrow College of Communication at Washington State University. Her primary research is in the areas of health communication and strategic communication, focusing on the role of messaging content, technology use, visual attention, and emotions in the context of health crisis and risk communication.

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