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date: 26 July 2017

Technologized Interaction

Summary and Keywords

As the use of online technologies has grown in recent years, so has the study of computer-mediated communication.

Online communication began in universities through the use of e-mail. Soon, spaces such as multi-user dungeons (MUDs), Listserv, and bulletin boards were developed, which not only allowed people who knew each other offline to interact but also enabled individuals who were not previously acquainted to communicate via the Internet. The development of Web 2.0, which allowed for more user-generated content, led to new and innovative ways of interacting online, most notably thorough social media sites. Social media sites, such as Facebook and Twitter, allow not only for text-based interaction to occur but also for image- and video-based interaction.

Through all these developments, interactional norms and practices have developed. A key factor in these norms is what the medium enables, or affords, participants to do. Features such as whether an interactional platform is synchronous or asynchronous can impact the nature of the interaction. Similarly, the lack of visual or verbal contact when interacting may impact upon the interaction, through the potential for misunderstandings. Participants do, though, develop practices to suit the medium. If we examine these practices in detail, it is possible to also analyze the role which technology plays in the interaction. One method that has been used to do this is conversation analysis, which was developed for and using spoken interaction. Conversation analysis examines conversation in forensic detail to illuminate the norms and practices through which we conduct our everyday lives. In using this method for analyzing online interaction, we can not only understand the practices but also examine the affordances of particular interactional platforms.

Various interactional features of computer-mediated communication (CMC) have been examined from a conversation analytic perspective, including sequential organization, openings, turn-taking, and repair. A common focus of these studies it to explore the interactional patterns but also to understand how these might be impacted by the technology itself. The development of norms for a variety of forms of technologized interaction demonstrates how individuals are capable of adapting their interactional practices for new contexts.

Keywords: online communication, computer-mediated communication, affordances, conversation analysis technology

An Interactional Approach to Technology

The development of technology used for communication can be dated back to the early 1840s when the telegraph was first invented. Technologies have advanced since then in numerous ways, with notable developments including the telephone, wireless radio, television, and, of course, the computer (Winston, 1998; see also Burns, 2004, for a more detailed history). A common denominator of these technologies is that they allow individuals or groups to interact even when they are geographically distant. The most recent development has been the rise of computer-mediated communication (CMC). The Internet was first developed for both academic and military purposes in the 1970s (Winston, 1998), with e-mail being used in a number of universities by 1983. The Internet as we now know it has its origins in the 1990s, when Tim Berners-Lee created the world wide web. There is a commonly noted divide between Web 1.0, where pages were mostly static and tended to be created by companies, and Web 2.0, where content on the Internet became more user-generated (O’Reilly, 2007). However, it has been argued that this distinction may well be blurred, as even from the beginning the content of the Internet was “user-generated” (Baym, 2011); for example, even in Web 1.0, there were newsgroups, e-mails, bulletin boards, and MUDs (multi-user dungeons—a multi-player virtual world, based on written interaction). However, with Web 2.0, sites for CMC grew, including chat rooms, online forums, massively multi-player online role-playing games (MMORPG), instant messaging, and social networking sites (SNS), such as Facebook, Twitter, mySpace, and Bebo. More recently, we have seen the rise of multi-modal means of communication, including SnapChat, YouTube, Instagram and so on.

This range of platforms for interacting has, unsurprisingly, attracted academic attention. There was, though, a lack of major academic studies on the language of the Internet until the late 1990s (Baron, 2011). Within the field of linguistics, the focus was on whether online language could be seen as a completely new form of communication (Crystal, 2001). It was suggested that the written language that developed online was a new register of language that was distinct from both spoken and written language (Ferrara, Brunner, & Whittemore, 1991). This form of language was known as “netspeak” and was characterized by abbreviations, emoticons, and non-standard spellings (Crystal, 2001; Herring, 2007). It was argued, though, that this “netspeak” was more like writing, with very limited features in common with speech (Crystal, 2001). Further study focused on whether this online language was starting to influence offline language, both written and spoken (Baron, 2011).

One challenge for studies of CMC is that as much as the Internet is heterogeneous, so is the language used on the Internet. Even studying interaction on one platform can be challenging. For example, e-mail is one of the earliest forms of technologized interaction. However, it is used very differently across different contexts, such as in the workplace, or in more informal contexts, such as between friends (Bou-Franch, 2011). As there is such a wide range of different modes of communication, it is important when studying online communication to explore how the technology itself can impact upon the interaction.

There are two main approaches to the role of technology in interaction, which can be broadly described as technological determinism and social constructivism. Technological determinism suggests that “forms of technology actively cause new forms of social relations to come about” (Hutchby, 2001, p. 15). Social constructivism, on the other hand, suggests that no technology has any particular features that lead to particular social consequences. Instead, it is how the technology is utilized, or interpreted, that leads to it having certain social properties. In this article, the approach taken to technologized interaction draws on the work of Hutchby (2001). Hutchby uses Gibson’s (1979) concept of “affordances,” which was based in cognitive psychology, to suggest a way of approaching technologized interaction that stood somewhere between determinism and constructivism. Gibson’s concept of affordances suggested that any object (not just technology) could be perceived in different ways by different observers. However, any object has particular qualities that may affect the way in which that object can be perceived or interpreted by any observer. For example, a napkin might be used by an observer for many things: to wipe their mouth, to blow their noise, to write their phone number on, to remove makeup, and so on, but its particular properties mean that if, for example, you needed to put fuel in your car, a napkin would not do the job. One point, of course, is that while there are perhaps immediate uses that we, as an observer, could perceive for a napkin, there are also particular social conventions for how the napkin could be used. For example, it would be plausible to use a napkin as an item of clothing. However, social convention would suggest that walking around mostly naked with only a napkin on is not an appropriate use of that item. So an affordance of any object may be a part of its particular physical properties, but there are also affordances based on social norms and rules (Gibson, 1979).

Hutchby (2001) applies this concept of affordances to technology and argues that there are particular technological features that are physical properties of any piece of technology. However, in contrast to technological determinism, Hutchby does not suggest that these particular physical properties lead human actors to behave in a certain way. Instead, these features both afford and constrain the interactional potential (Hutchby, 2001). Therefore, we can analyze online interaction with reference to how the users of the technology find ways of interacting while managing the particular affordances of that technology. However, although the affordances might constrain the interaction in certain ways, “not everything done or not done with an object is related to its material properties” (Rintel, 2013, p. 3344). In other words, instead of presuming that any particular affordance necessarily enables or constrains any particular action, the interaction itself should be examined to see how the participants manage their interactional environment and how they potentially adapt or create new social practices that implicitly or explicitly orient to the affordances and constraints of the technology (Rintel, 2013).

The approach of examining the interaction itself lends itself readily to conversation analysis (CA). CA is an approach to language that focuses on analyzing the ways in which talk is produced in naturally occurring interactional environments (Sacks, 1992; Sidnell, 2010). CA aims to “describe, analyse and understand talk as a basic and constitutive feature of human social life” (Sidnell, 2010, p. 1). It seeks to address how speakers maintain intersubjectivity—or a joint or shared understanding—through interaction (Sidnell, 2010). In talk-in-interaction, any utterance occurs in a particular interactional context; it is responsive to a previous turn, and it creates the interactional context for the subsequent turn (Goodwin & Heritage, 1990). In CA the interactional context does not revolve around “topic” but instead around action; in other words, the interest is in what a turn is doing rather than what it is about (Schegloff, 2002). For example, a particular turn might be an invitation to go for a drink. This particular turn is, on the face of it, about a drink, but it is also an invitation. It subsequently sets up a context in which the next turn will be a response to the invitation, not necessarily a discussion about drinking. So in any particular turn, the recipient will be monitoring the turn and analyzing it for what action the speaker is doing with their turn (Schegloff, 2002). CA, therefore, focuses on what the participants themselves orient to in their talk, rather than the analyst’s orientations.

Hutchby (2001) argues that CA is particularly useful for studies of technologized interaction, as its focus is on how talk in any particular setting might orient to that setting through the actions of the participants. This talk can be seen as demonstrating the underlying social organization, not in the sense that it drives participants’ actions but rather that through examining talk-in-interaction, we can see how participants orient to those underlying norms, practices, and social organization. In terms of technologized interaction, we can examine participants’ talk to explore how it orients to the particular technological setting in which that interaction is occurring.

This article focuses on the conversation analytic approach to technologized interaction. The aim is to explore the findings from studies of CMC that have utilized CA-informed methods of analysis. Subsequent sections will address findings in relation to the openings of online interaction; how coherence is maintained online; turn-taking in technologized interaction; how participants deal with “trouble” online; and finally, gaze, gesture, and body language in online interaction. The next section, though, will discuss how interactional platforms can be classified according to their particular technological affordances.

Classifying the Technology of Interaction

As discussed in the previous section, a wide variety of platforms are used for technologized interaction, from social media sites, such as Facebook and Twitter, to more personalized interactional contexts, such as instant messaging or WhatsApp. These technologies have changed over time, with new platforms being developed (e.g., Twitter) and others waning in popularity (e.g., MySpace). The technological features of the medium that may impact the nature of the interaction can be classified in various ways.

First, we can classify whether a platform allows for written or spoken interaction or for both (Herring, 2007). Some platforms, such as Skype (see Figure 1), allow for both video and written instant messaging. Other platforms, such as the majority of online forums and e-mail, only allow for written interaction.

Technologized InteractionClick to view larger

Figure 1. Skype video-messaging.

Online platforms can also be classified according to the number of channels or sources of communication (Herring, 2007). Video communication provides participants with information through multiple channels, auditory and visual, and so is particularly rich. Websites that allow both text and image-based interaction, such as Instagram, Facebook, or Twitter, are less rich than video communication but provide for more channels of communication than purely text-based interaction. Text-based interaction is, arguably, the least “rich” form of interaction, as it only makes available one source of information. In text-based interaction, parties do not have access to the visual and verbal cues that would accompany spoken interaction. The lack of cues does not, though, mean that people cannot express themselves using text, with users finding a number of ways to express themselves, including the use of emoticons, punctuation, abbreviations, and acronyms (Walther, 1996).

In addition to the number of channels and basic medium variables, we can also classify online interaction according to the level of synchronicity (Herring, 2007). Asynchronous interaction allows users to interact even if they are not online at the same time. Messages are stored at a particular site or server, and users can view these messages whenever they log in. Asynchronous interaction is, perhaps, predominant in online interaction, with examples including e-mail, Twitter, Facebook, and YouTube, among others (see Figure 2). The opposite of asynchronous interaction is synchronous interaction, where users have to be online at the same time in order to interact. Examples of this type of interaction include Internet Relay Chat (IRC), instant messaging systems such as MSN messenger, and of course video messaging.

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Figure 2. Facebook instant messenger.

It is sometimes argued that interactions on IRC or instant messaging could be more accurately termed quasi-synchronous interaction (Garcia & Jacobs, 1999). These types of interaction could be called quasi-synchronous because, although the parties are online at the same time, the interaction is not actually synchronous because the process of message transmission, that is, writing the message, is not synchronous with the process of message construction, or sending the message.

However, this asynchronicity of message transmission and construction can be accounted for via another classification; that is, whether it is a one-way or two-way transmission (Cherny, 1999). One-way transmission is where the message construction and transmission are not synchronous and the message is written “privately” and then transmitted in its entirety to the recipient(s). The alternative is two-way transmission, where all parties to the interaction can see the message as it is being produced. Two-way transmission is most obvious in video messaging, such as Skype or FaceTime. However, there are also examples of text-based interactional platforms that allow for two-way transmission (Anderson, Beard, & Walther, 2010), although these are rare.

Table 1. Classification of Online Affordances

Medium

Number of channels

Synchronicity

Type of transmission

Written

Video

Asynchronous

One-way

Spoken

Images

Synchronous

Two-way

Both

Text

(Quasi-synchronous)

Voice

These basic classifications, which are summarized in Table 1, allow us to describe the technology of an interactional platform based on the medium, number of channels, level of synchronicity, and type of message transmission.

Opening Sequences in Online Interaction

The start of any interaction, either face to face or online, is important for a variety of reasons. The opening sequence firstly tells us something about the nature of the interaction (Schegloff, 1986), for example, if it is an “institutional” conversation (Heritage, 2005), such as an interaction between a doctor and a patient, or if it is more mundane, like a conversation between friends. The opening of an interaction also tells us something about the relationships between participants (Schegloff, 1986). There has been a lot of work conducted on the opening sequences of landline telephone calls (e.g., Schegloff, 1968, 1979, 1986). It has been found that four possible sequences need to be accomplished before the interaction can proceed (Schegloff, 1986). These sequences are: (1) the summons-answer, which alerts the intended recipient to the fact that someone wants to interact with them and tells the summoner that their intended interlocutor is available; (2) identification and recognition of speakers; (3) greetings; and (4) initial inquiries, such as “how are you?” We can see how these sequences clearly orient to the interactional context of speaking on the telephone (Hutchby & Barnett, 2005). For example, identification and recognition orients to the fact that participants are not visually available to one another, and therefore there is a need to ensure that they know who they are speaking to.

The earliest CA-based studies of openings in online interaction focused on multi-party chat rooms, such as Internet Relay Chat (IRC). Multi-party chat rooms are synchronous text-based chat clients, where the interaction involves multiple participants. Users must be online in order to interact, but transmission is one-way. In IRC, it has been found that there is an automatic notification, initiated by the server, that informs already-present users that a new user has entered the chat room (Rintel, Mulholland, & Pittam, 2001). Following the appearance of this automatic notification, the new user may post a greeting, which may be directed either at the whole chat room (e.g., “Hi everyone”) or to a particular individual user who is already present and posting in the chat room. Alternatively, already-present users who notice the automatic notification may greet the newly joined user. Therefore, in the case of IRC the technology may play a role in the interaction by effectively doing a summons. However, the automatic notification only informs the existing users of the presence of someone else in the room; it does not necessarily require the initiation of any sort of interaction, nor does it specify who should start any interaction.

There are similarities between the summons in multi-party chats and in one-to-one instant messaging interaction. The summons in instant messaging chat is also an electronic notification. However, there are two notable differences: the first is that the electronic notification is not automatically sent by the server, instead the summoner has to type a message and send it to initiate a summons; the second difference is that it tells the recipient that someone wants to start an interaction with them, it does not simply demonstrate that they are online (Meredith, 2014). With both multi-party and one-to-one chats, the opening sequence found in telephone interaction may be omitted completely (Meredith, 2014; Rintel et al., 2001) and a topic initiation may be used as the opening turn. When a topic initiation is used to start an interaction, it can be seen as orienting to the affordances of the medium (Meredith, 2014). The fact that both one-to-one and multi-party chats are written media means that the topic initiation remains on-screen. Therefore, it is not necessary for the chat starter to check whether the recipient is available prior to starting the interaction. The written nature of the medium and persistence of text on-screen have afforded the possibility of opening an interaction with a topic rather than, say, a greeting sequence. Users of both multi-party chat rooms and instant messaging systems have the names of their interlocutors available prior to the chat starting, so there is no need to have an identification and recognition sequence. For instant messaging systems, such as WhatsApp or Facebook messenger, the parties will have their own individual instant messaging account. Therefore, the chat starter can be fairly certain that the person who answers the summons will be the intended recipient. So starting a chat with a topic initiation, which is most likely designed for a particular recipient, orients to the fact that instant messaging accounts tend to belong to individuals (Meredith, 2014).

Another early form of interaction studied from a CA perspective was e-mail. The openings of e-mails show a number of differences with the findings from spoken interaction as well as the findings from chat rooms and instant messaging. First, in e-mails there is a “subject line,” which functions to tell participants broadly what the topic of the overall message will be. In early e-mail interactions, users often posted the first line of their message in the subject line (Duranti, 1986). The subject line effectively explains to the recipient why the e-mail is being sent. It has been suggested that e-mail messages tend to omit opening and closing routines (Baron, 1998). However, empirical studies have found that greetings do tend to be used in e-mails (Bou-Franch, 2011; McWilliams, 2001). In a large-scale study of workplace e-mails, Waldvogel (2007) found that the absence or presence of a greeting, and the type of greeting used can set the tone for the message. More recent research (Bou-Franch, 2011) based on e-mails sent in a university suggests that as an e-mail exchange proceeds, greetings are less likely to be used in each new e-mail. Similarly, Stommel (2012) found that the form of the greeting changes depending on the location in the exchange but also on the participants’ preferences for the form of greeting. In this sense, participants are adapting their practices to the local interactional context.

E-mails tend to be one-to-one or one-to-many asynchronous interactions. Online forums, on the other hand, are many-to-many asynchronous interactions, often between participants who are anonymous (see Figure 3).

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Figure 3. Example of an online form.

Studies of forums have suggested that greetings are not used as often, with opening posts most commonly simply starting with the topic of the post (Antaki, Ardévol, Núñez, & Vayreda, 2005). First posts in online forums may often be quite lengthy and may include a range of different questions or issues that could be responded to (Stommel & Koole, 2010). This leads to various issues when messages are being replied to, as often the recipients will choose particular aspects from the initial post to respond to rather than responding to everything. In addition, the replies may demonstrate some “misalignment” between what an initial post is asking and how it is responded to. For example, in an advice forum an initial post may simply be an introductory post or be asking for “permission” to post, yet the responses quite often offer advice, even when not directly asked for (Stommel & Koole, 2010; Vayreda & Antaki, 2009).

The opening sequences of these “mundane” instant messaging interactions show some orientation not only to the affordances of the medium but also to the social norms around how people behave on these platforms. In more “institutional” chat contexts this behavior changes again. For example, in online counseling sessions conducted via synchronous chat, the opening sequences differ quite markedly from those in spoken interaction or in “mundane” online interaction (Danby, Butler, & Emmison, 2009). Often these chats are started with requests for information or questions about the problem of the client rather than with greetings. If there have been pre-screening questions, the counselor may start the interaction with a general inquiry, such as “how may I help you?” or they may welcome the client to the chat as a form of greeting (Stommel & Molder, 2016). The interactional context here has as much of an impact on the norms and social practices of the interaction as the affordances.

More recent research has focused on technologies that allow for both visual and oral communication, such as Skype or Facetime. In these video calls the opening sequences unfold a lot like those found in telephone interaction. However, there are some differences; as interlocutors are available to one another visually, the identification and recognition sequence is not needed (Licoppe & Morel, 2012). There are exceptions to this; for example, if the face of the caller is not visible (they have not turned the video on, for example) then the recipient may raise this issue during the opening sequence. Similarly, if there is an additional or an unexpected person in the video, then a sequence where that person is introduced may occur (Licoppe & Morel, 2012). There are, then, particular norms that have arisen in video chats around the visibility of the interlocutors.

When we examine the openings of technologized interaction we find that they orient to particular affordances. However, the existence of these affordances does not determine exactly how the opening sequence occurs. It is equally possibly to find a topic-initiation in a one-to-one chat as it is to find an exchange of greetings, for example. In addition, the relationship between the participants plays a role in how the interaction is started. In a one-to-one chat between good friends, a topic initiation in first turn is less likely to be an accountable matter than between acquaintances (Meredith, 2014). The social and interactional norms of any particular platform may also play a role. As noted above, there appears to be some norm to include greetings in e-mail interaction but less so in online forums. The key when analyzing technologized interaction is to examine the interactional as well as the technological context to understand the relevance of the technology to the maintenance of relationships (Rintel, 2013).

Maintaining Coherence in Technologized Interaction

One of the key features regularly noted with regard to technologized interaction is issues with maintaining the coherence of an interaction; that is, it can be difficult for participants to identify which utterances “belong” together (Herring, 1999). This lack of coherence is also sometimes known as “disrupted turn adjacency.” Adjacency pairs are the basic building blocks of sequences of interaction, and they are composed of two turns, produced by different speakers, and are adjacent to one another in the interaction (Schegloff & Sacks, 1973). In spoken interaction, a basic rule of adjacency pair operation is that once any recognizable first part of an adjacency pair has been produced, the first speaker should stop and the next speaker should start and produce the response to that first part. Adjacency pairs should therefore be adjacent, as it is through the next turn that we show that we have understood the prior turn. It is this “nextness” or adjacency that is so often disrupted in online interaction.

It has been suggested that such disruptions are the norm rather than the exception in online interaction (Herring, 1999). One reason for this is that the majority of online interaction tends to be based on one-way transmission; that is, a turn is constructed in its entirety before it is sent to the recipient. While the turn is being constructed it is most commonly unavailable to the co-participant, at least in terms of the content of the turn-in-construction. Therefore, there can be no mutual co-ordination of when turns are sent. So, when two parties are typing at the same time, there is no guarantee that the party that started typing first will post their message first (Garcia & Jacobs, 1999). It is not clear the extent to which this sequential disruption leads to miscommunication. Garcia and Jacobs (1998) found that there may well be misunderstandings in places, although they were focusing on users learning a new technology, which could potentially lead to more misunderstandings while norms and practices develop. However, participants tend to have methods for managing these issues just as they would with spoken interaction.

The earliest studies of online interaction tended to be of multi-party chat rooms, where the interaction is very fast-moving, and this often made disrupted turn adjacency particularly notable (Reid, 1991). One way participants manage this is to “break up” their turns, simply to provide some input into the interaction before their turn becomes irrelevant (Benwell & Stokoe, 2006). What might, in spoken interaction, be one entire turn may be sent as two or three separate messages in online interaction. This practice also occurs in two-party instant messaging interaction, despite the fact that these interactions should be easier to manage due to there being fewer participants (Meredith, 2014). The practice of breaking up turns means that participants can ensure that their messages are not too dislocated from the first part of an adjacency pair, as writing shorter messages means that other users are less likely to post messages that interfere with the coherence of the interaction. Tudini (2015) notes that splitting a turn may allow participants to indicate that they will be making multiple posts (such as a list). Breaking up turns may also lead to issues with coherence, because a recipient may start responding to the first sent message while the sender continues to write the multiple messages that make up the “turn.” These multiple messages that form a coherent turn could therefore be broken up by responses to each individual message. Therefore, breaking up turns, a practice that has developed to enable users to manage potential issues with coherence, may also exacerbate the issue in places.

Other strategies used to maintain coherence include addressivity (Greenfield, Gross, Subrahmanyam, Suzuki, & Tynes, 2006), which is the use of the participants’ names to ensure that they are aware when any message is aimed at them. Lexical repetition, where the same words are repeated across multiple turns in the same thread of interaction, is also used to make it easier for readers to follow the interaction (Berglund, 2009). In both multi-party and one-to-one chats, the use of conjunctions such as “and” and discourse markers such as “so” are used to show that one utterance is linked to another (Park, 2007).

The maintenance of coherence in asynchronous interaction is often easier, as many platforms allow users to “quote” previous messages to show which post is being responded to (Severinson Eklundh, 2010). However, methods such as addressing a post to a particular recipient, which is also seen in more synchronous interaction, can help to ensure that the post is directed to the appropriate person (Gibson, 2009).

The existence of disrupted turn adjacency and some incoherence online can be attributed to the particular affordances of the medium. However, there are also certain affordances that enable coherence; the previously mentioned “quoting” facility on many forums and in e-mails, for example. One key affordance that enables coherence to be maintained is the fact that the text remains on-screen. Therefore, when strategies such as lexical repetition are used, the recipient can see the original messages and see how they are connected. In multi-party chats, where the chat moves more quickly, this is more difficult, although it is still possibly to scroll back through the chat if necessary.

It is interesting that, despite the number of claims that online interaction is incoherent, participants have adapted their practices to suit the different media and manage to maintain coherence remarkably well (Benwell & Stokoe, 2006). As such, it has been questioned whether the continued use of terms such as “disrupted turn adjacency” should be used (Greiffenhagen & Watson, 2005). As researchers continue to find that disrupted turn adjacency and supposed incoherence are the norm across multiple interactional platforms, we might instead suggest that the use of adjacency pairs has been adapted for the local interactional context.

Turn-Taking in Technologized Interaction

In spoken interaction, the key aspect of the mundane speech-exchange system first described by Sacks, Schegloff, and Jefferson (1974) is that people take turns to talk. Although this, on the face of it, is true of most forms of online communication, it is arguable how much turn-taking is closely coordinated. A considerable amount of online interaction is written, asynchronous, and uses one-way transmission, which means that co-ordinating transition between speakers can be complex. However, the separation of message construction and transmission can lead to issues with managing turn-taking. Any message sent to a chat, e-mail, forum, and so on can be seen as potentially complete and therefore is available to be responded to (Meredith, 2014). However, a user may choose to use syntax or punctuation in order to signal that their turn is not complete (Tudini, 2015). Therefore, the recipient(s) has to rely on what has been posted in order to identify whether or not there is a possible space for transition of “speakership” (Tudini, 2015). Due to the separation of message construction and sending, the writer may be “breaking up” their turn and so may self-select to continue their message (Panyametheekul & Herring, 2003). There is, then, no way to coordinate who has the rights to the next turn, particularly if both parties start writing at once (Garcia & Jacobs, 1999).

In spoken interaction, hearers are able to monitor turns-in-progress for when they might be possibly complete, in terms of grammar, prosody, and action, so they can take a turn (Drew, 2005). In most forms of online communication, with the notable exception of video messaging, it is not possible to do this. Similarly, recipients cannot provide simultaneous feedback in the form of response tokens or continuers during the turn-in-progress (Danby et al., 2009). As well as not being able to mutually coordinate when each party takes a turn, the participants in the interaction also cannot tell whether another party will take a turn. In multi-party environments, numerous turns may go unanswered, so even though there is the opportunity for another party to take a turn, it does not occur (e.g., Horne & Wiggins, 2009; Schönfeldt & Golato, 2003).

There may, then, be a number of issues with describing technologized interaction as having a turn-taking system; certainly it is dissimilar to the system in spoken interaction. However, we could argue that this potential lack of a turn-taking system is not inconsequential to the interaction (Garcia & Jacobs, 1999). Rather the turn-taking systems within technologized interaction can simply be understood as a different form of speech-exchange system (O’Neill & Martin, 2003). A key difference is that, as noted above, in one-way transmission participants in the interaction often write their messages at the same time. Some interactional platforms, such as instant messaging, inform the recipient if the other person is writing, such as through a writing icon that appears on-screen (Meredith, 2014; see Figure 4).

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Figure 4. Facebook chat.

This information on when the other person is writing appears in many instant messaging clients (WhatsApp, Facebook messenger, Skype messenger), but it can be unreliable (Stommel & Molder, 2016). Even when the writing icon appears to be reliable, writing overlap appears to occur in many instant messaging interactions (Meredith, 2014), although there is a lack of research on how exactly this occurs. It is the affordances of the medium that allow for such overlaps. One-way transmission means that overlaps do not need to be resolved, as they do not impede understanding or the progressivity of the interaction. In other words, if two parties write a forum post at the same time, it does not stop them from being able to understand the other person’s post once it is sent. Compare this to spoken interaction, where if two parties are speaking at the same time, neither party will be able to hear precisely what the other is saying; thus it would need to be resolved (Schegloff, 2000). In addition, the persistence of text on-screen means that if another party is writing as their recipient(s) posts a message, the message will still be available to them when they have finished writing and sending their message.

Another aspect of the turn-taking system in online interaction that is different from spoken interaction is the length of silence between turns. In spoken interaction, a long silence can indicate that there is some “trouble” in the interaction (Schegloff, 2002). In online interaction it has been found that there are often long gaps between turns, both in asynchronous and synchronous interaction (Cherny, 1999; Meredith, 2014; Stommel, 2012). We may expect that the gaps between turns would be shorter in synchronous interaction, where both parties are online at the same time. However, this idea of gaps between turns being inherently related to the synchronicity of the medium is somewhat outdated. If both parties are online and sending e-mails at the same time, for example, the interaction may be more synchronous. In more synchronous forms of interaction, participants may be logged in but may not be attending to the interaction, so the interaction may appear more asynchronous (Meredith, 2014).

Longer gaps between turns are rarely accountable in many written forms of online interaction, but this can be dependent on the nature of the interaction itself (Antaki et al., 2005). If the gaps have been relatively short but then a longer gap occurs, it may well be made accountable by recipient(s), or there may be a pursuit of a response (Kalman & Rafaeli, 2010; Schönfeldt & Golato, 2003). There are various reasons for these longer gaps between turns. In spoken interaction, we monitor our interlocutor’s talk for possible points when they may be finishing their turn and start our turns as soon as possible after that completion point (Sacks et al., 1974). It has been found, for example, that there is a preference for gaps of less than a second between turns (Jefferson, 1989). However, in online interaction where the transmission is one way, participants cannot monitor turns-in-progress and so cannot project a possible completion point of the previous participant’s turn and must wait until a message is sent before reading and responding to it. There is, necessarily, a gap between turns because of the time it takes to write the message. It is also worth noting here that the medium itself can play a role in the gaps between turns, due to “lag” (Herring, 1999). Lag is a technological issue whereby a message that is sent from one participant’s computer does not necessarily reach its destination (i.e., the chat room, instant messaging chat, forum, app) immediately. In these cases there may be a longer gap than expected as the recipient has not seen the message as soon as it is sent. Similar technical issues may also impact upon video messaging (Rintel, 2013), with issues such as lagged, blurry, or frozen video or potentially dropped connections, which participants in the interaction have to manage.

Repair or Dealing with “Trouble” in Interaction

As with spoken interaction, participants in technologized interaction have practices for managing potential problems, and the conversation analytic term “repair” is relevant when discussing those practices. Repair refers to ways in which interlocutors manage trouble in speaking, hearing, or understanding talk (Schegloff, Jefferson, & Sacks, 1977). It does not simply refer to correcting “errors” in talk but may refer to a wide variety of different mechanisms for managing trouble.

The first study of repair in online interaction focused on multi-party chats (Schönfeldt & Golato, 2003). This study found that participants may well adapt the basic repair mechanisms of ordinary conversation to manage the specific problems of chat communication. In other words, participants may ask for clarifications or indicate their misunderstanding after a turn has been posted. Unlike spoken conversation, where recipients can, if necessary, indicate that they have not understood while the turn is still in progress, in both asynchronous and quasi-synchronous online interaction, the parties have to wait until the message has been posted. When correcting actual errors, such as typos, after a message has been sent, participants often mark these as repairs. Collister (2011) noted that in the MMORPG game World of Warcraft, players often marked corrections with what she termed a *-repair; that is, the corrected word had an asterisk placed after it to indicate that it was a repair of a previous typing error.

One key affordance of one-way transmission is that it is possible for the writer to preempt any potential issues and try to manage these before the turn is even sent. It has been argued that this ability to construct messages in their entirety before sending means that participants may well exploit this affordance in order to communicate more effectively (Condon & Čech, 2000), as they have more time to prepare their responses, review the posts, and revise their messages. In their study of three-way instant messaging, Garcia and Jacobs (1999) found that users edited their messages in progress to account for something posted by another participant. In other words, if a user was in the process of typing something that was then made irrelevant by a message another user posted, they would edit the message they were typing so that it fit the sequential context. This type of “sequential” repair has also been found in one-to-one instant messaging (Meredith, 2014). This is not, however, the only type of editing that participants may make during message construction. There are limited studies that examine how this affordance is actually used, but those that exist (Meredith & Stokoe, 2014) note that participants will not only correct typos but also edit features such as emoticons or smilies so that the content of the message is understood as having a particular stance or “tone.” As will be discussed in the section below, emoticons and smilies are vital in indicating how a written message should be understood, and so ensuring that the correct one is used has been found to be a concern of participants. In a similar way, users may also edit “pronunciation” of their words, adding extra letters or writing the word as it might be said. Meredith and Stokoe (2014) provide an example of a participant changing the word “always” to “allllways” during message construction, to indicate how this word should be “heard.” One particular affordance of being able to edit messages during message construction is the possibility to delete an entire message, replacing it with another. Meredith and Stokoe (2014) note that when entire messages are deleted, the sent message works to take the conversation in a different direction to the originally typed message by altering the sequential implications of the interaction. In other words, a message that was originally a question might be replaced with a summarizing statement. In this case it alters the expected response from an answer to, potentially, topic closure.

The usage of one-way transmission for a variety of different interactional functions shows how users of instant messaging have adapted their practices to suit this particular technological feature. However, some forms of instant messenger, such as Skype, allow users to edit messages after they have been sent, and as long as the recipient has not seen the message, it will be edited and they will never see the original message (although they will be notified that the message has been edited). There have, as yet, not been any studies that have examined how this feature is used and if it might impact upon the interaction.

Gaze, Gesture, and Body Language in Technologized Interaction

It is often suggested that certain features of spoken interaction, such as pauses, body language, paralanguage, and so on, are simply not evident in online interaction (Crystal, 2001). Yet, we see ways in which interlocutors in technologized interactions find ways of representing such features online. Emoticons, which are combinations of punctuation used to convey facial expressions, developed online as early as 1979 (Winston, 1998) to convey the mood or attitude of the speaker (Benwell & Stokoe, 2006). These then developed into “smilies,” images that reflect these emoticons, and there are now a wide range of “emojis” that can indicate a speaker’s mood. It is argued that smilies arose on the Internet because online interaction is informal, fast-moving, and involves a lot of humorous or sarcastic posts, so some means of displaying humor is needed. These visual representations of facial expressions are usually understood differently depending on the context in which they are used (Markman & Oshima, 2007). In addition, the sequential placement of a smilie or emoticon can impact upon the action it is doing. For example, smilies posted at the start of a turn might indicate a stance toward the previous turn. However, a smilie posted at the end of a turn indicates a stance toward one’s own turn (Meredith, 2014). Another method is used in multi-modal interaction to display stance through the use of animated messages, commonly known as GIFs (Tolins & Samerit, 2016). Tolins and Samerit (2016) argue that the use of GIFs that display others’ body language and expressions allows users of a predominantly text-based communicative platform to ascribe this embodied conduct to themselves. This is, therefore, a way in which participants have adapted their practices to manage to constraints of text-based technology.

Other practices have developed that allow for some sort of paralanguage in online interaction. Punctuation can be used in order to indicate the turn’s stance or tone (Crystal, 2001). So, for example, a double question mark (??) might indicate particular surprise or incredulity when asking a question. Other typographical resources, such as capital letters, may be used as a resource to indicate tone. In some cases the capitalization of complete words is often understood as shouting and so may be seen as rude (Martey & Stromer-Galley, 2007), but in other cases capital letters may indicate excitement (Meredith, 2014). Non-standard spelling may also be used to approximate pronunciation and prosody (Benwell & Stokoe, 2006), with additional methods used for representing laughter (e.g., hehe or hah). All these practices are context-specific, but they are ways in which participants have adapted their language use to manage the online medium.

Another method by which the lack of visual contact has been managed in online interaction is through creating virtual bodies or avatars. Avatars and virtual bodies are most commonly used in online worlds and games, such as Second Life or World of Warcraft. In an interactional context, players may utilize their virtual bodies in order to manage the interaction. Therefore, they might “walk away” from an interaction that they no longer wish to be involved in (Pojanapunya & Jaroenkitboworn, 2011). Similarly, avatars may shift their gaze in order to indicate that they are unavailable to talk (Brown & Bell, 2004). The use of avatars may well develop further over time and become used more frequently in online interaction and in virtual reality. However, as the use of video messaging is becoming more prevalent, it may be that the use of a virtual body will no longer be necessary, as parties in an interaction can easily have visual access to one another.

Review of the Literature

The field of Internet studies is varied and vast (see, e.g., Consalvo & Ess, 2011; Dutton, 2013), so this review of the literature focuses on the field of computer-mediated communication (CMC). Even the field of CMC spans disciplines like linguistics, psychology, sociology, and computer science. Early theories focused on explaining how people managed and maintained interaction when there were no visual or vocal cues to rely on. These theories, which can be broadly described as “cues-filtered-out” theories, were often focused on other forms of technologized interaction but were adapted for CMC. The aim of many of these theories was to explain how the lack of social and contextual cues could lead to communication online becoming disinhibited, self-focused, and demonstrating negative affect (Sproull & Kiesler, 1986). Media richness theory (Daft & Lengel, 1986), for example, suggests that the more “rich” the media, the less chance there is for misunderstandings. Whether a medium is “rich” or not is dependent on the number of cue systems it allows (verbal or non-verbal), the immediacy of feedback from the interlocutor, and whether the language is more formal or informal. However, as CMC has developed, these types of theories have become less widely used as it has become clear that the lack of cues does not necessarily cause disinhibited behavior. Other theories, such as the social identity model of deindividuation (SIDE; Reicher, Spears & Postmes, 1995), social information processing (Walther, 1992), and hyperpersonal effect (Walther, 1996), have been developed to further explain online behavior, but with less focus on communication.

Another branch of studies aimed to understand how online interaction impacts offline lives and interactions. Turkle (1995, 2012, 2016) in particular has published widely on the role of technology in our lives and on the impact it has on everyday interactions. Baron’s work (e.g., 2010) has specifically examined how digital language is affecting offline language. From a linguistic perspective, Barton and Lee (2013) focus on the linguistic resources and practices used in digital texts. There is also a focus in the literature on how identities are formed online (e.g., Turkle, 1995), and the role of language and discourse in identity construction has been the subject of some key texts and articles (Benwell & Stokoe, 2006; Horne & Wiggins, 2009; Varga & Paulus, 2014). Benwell and Stokoe’s book Discourse and Identity is more broadly about the role of language in constructing identity but includes a clear chapter on virtual identities. Equally, while there is a wealth of research that examines the discourses of technologized interaction (see Further Reading), the aim of much of this research is to examine the topic of the interaction rather than the technology. A good example of this kind of work is a study on far right discourse on Facebook (Burke & Goodman, 2012), which examines the language used in extremist Facebook groups but does not examine in detail the role the technology might play in the interaction.

The more interactional approaches this article discusses started with work by the linguist David Crystal (2001), who wrote a seminal text: The Language of the Internet. This book describes online language and aims to evaluate whether online language was more like spoken or written discourse or whether it was a new type of language entirely (Crystal, 2001). Further studies built on this work in order to classify the different forms of language and to understand how the medium affected it (Herring, 2007). One of the key texts that started to examine technologized interaction in context, and drew upon the methods of conversation analysis, was Cherny’s (1999) work Conversation and Community: Chat in a Virtual World. In her book Cherny examined practices such as turn-taking and sequence organization as well as examining some of the more visual aspects of the context. Further research was conducted by Hutchby (2001) in his book on Conversation and Technology: From Telephone to the Internet, which is a key text for exploring how various different online platforms can be analyzed using conversation analytic methods.

A problem for research within this field is that published works often are quickly out of date as the technology changes, is adapted, or becomes obsolete. Therefore, the bulk of more recent research on technologized interaction tends to appear in journals. Garcia and Jacobs’s (1998, 1999) research on turn-taking, Rintel’s (2001) work on openings, and Schönfeldt and Golato’s (2003) article on repair are key texts that start to really unpack the interactional practices of various synchronous interactional platforms. Other, later, work focused in more detail on asynchronous interactions and addressed the feasibility of applying conversation analysis to these types of interactions (e.g., Antaki et al., 2005; Stommel, 2008). A recent paper (Giles, Stommel, Paulus, Lester, & Reed, 2015) continued to argue for an interactional approach to technologized interaction and laid out very strongly the case for developing conversation analysis for technologized interaction.

Primary Sources

For analyzing technologized interaction, the primary source of data is, clearly, the online interactions themselves. The sources of potential data of online interaction are, it seems, infinite. When taking an interactional approach as has been discussed here, it is particularly important that an effort is made to collect what is known as “naturalistic” data, which aims to reduce the level of researcher involvement in the collection of data (Speer, 2002). Online data is, for the most part, naturally occurring, as it is not generated only for the purposes of research. If data are being collected specifically for research, it is best to collect materials from participants’ ordinary use of PC or other devices rather than setting up such materials in laboratory or other formal settings. At the same time the focus will be on people’s use of their familiar programs. If a new program has to be taught for the purposes of data collection, this is likely to have an important and not easily explicated impact on the material generated.

There are clearly ethical considerations when collecting online interactions. Different researchers take different approaches to gaining informed consent to use publicly available sources of data (e.g., Stokoe, 2011, Vayreda & Antaki, 2009). Clearly, for private sources of data, informed consent must be obtained and, as with any piece of social research, information should be provided on anonymity, confidentiality, and the right of participants to withdraw from the research.

Further Reading

Androutsopoulos, J., & Beisswenger, M. (2008). Introduction: Data and methods in computer-mediated discourse analysis. Language@Internet, 5, Article 2. Retrieved from http://www.languageatinternet.org/articles/2008/1609.Find this resource:

Baym, N. K. (1999). Tune in, log on: Soaps, fandom and online community. Thousand Oaks, CA: SAGE.Find this resource:

Beißwenger, M. (2004). Sprachhandlungskoordination im Chat. Zeitschrift für germanistische Linguistik, 31(2), 198.Find this resource:

Drew, P. (2005). Conversation analysis. In K. L. Fitch, & R. E. Sanders (Eds.), Handbook of language and social interaction (pp. 71–102). Mahwah, NJ: Lawrence Erlbaum.Find this resource:

Gibson, J.J. (1979). The ecological approach to perception. London: Houghton Mifflin.Find this resource:

Hennoste, T. (2012). Enda algatatud eneseparandus eestikeelsetes MSN-i dialoogides. [Self-initiated self-repair in Estonian instant messaging interaction]. Eesti Rakenduslingvistika Ühingu aastaraamat, (8), 37–54.Find this resource:

Hutchby, I., & Wooffitt, R. (1998). Conversation analysis: Principles, practices and applications. Cambridge, U.K.: Polity Press.Find this resource:

Jones, S. (Ed.). (1998). Cybersociety 2.0: Revisiting computer-mediated community and technology (Vol. 2). SAGE Publications.Find this resource:

Lamerichs, J., & te Molder, H. F. M. (2003). Computer-mediated communication: From a cognitive to a discursive model. New Media & Society, 5(4), 451–473.Find this resource:

Meredith, J. and Potter, J. (2013) Conversation analysis and electronic interactions: methodological, analytic and technical considerations. In H. Lim & F. Sudweeks (Eds.) Innovative methods and technologies for electronic discourse analysis (pp. 370–375). IGI Global.Find this resource:

Vallis, R. (2001). Applying membership categorization analysis to chat-room talk. In A. McHoul, & M. Rapley (Eds.), How to analyse talk in institutional settings (pp. 86–99). London: Continuum.Find this resource:

Werry, C. C. (1996). Linguistic and interactional features of Internet Relay Chat. In S. C. Herring (Ed.), Computer-mediated communication: Linguistic, social and cross-cultural perspectives (pp. 47–64). Amsterdam: John Benjamins.Find this resource:

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