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Social Media

Jesse Fox, Ohio State University, USA

Bree McEwan, DePaul University, USA

Citation:

Fox, J., & McEwan, B. (2019). Social media. In M. B. Oliver, A. Raney, & J. Bryant (Eds.),

Media effects: Advances in theory and research (4th ed.). New York, NY: Routledge.

Order the book here: https://www.crcpress.com/Media-Effects-Advances-in-Theory-and-

Research/Oliver-Raney-Bryant/p/book/9781138590229

Introduction

Although the term social media was not commonly adopted until the 2000s,

masspersonal communication channels have existed since the advent of networked digital

communication. Many outlets have emerged for people to interact online, including bulletin

board systems (BBSs), newsgroups, multi-user dungeons (MUDs), social networking sites, and

massively multiplayer online games.

Given the impossibility of representing the entire scope of social media research in one

chapter, we focus largely on research representing notable distinctions from other computer-

mediated communication (CMC) research due to affordances. Affordances are inherent

functional attributes of an object that emerge when a user interacts with it (Gibson, 1979).

Recent work has specified important social media affordances (Rice et al., 2017; Treem &

Leonardi, 2013) and clarified differences in perceptions of affordances across social media and

other channels (Fox & McEwan, 2017).

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This review will first discuss conceptualizing social media. Next, we identify notable

affordances and elaborate popular types and uses of social media. Then we review focal research

areas. After identifying limitations of extant research and providing goals for scholarship, we

conclude by considering the future of social media.

Conceptualizing Social Media

One of the greatest challenges in reviewing research on social media is establishing scope

and boundary conditions, given a long history of loose conceptualization. As Web 2.0

development exploded, companies and popular media were quick to label any internet-based

technologies facilitating interpersonal interaction as “social media.” Although such a broad

conceptualization offered limited utility to scholars, definitions emerging in the concurrent

research literature were rarely any clearer (see Carr & Hayes, 2015, for a review).

One issue is scholars have often derived conceptualizations from currently popular

technologies (Carr & Hayes, 2015). Further, they may be based on dominant user practices

reflecting a relatively homogeneous group of users, particularly in early phases of a technology’s

diffusion and adoption. One example is the concept of social networking sites (SNSs), a subset

of social media defined by Donath and boyd (2004) as “online environments in which people

create a self-descriptive profile and then make links to other people they know on the site,

creating a network of personal connections” (p. 12). boyd and Ellison (2007) later rejected the

term “social networking site” in favor of “social network site,” based on data indicating people’s

Facebook networks reflected existing offline networks and forging new relationships was not a

primary goal (Ellison, Steinfield, & Lampe, 2007). Beer (2008) cautioned against rebranding, but

scholars widely adopted the modified term even though contemporaneous research found SNSs

were commonly used to expand networks (e.g., Grasmuck, Martin, & Zhao, 2009).

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As this example illustrates, technology researchers face an ongoing struggle: Sound

scholarship demands consistent, clear, and valid conceptualizations, yet scholars examining

rapidly evolving technologies must aim at blurry, constantly moving targets. Scholars are not

fortune tellers, yet they must attempt to both encompass the current state of a technology and

predict how it may evolve in the future. Otherwise, conceptualizations constantly shift and

related theorizing is tenuous at best; irrelevance and obsolescence is a perpetual threat.

Carr and Hayes (2015) made an admirable attempt to synthesize definitions and establish

parameters, defining social media as “internet-based, disentrained, and persistent channels of

masspersonal communication facilitating perceptions of interactions among users, deriving value

primarily from user-generated content” (p. 49). They further clarified social media “allow users

to opportunistically interact and selectively self-present, either in real-time or asynchronously”

(p. 50). This definition presents some strengths in conceptualization, such as defining social

media as masspersonal, meaning they have the capacity to deliver personalized messages to a

broad audience (O’Sullivan & Carr, 2018). Other elements of this definition present some

unclear constraints such as how the value of user-generated content is established and whether

social media require interactions between human users.

Given the ambiguity, we have not adopted a specific definition for this review. Rather,

we adopt an affordance-based approach to delineate what will be considered social media.

Although Carr and Hayes (2015) critiqued affordance-based conceptualizations of social media,

the definitions they provide explicitly cite affordances (synchronicity and channel persistence,

related to accessibility) and imply others (disentrainment indicates conversational control,

whereas selective self-presentation suggests editability). Further, a recent conceptualization of

masspersonal communication is founded on affordances (O’Sullivan & Carr, 2018).

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Universal Affordances of Social Media

Specific affordances are required to differentiate social media from other channels:

interactivity, accessibility, visibility, and personalization. Social media provide at least two

layers of interactivity: interacting with a responsive mediated system and interacting socially

with other users (Sundar, 2007). Users must be able to manipulate a responsive interface and

generate some form of socially relevant content. Further, this system must facilitate interactivity

among users through some modality, such as exchanging text-based messages or images,

speaking through an audio channel, or communicating via avatars. Users may also generate

system cues, such as page views or aggregated “likes,” that communicate information to other

users (Walther & Jang, 2012). Thus, social media often provide multiple ways of achieving

social interactivity through both user-generated and system-generated content.

Another key affordance is accessibility, or the capability of using a channel regardless of

time, place, structural limitations, or other constraints (Culnan & Markus, 1987; Fox & McEwan,

2017). Social media maintain a certain level of accessibility due to their continual availability, as

sites continue to function regardless of any individual user’s participation (Carr & Hayes, 2015).

Digital divides based on factors such as age, socioeconomic status, and education still exist in

regards to internet access and social media adoption (e.g., Hargittai, in press).

Given their masspersonal nature, social media must also enable visibility of social

interactions to a wide audience (Treem & Leonardi, 2013), which may or may not align with the

imagined audience users anticipate when posting (Marwick & boyd, 2011). Many platforms offer

privacy settings to allow users some control over who can see their content. Because digital

content is transmitted and replicated easily, however, a message can be spread through shares,

reposts, and retweets to a wide, sometimes unintended, audience with little effort. Because of this

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scalability, messages can become viral, meaning they are widely dispersed by users across vast

audiences, sometimes reaching millions of users almost instantly (Marwick & Lewis, 2017).

Despite the potentially broad audience, another requisite affordance of social media as a

masspersonal channel is that users can personalize messages (O’Sullivan & Carr, 2018). Users

can tailor their message or direct it to a smaller segment of the audience.

Aside from these universal affordances, other affordances vary considerably across social

media and are used to distinguish different types or explain discrepancies in uses or effects.

Articulating these affordances allows scholars to perform a nuanced evaluation of social media,

distinguish them from other communication channels, and inform theorizing.

Other Social Media Affordances

Perhaps the most commonly examined affordance is anonymity or identifiability, the

degree to which users’ real names or true identities can be concealed in a channel (Lea & Spears,

1991). Anonymity has been central to theorizing on online disinhibition, in which people engage

in less socially normative behavior online (e.g., social identity model of deindividuation effects,

Lea & Spears, 1991). Even if users try to maintain anonymity, they often leak cues to their

identity through profile information, network members, geolocated content, or “likes” (see Shu,

Wang, Tang, Zafarani, & Liu, 2017, for a review).

Some affordances shape how interactions transpire via social media. Sites vary in

synchronicity, or the timing of message exchange (Culnan & Markus, 1987). Conversational

control involves managing the mechanics of an interaction, such as regulating turn-taking or

ending a dialogue (Fox & McEwan, 2017). For example, a system may limit how many times a

user can respond to a post, or users may be able to “mute” or “block” others’ comments.

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Other affordances determine the nature of messages and content. Bandwidth is the scope

of verbal and nonverbal cues that can be conveyed through various modalities, such as text,

graphics, audio, or video (Walther & Parks, 2002). Limited bandwidth and asynchronicity

facilitate editability, or the capacity to revise messages (Walther, 1996). The digital materiality

of social media messages affords easy modification. This materiality also makes messages easily

replicated and transmitted, facilitating the persistence of messages (Treem & Leonardi, 2013).

Although users may be able to delete messages, these can also be shared, downloaded, or stored,

and so may remain long after the original transmission.

Finally, network association enables users to visibly link to other users, creating a

traceable network of connections. Through common nodes or “friends,” users can identify other

network members and often access their content (boyd & Ellison, 2007; Treem & Leonardi,

2013), creating networks of strong, weak, and latent ties (Haythornthwaite, 2005). Network

association facilitates context collapse, which is experienced when social circles normally

maintained separately (such as a person’s co-workers, their former classmates, and their

extended family) are blended in a shared environment (Marwick & boyd, 2011).

Types and Uses of Social Media

Several types of social media have emerged, although individual platforms or groups may

fall into multiple categories. The primary functions of social media are interacting with others

and sharing information; other uses and gratifications vary across sites (McEwan, 2015). Some

of the earliest social media research focused on bulletin board systems, online forums, and online

communities (e.g., Jones, 1995; Rheingold, 1993; Wellman & Hampton, 1999). Discussion

forums may be organized around topics (e.g., Reddit, 4chan) or specific content (e.g., comment

sections on news articles). Some forums may be considered online communities, which are

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characterized by aggregates of individuals who share a common feature or interest (McEwan,

2015). Online community members engage in social goals such as forming relationships,

building a collective culture, and creating, negotiating, and sharing group norms (Baym, 2010).

Among the most common social media are social networking sites (SNSs) such as

Facebook, Twitter, Instagram, and LinkedIn, preceded by sites such as Friendster, MySpace,

Hyves, and Orkut. SNSs are characterized by the abilities to create a profile, link to other users,

and observe how other users are connected within the broader network sustain a profile via the

affordance of network association (boyd & Ellison, 2007). Thus, establishing social connections,

maintaining relationships, and building networks are common uses of SNSs.

Some social media are characterized by richer environments and tasks beyond socializing

and exchanging information. Social virtual worlds (e.g., Second Life and VRChat), open

sandbox platforms (e.g., Roblox), and massively multiplayer online games (e.g., Fortnite)

typically enable richer forms of self-representation such as customizable avatars (Yee, 2014) and

near synchronous communication via text chat, voice chat, or avatar interactions. Given their

diversity of tasks, other common uses for these sites include collaboration, competition,

achievement, discovery, role-playing, and escapism (Yee, 2014).

Content-based social media sites often constitute participatory cultures, as these sites are

designed primarily to share, consume, and interact with material created or curated by the user

(e.g., Pinterest, Tumblr, YouTube, Twitch, blogging communities, wikis; Jenkins, 2006). Other

types of social media are distinguished by affordances, such as locative social media designed to

track and report users’ movements to other users (e.g., FourSquare, Dodgeball; Humphreys,

2007) and anonymous sites designed to elicit disinhibited disclosures (e.g., Whisper, Yik Yak,

Formspring). Other types of social media are likely to emerge with future technologies.

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Areas of Social Media Research and Theorizing

Social media can influence human communication processes in three ways. First, social

media may simply accommodate the manifestation of communication phenomena without

changing the communication process. Existing theories do not require additional clarification

because the channel does not have a notable impact. For example, Carpenter and Spottswood

(2013) observed that self-expansion effects previously studied in offline interactions between

romantic partners can also occur via Facebook. Second, social media may amplify observed

communication processes by expediting, expanding, or enhancing phenomena compared to other

channels. For example, social media allow activists to organize collective action more efficiently

than other channels (Tufecki, 2017). Regarding amplification, existing theories may increase

their explanatory power by assessing relevant social media affordances, but they do not require

major revisions. Finally, social media may alter communication processes in fundamentally

different ways. For example, according to social penetration theory, if two strangers meet face-

to-face, they would have to engage in ongoing self-disclosure to get to know each other. On an

SNS like Facebook, however, they may have access to considerable information about each other

in terms of breadth (tastes, friends, opinions) and possibly depth, perhaps without ever

interacting. When social media alter processes, theories must be revised or new theories must be

developed. In this review, we will largely focus on research examining amplification and

alteration via social media.

Self-Presentation, Impression Management, and Identity Performance

Social media have altered how identities are performed online, but sites are not

equivalent in their effects on identity performance. Affordances like asynchronicity and

editability enable users to engage in selective self-presentation and more diligent impression

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management (Walther, 1996). Anonymous spaces can grant more flexibility in the identities

people can present (McEwan, 2015; Turkle, 1984). These affordances are valuable for people

who experience marginalization offline (McKenna & Bargh, 1999). Yet, network association can

complicate identity performance; due to context collapse, members of one social audience

segment may see identity performances meant for another audience (Marwick & boyd, 2011).

McEwan (2015) proposed considering social media spaces along a fixed-flexible

continuum contingent on the access of particular types of network members. Fixedness or

flexibility is based on varying degrees of corporality, anonymity, and persistence. Flexible

spaces are divorced from stable connections between network members, including a separation

from one’s online communication and a corporeal self (i.e., unanchored relationships). Within

these spaces participants can engage in identity experimentation (e.g., Livingstone, 2008;

Valkenberg, Schouten, & Peter, 2005) or even present as multiple identities (Turkle, 1984).

Within fixed network spaces, users’ performed identities must be coherent and consistent for at

least one potential social audience and often for multiple audience contexts (e.g., Stutzman,

Gross, & Acquisiti, 2013). People may manage fixidity by maintaining different profiles with

different audiences. Alternatively, they may attempt to present an identity appropriate for

multiple audience segments (Hogan, 2010).

Fixidity is also influenced by visible feedback offered by other users. According to

warranting theory, because online self-presentation can be more easily manipulated by the

source, users seek out and evaluate cues to assess the veracity of this self-presentation (Walther

& Parks, 2002). The less a cue can be manipulated by the source, the more value and weight it

has to the user (DeAndrea, 2014). On social media, people trust friends’ comments about a

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person more than the person’s self-presentation (Walther, Van Der Heide, Hamel, & Shulman,

2009). In this way, identity performance is constrained by affordances and audience members.

Disclosure and Privacy

Self-disclosure and privacy have been a popular focus for social media research

(Stoycheff, Liu, Wiwobo, & Nanni, 2017). Several concepts have been clarified through research

focused on social media, such as context collapse, the imagined audience, and the privacy

paradox, which describes the inconsistency between users’ privacy concerns and their behaviors

(Barnes, 2006; Marwick & boyd, 2011). The masspersonal nature of social media further

complicates privacy management and what is perceived as acceptable self-disclosure.

To examine this, Bazarova (2012) adopted a disclosure personalism framework to

examine perceptions of intimate and nonintimate messages shared on Facebook. Comparing

masspersonal, public Facebook posts and private interpersonal Facebook messaging, Bazarova

found people judged senders and their intimate disclosures more negatively in masspersonal

contexts. Examining senders, Bazarova and Choi (2014) extended existing theorizing to a

functional model of SNS disclosure, which argues senders’ impression management concerns are

amplified by SNS affordances such as visibility and personalization.

Relationship Development and Maintenance

Within existing relationships, a social media site may become an additional channel

through which to communicate, contributing to media multiplexity (Haythornthwaite, 2005).

Social media may also facilitate new relationships (Parks & Floyd, 1996; Utz, 2000). Some sites

enable people to connect over shared interests or content, which can minimize factors that may

have prevented a relationship from developing otherwise, such as geographical distance or

demographic dissimilarities (Baym, 2010; McKenna & Bargh, 1999; Parks & Floyd, 1996). In

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addition to social interaction, users may engage in shared tasks (e.g., game activities, content

moderation) to maintain relationships (Baym, 2010; Ledbetter & Kuznekoff, 2012; Yee, 2014).

SNSs have been a major focus for relational maintenance research. SNSs greatly increase

the number of weak ties maintained by users (Donath & boyd, 2004) and can help solidify

emerging relationships (Ellison et al., 2007). The SNS affordance of network association may

also help people maintain not just direct connections, but also connections between those whom

we see connected to our connections (Ellison, Vitak, Gray, & Lampe, 2014).

People can use SNSs to enact traditional maintenance strategies (Bryant & Marmo, 2009)

as well as site-specific strategies (e.g. McEwan, Fletcher, Eden, & Sumner 2014). For example,

messages directed to specific others indicating social contact and relational assurances are

correlated with satisfaction, liking, and commitment in friendships. Yet, messages seeking

comfort from a general audience are negatively related to these outcomes (McEwan, 2013).

Social Capital, Social Resources, and Social Support

Social capital refers to the value imbued within an individual due to their representation

of other, potentially powerful, network connections (Bourdieu, 1986). Bonding social capital is

associated with close network relationships, and bridging social capital is produced through the

accumulation of weaker ties. Maintained social capital can sometimes be converted into

resources. Through building capital-rich networks, social media users may later be able to

request instrumental and social resources from their network connections. Research has shown

SNSs like Facebook can help users develop bridging social capital and attain resources (e.g.,

Ellison et al., 2007; Ellison et al., 2014).

One such resource is social support, which is commonly obtained through SNSs and

online support groups (e.g., Wright, 2000). Informational and emotional support are easily

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conveyed online, although tangible support can be more difficult (Mikal, Rice, Abeyta, &

DeVilbiss, 2013). Affordances affect support seeking and provision. Accessibility is key, as

users can obtain support any time; further, they may be able to identify support providers they do

not have access to offline, such as other people with a similar condition (Rains, 2018).

Anonymity may facilitate more disclosure and help-seeking, particularly for those with

stigmatized conditions (Mikal et al., 2013). The visibility of others’ supportive messages on

social media leads users to create higher quality support messages (Li & Feng, 2015).

Seeking support and resources through social media may not always be effective. Some

research has indicated people must be actively engaged with network members to have resource

requests fulfilled (Ellison et al., 2014). In some cases, masspersonal support requests may be

judged negatively by weak tie connections (High, Oeldorf-Hirsch, & Bellur, 2014).

Psychological Well-Being and Health Communication

An evergreen topic for researchers has been the effects of social media use on well-being,

which have been associated with individual traits, consumed content, and the nature of use.

Evidence has been found to support both the social compensation hypothesis (“poor-get-richer,”

in which those lacking offline have needs met online) and social enhancement hypothesis (“rich-

get-richer,” in which those who already have support or resources offline also benefit online;

Seabrook, Kern, & Rickard, 2016). Evidence suggests it is the nature of the communication that

matters. Similar to other channels, positive and supportive interactions are associated with

positive well-being, whereas negative interactions and social comparisons are associated with

depression, loneliness, and anxiety (Seabrook et al., 2016). Excessive use (i.e., “addiction”) has

been associated with negative well-being, although more nuanced findings suggest these are

likely co-occurring outcomes attributable to individual differences (Seabrook et al., 2016), and

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problematic or maladaptive use (e.g., surveillance of one’s ex-partner or disruptive multitasking)

should be examined more specifically (see Caplan, 2018).

Extremely negative interactions, such as cyberbullying and online harassment (e.g.,

trolling) have shown consistent associations with negative outcomes and may be amplified by

online affordances (Fox & Tang, 2017; Tokunaga, 2010). For example, doxing and revenge porn

involve disclosing a target’s private information without their consent (Marwick & Lewis, 2017).

Although these breaches would also be violating offline, the visibility, scalability, persistence,

and searchability of this information online may make these experiences especially pernicious.

Unfortunately, few studies have compared channels or assessed affordances to determine

whether social media are augmenting effects on mental health. Establishing causality can also be

difficult. One notable experiment manipulated interactivity on Facebook, finding passive

browsing, compared to actively communicating with others, caused a drop in affective well-

being over time. A follow-up field study using experience sampling further clarified passive

browsing was associated with greater feelings of envy, possibly due to social comparison with

one’s ties (Verduyn et al., 2015). A controversial experiment conducted by Facebook tested

network effects by manipulating the visibility of positive or negative emotional posts in users’

newsfeeds and analyzing their subsequent posts. Seeing more positive posts increased users’

positive posts and reduced negative posts whereas seeing more negative posts had the opposite

result, indicating an emotional contagion effect (Kramer, Guillory, & Hancock, 2014).

Other health-related research has investigated information seeking, support seeking, and

patient-provider communication through social media (see Rains, 2018, for a review). Despite

the apparent advantages of SNSs for health interventions, randomized controlled trials have

yielded minimal effects, similar to other media (Yang, 2017). One novel use of social media in

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the health context has been the tracking of outbreaks (e.g., flu, food poisoning) through SNS

posts and networks (see Charles-Smith et al., 2017, for a review).

Information Diffusion and Evaluation

The convergence of established mass media, online news, and interpersonal sources

within and across social media create information flows that can be difficult for the average user

to evaluate. The source of the message can become ambiguous (Flanagin, 2017). Methods of

curation and censorship by sites (e.g., algorithms, filters, content moderators) and users can

further cloud the veracity and comprehensiveness of presented information (Flanagin, 2017).

Regardless of accuracy, the scalability of social media messages enables murky sources or

misinformation to circulate far and wide (Marwick & Lewis, 2017).

For these reasons, the credibility of information shared via social media is often

questioned. Only three percent of U.S. Americans claim to have a lot of trust in information they

find via social media (Smith & Anderson, 2018). Research indicates, however, users are more

likely to trust digital misinformation shared by friends (Garrett, 2011), and friends’ endorsements

on social media affect news selection (Messing & Westwood, 2014). In this way, social media

may have distinct effects compared to misinformation from other online sources, as users may be

more likely to believe and propagate “fake news” when it is shared by a friend.

The differing affordances of social media sites may influence information diffusion.

Online communities may facilitate homogenous spaces where users can share like views that

become reinforced over time (Wojcieszak, 2010), whereas SNSs often facilitate large weak tie

networks which expose users to greater information diversity (Bakshy, Messing, & Adamic,

2015). Although nonanonymous SNSs like Facebook certainly are not free of incivility, political

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discussions on SNSs may feature more politeness than anonymous spaces like a YouTube

comments section (Halpern & Gibbs, 2013).

Political Communication and Collective Action

Social media research has indicated amplifying effects on political expression and

collective action, particularly given the linkages and rapid diffusion of information among ties on

social networking sites (e.g., Freelon, McIlwain, & Clark, 2016; Kreiss, 2016). The accessibility

of social media may promote greater political engagement (Papacharissi, 2002). SNS users may

feel more comfortable expressing themselves online and may reach more politically diverse

audiences than they would offline due to network association and scalability (Freelon et al.,

2016), which may also facilitate collective action more efficiently and on a greater scale than

traditional channels (Tufecki, 2017). These same affordances, however, may drive a spiral of

silence for marginalized users (Fox & Warber, 2015).

Another concern is that social media provide unprecedented tactics and power to political

operatives and corporations (Vaidhyanathan, 2018). Facebook demonstrated it could influence

voting behavior by manipulating the visibility of voting messages in users’ feeds (Bond et al.,

2012). Sock puppet accounts and bots can be used to disseminate misinformation, astroturf (i.e.,

disguise operatives’ efforts as grassroots movements), or instigate discord or further polarization

(Marwick & Lewis, 2017). A final concern is that the visibility and aggregation of social media

users’ activities generate considerable data that have been used by political parties, corporations,

and bad actors to identify, target, and silence dissidents; perpetuate misinformation and

propaganda; and influence political outcomes (Pearce & Kendzior, 2012; Vaidhyanathan, 2018).

Future Directions for Social Media Research

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In the relatively short history of social media research, a few consistent issues have

emerged. Here, we address some observed limitations in existing research, provide some goals

for researchers, and consider emerging social media platforms and their affordances.

Improving Social Media Research

Do your homework. First, social media scholars need to begin their investigations by

digging much deeper than recent social media research on their topic within their field. Lacking a

historical grounding, too often social media researchers commit a false novelty error, in which

they assume a phenomenon is unprecedented and attributable to social media. Often these

phenomena are not novel; rather, they illustrate amplifying effects of social media on existing

processes. If researchers do not conduct historical research across different disciplines, they may

assume trolling (social aggression and harassment), ghosting (relationship dissolution), and fake

news (rumors, gossip, and deceptive journalism) are new occurrences or unique to social media.

Recognizing how phenomena manifest outside of social media contexts is not just sound

empirical practice, it also challenges one-sided narratives in which social media are uniformly

heralded as saving humanity or blamed for destroying it.

Be patient. Social media researchers should not be baited by apparent novelty, media

frenzies, or technophilia; proceed diplomatically and assess similarities to and differences from

existing channels. Historical research may reveal patterns in how related technologies have been

perceived, used, adopted, or abandoned, which may give insight on the durability of an emerging

technology (Rogers, 1962). Another reason patience is advised is that technology users and

practices evolve over time. Initial users are likely to differ from other users in significant ways

(Humphreys, 2007; Rogers, 1962), limiting conclusions or theorizing based on early findings.

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Diversify. A third goal is to expand the populations, topics, and sites researchers study.

Due to growing internet access, social media audiences are diversifying globally. Various

cultural norms, governmental regulation or monitoring, and literacies influence social media use

(e.g., Pearce & Kendzior, 2012). Additionally, studies are often conducted with a single site

(often Facebook) and findings are erroneously generalized to all social media (Stoycheff et al.,

2017). Sites vary in the nature of their users and audiences, the features they offer, and their

affordances (e.g., Fox & McEwan, 2017). Finally, researchers should also seek out nonusers,

examining digital divides, group differences, and selective avoidance (e.g., Hargittai, in press).

Of particular concern is that individuals, particularly those from marginalized groups, may avoid

or quit using technologies due to negative social experiences (e.g., Fox & Tang, 2017).

Adopt an affordance-based approach. Researchers should account for structural and

perceived affordances when studying social media as they are important determinants of site

selection, use, communicative behaviors, and other effects. Clarifying the role of affordances

will help scholars better predict what findings generalize across sites or across channels more

generally, enabling more flexible and durable theorizing (Fox & McEwan, 2017).

Improve measurement. A fifth goal is to better operationalize social media behavior,

which may include updating one’s profile; creating or sharing content; viewing or interacting

with others’ content; or messaging another user in a private channel. Unfortunately, researchers

typically only assess time spent on sites. Many studies’ hypotheses, however, concern the type of

content participants are encountering and how much they are attending to, processing, and

interacting with such content. For example, a study examining the impact of cross-cutting

political discussions on Twitter needs to assess how much users notice, read, and engage with

such discussions, not how much time they spend watching cute chinchilla videos. Given there are

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considerable limitations to common techniques (e.g., self-report, automated tracking, experience

sampling, data scrapes; see de Vreese & Neijens, 2016), triangulation of methods is advised.

Researchers should also consider how social media fit within media repertoires as well as

within other social experiences (Stoycheff et al., 2017). Processes may be working in

conjunction, perhaps indicating additive effects. For example, women may receive consonant

messages reinforcing the importance of their physical appearance across traditional media, social

media content, and social interactions. In other cases, notable contradictions may emerge. For

example, individuals who cannot discuss their sexual orientation among known ties may express

themselves freely on unanchored social media (e.g., McKenna & Bargh, 1999).

Conduct ethical research. A final advisement is social media researchers must give

ongoing consideration to a number of ethical issues in our ever-evolving domain. The thirst for

easily accessible data—and perhaps envy of corporations’ stockpiles—does not obviate scholars’

ethical obligations to protect participants and maintain public trust in scientific research. Current

research practices beget two ethical questions: Should researchers use participants’ data without

explicit consent? Should they scrape and aggregate this data and share it freely on the internet?

Researchers must concede users’ outrage about Facebook’s many missteps (see

Vaidhyanathan, 2018) indicates many users are not happy about their data being used without

their awareness or approval. Specific to scientific study, Fiesler and Proferes (2018) surveyed a

sample of Twitter users and found over 60% were not aware researchers could use their tweets.

Nearly half indicated they would feel uncomfortable if their Twitter history was used for

research, and 65% said researchers should not be allowed to use tweets without asking

permission from the user. These findings indicate many users object to researchers taking their

data without informing them or obtaining consent.

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Researchers must also acknowledge that accumulating and aggregating social media data

inherently increases privacy risks to users. The process generates copies, links data in ways that

may be otherwise not easily discernible, and establishes persistence the user has no control over.

Even if a user deletes their account and all their posts, the researcher is now a curator taking

away the user’s “right to be forgotten” (Rosen, 2012). Aggregate datasets posted online are more

identifiable and create greater risk for participants than scholars may realize, given many forms

of social media data are searchable (e.g., the content of a tweet) and thus potentially identifiable

without names attached—not to mention algorithms already exist that are capable of linking data

across anonymous and nonanonymous sites and identifying users (Shu et al., 2017). Moreover,

scholars cannot anticipate how corporations, insurance companies, employers, law enforcement,

governments, or criminals may use this conveniently compiled data or link it to other records.

Perhaps the underlying issue here is the objectification of social media users: they—we—

are now seen as data points, not people. But what we do on social media sites is more than just

data or information or content. What we create and share through social media are our personal

histories, artistic expressions, memories, feelings, conversations, and secrets. Collectively, these

artifacts constitute a digital self that people want to share with others socially, but they may

object to having placed under a microscope. Social media scholars should consider these ethical

issues carefully in the design, conduct, and reporting of their studies and associated data.

Emerging and Evolving Social Media Platforms

Although it is difficult to determine how emerging forms of social media will manifest

and whether they will endure, some recent social media have provided distinct features or

combinations of affordances. In recent years, for example, Twitch has become an immensely

successful global platform by merging video livestreaming and text-based chat. Streamers can

SOCIAL MEDIA 20

create profiles and broadcast live video to an interactive audience. Although research is emerging

on Twitch (e.g., Taylor, 2018), theorizing has yet to tackle the confluence of one-to-many mass

communication (the streamer broadcasting), many-to-many computer-mediated group

communication (text-based chat among audience members), and one-to-one or many-to-one

computer-mediated interpersonal communication (audience members addressing the streamer).

Social virtual environments such as massively multiplayer online video games (MMOs),

3D virtual worlds, and collaborative virtual reality have grown in popularity. They are often

overlooked within the scope of social media, but by many definitions, these environments

qualify and provide distinct affordances. For example, embodiment is often afforded through the

use of a responsive avatar controlled by keypresses or body movements. In fully immersive

virtual environments, users can move their bodies in natural ways and their avatar responds

accordingly. This mapping may have distinct effects for mediated social interaction compared to

communicating through less natural methods, such as keypresses.

Another crucial consideration for social media researchers will be to account for the

growing influence of computer-generated content, algorithms, and agents (i.e., computer

controlled entities, such as bots and nonplayable characters) in social media spheres. Already,

users may find themselves engaging in Turing tests to determine whether they are interacting

with a human or a computer. As agents become more sophisticated, however, it may be more

difficult to identify when they are masquerading as human users. When senders and receivers are

no longer human or predominantly human-controlled, the applicability of existing

communication theories will have to be reconsidered.

In conclusion, social media have become an integral communication channel for many

people, providing a conduit for interaction, but also amplifying and altering communication

SOCIAL MEDIA 21

processes. As social media and their users continue to evolve, researchers face an ongoing

challenge of keeping pace with changing practices and a changing society.

SOCIAL MEDIA 22

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