Illocutionary acts and functional orientation of SMS texting in SMS social networks
Susana M. Sotillo
Montclair State University
Investigations of short message service (SMS) texting practices have shown that SMS language constitutes a particular variety of naturally occurring language characterized by structural simplifications and recoverable semantic implications. Despite omissions of noun phrases, function words, auxiliaries, and other features of formal writing, recent studies have shown that the implicit communicative intention is successfully recovered and interpreted by the message recipient. Though various studies have described the transactional, orthographic, and linguistic aspects of text messaging (e.g., Fairon, Klein & Paumier 2006; Hård af Segerstad 2005; Tagg 2009), Thurlow & Poff (2011: 12) claim that perhaps the most important feature of texting is its “sociable function” or relational orientation. Building on previous research that uses Speech Act Theory (SAT) for data analysis (e.g., Nastri, Peña, & Hancock 2006), and Thurlow and Brown’s (2003) communicative intent-functional orientation framework, this study investigates illocutionary acts and their intended function in a subsample drawn from a corpus of 5,809 sent and received text messages. Two research questions are addressed: 1. What types of illocutionary acts are found in the texting practices of individuals who form part of six SMS social networks? 2. What is the communicative intent or functional orientation of illocutionary acts evident in these SMS texting exchanges? The results show that assertives and expressives, followed by directives and commissives, account for the majority of illocutionary acts in the SMS texting data analyzed, and that the functional orientation of SMS texting exchanges can be classified along a continuum of personal-relational and transactional-informational.
Mobile telephony and computer-mediated communication have been studied from multiple perspectives in a variety of disciplines including behavioral psychology, communication studies, discourse analysis, sociolinguistics, social network analysis, and sociology. With respect to the impact of mobile devices on language and communication, Baron (2008) has shown how electronically-mediated technologies are changing the way we communicate and relate to each other. More extensive findings relating to relational and linguistic features, including the maxims that speed and brevity, paralinguistic restitution, and phonological approximation characterize SMS texting, are presented by Thurlow & Poff (2011). In addition, Tagg’s (2009) doctoral research shows that while not all text messages are brief, texters display creativity and performativity in their texting practices.
There are several studies of short message service (SMS) texting practices from a social network analysis perspective that have measured adolescent use of socially interactive technologies (SITs) and their relationship to offline social networks (Bryant, Sanders-Jackson, & Smallwood 2006). Their results showed that socially isolated adolescents did not use SITs, but those who favored their use did not necessarily increase their offline ties. Other studies of teen and young adult texting and instant messaging have also addressed social functions and linguistic and metalinguistic issues. Contrary to the exaggerated claims of journalists and social pundits, a positive association between texting and literacy practices, including better performance on standardized measures of English proficiency, was found by Plester, Wood, & Bell (2008) and Plester, Wood, & Joshi (2009). Texting was shown not to interfere with the acquisition of the standard code (Tagliamonte & Denis 2008).
Scholarly research as well as the popular press point to the importance of text messaging or digital communication, which is widely used around the world by children, adolescents, and adults. Anyone, anywhere in the world has the ability to send a message via the SMS of mobile phones, smartphones, and other techno-cultural artifacts. Opencode-Mobile Network Systems (February 2012) estimates that the total number of text messages sent by individuals/consumers to mobile phones worldwide is approaching 10 billion SMSs per month. This technology, according to ABI Research, continues to be the preferred mode of communication among younger groups, with the most popular types of communication being SMS, MMS, mobile email and instant messaging. Their use will vary according to age, purpose, and affordability (Tsirulnik 2010). In addition, SMS today is widely used in the corporate world for instant notification of important events.
In the United States, not all teenagers, young adults, or individuals with limited income are in a position to afford the mandated data plans when purchasing communication devices. However, these groups, including mature adults, are in a position to use SMS texting for maintaining social relationships, obtaining information, scheduling appointments, asking/answering questions, criticizing, or producing the textual equivalent of “illocutionary” acts (i.e., meaningful utterances/messages with a certain conventional force) or texter’s intention in sending a text message. Texters also produce what are in essence “perlocutionary” acts that compel the message recipient to react to the message received. For example, a recent study by Nastri, Peña, & Hancock (2006) used speech act analysis to examine the nature of “away messages,” a form of digital communication. Their results showed that assertives and expressives were more numerous than commissives, and that directives were rarely used because away messages are constructed for informational and entertainment purposes, confirming previous findings by Baron et al. (2005). In the case of SMS texting, studies have shown that people send texts to those who form part of their personal or professional SMS social networks for a variety of reasons (Betti 2008; Ling & Donner 2009; Lloyd & Gillard 2010; Sotillo 2010; Tagg 2009; Thurlow and Brown 2003; Zarantonello 2001). These include constructing identities, enhancing linguistic creativity, strengthening personal and professional relationships, exchanging information, and maintaining SMS social networks.
This study builds on previous research by Nastri, Peña, & Hancock (2006) and Twitchell & Nunamaker (2004) who used SAT as a model for analyzing language use in computer-mediated communication because it allows researchers to explain the intended meaning of speech acts. However, few studies have used SAT in order to analyze digital communication in SMS texting and this is the purpose of this investigation. The study also seeks to expand on Thurlow and Brown’s (2003) findings concerning the sociability or relational nature of SMS text messages. SAT and Thurlow and Brown’s framework are useful for analyzing SMS texting data since these two approaches complement each other. By using SAT it is possible to explain the intended meaning of text messages identified and coded as different types of illocutionary acts. Similarly, an adaptation of Thurlow and Brown’s (2003) framework is helpful in uncovering the communicative intent or functional orientation of these text messages. By combining these two approaches the aim of this exploratory study is to explain how illocutionary acts are instantiated in text messages, and what their intended function or purpose is. Two general research questions are addressed: 1. What types of illocutionary acts are found in the texting practices of individuals who form part of six SMS social networks? 2. What is the communicative intent or functional orientation of illocutionary acts evident in these SMS texting exchanges?
2. The corpus
This study is based on a subsample of a corpus of 5,809 sent and received SMS text messages donated by six individuals, three males and three females, who owned six SMS social networks. Data collection was approved by the researcher’s Institutional Review Board. Each SMS social network centered around an individual and his/her texting partners, which included family, friends, relatives, neighbors, and co-workers. The six who contributed their text messages were teenagers, colleagues, neighbors, friends, and some family members of the researcher. The individuals identified as the owners of the six SMS social networks included two female teenagers, ages 16 and 19, respectively, and a 17 year-old male. The adult SMS social network owners included a 57 year-old female educator, a 38 year-old IT specialist, and a 62-year old male professor. SMS texting social networks in this study are defined following Fuhse (2009) as “configurations of social relationships interwoven with meaning” (p. 51), which are comprised of sociocultural structures. In ego-centered networks, the structure of relationships can be examined by looking at the types of transactions that take place between individuals (Fuhse 2009: 52). Thus, an SMS social network is defined as a complex system of interpersonal texting relationships and expectations between an actor or texter (SMS social network owner) and various individuals who receive and respond to the texter’s messages. More than 59 individuals from different social backgrounds and ages formed part of the six SMS social networks. In the subsample analyzed, the average number of participants in the three teenagers’ SMS social networks was 19, whereas it was 23 in the adults’ SMS social networks.
2.2 Data collection procedures
Sent and received text messages collected for this study were downloaded by contributors using software developed for smartphones such as Treos and Blackberries, among other brands. The subsample consisted of 1,271 sent and received text messages that were randomly selected from the beginning, middle, and end of the SMS text message data sets contributed by each of the six owners of the SMS social networks. There were 417 sent and received text messages in the SMS social networks of the teenagers, 348 from owners and members of two of the adult SMS social networks, and 506 from information technology (IT) specialists, who formed part of the SMS social network of the third adult contributor.
3. Theoretical framework of analysis
Though most studies motivated by Speech Act Theory (SAT) have focused on the utterance as the unit of analysis, digital technologies require new perspectives or approaches to the study of language, which in the past have often privileged the spoken language or literary language. SAT as a method for analyzing SMS texting data was chosen because it is a practical taxonomy that has been used in studies of natural language processing and computer-mediated communication (Nastri, Peña, & Hancock 2006; Twitchell & Nunamaker 2004). Furthermore, as mentioned in the Introduction, SAT allows researchers to explain the intended meaning of text messages identified and coded as illocutionary acts, whereas approaches such as Discourse Analysis and Conversation Analysis generally focus on the co-construction and negotiation of meaning in face-to-face interaction or recorded telephone conversations.
Few studies have used SAT or related taxonomies to analyze digital communication in Instant Messaging or SMS texting (Nastri, Peña, & Hancock 2006). However, there is still a need to study the pragmatics of text messaging practices. This study seeks to add to recent findings concerning the nature of SMS texting by using SAT analysis and an adaptation of Thurlow and Brown’s (2003) communicative intent-functional orientation framework. In SAT, functional units of communication have locutionary or propositional meaning (i.e., the literal meaning of what is said), illocutionary meaning or the intended meaning of what is said, and perlocutionary force or the effect of what is said on a hearer or message recipient. In this study, the focus will be on illocutionary meaning because the data consist of text-based digital exchanges. Also, the functional orientation of these text messages will be investigated.
3.1 Brief overview of SAT
Communication and language scholars often draw on Speech Act Theory (SAT) in an attempt to explain how speakers use language in order to accomplish intended goals or actions and how hearers or recipients of an utterance or message infer the intended meaning from what is said. Austin (1962) initially presented five general classes of illocutionary acts or conventional force of utterances (verdictives, exercitives, commissives, behabitives, and expositives). His concepts and taxonomy were extended by Searle (1965, 1969, 1975), who proposed constitutive rules and broadened Austin’s notion of uptake by asserting that the performance of an illocutionary act involves the securing of uptake (Halion 1989).
In his comprehensive review of the history of SAT, Smith (1990) traces back the development of speech act theory by analyzing the contributions of various philosophers, beginning with Thomas Reid’s rejection of the Aristotelian view of language toward the end of the 19th century. He expounds on the insightful contributions of various members of the Munich school of phenomenologists (1990: 49) and demonstrates the closeness of Reinach’s thinking to Austin’s and Searle’s. Searle, expanding on Austin’s work, introduced a distinction between literal word or sentence meaning and speaker’s utterance meaning. For Searle, the production of a word or sentence in the performance of a speech act constitutes the basic unit of linguistic communication (Searle 1965: 136).
SAT is not without problems because of flawed conceptualizations of language that regard the sentence as the unit of analysis for speech acts (e.g. Austin 1962; Searle 1969, 1975, 1979) and the claim made by some scholars that there are universal pragmatic principles (e.g., Austin 1962; Habermas 1976; Brown & Levinson 1978). Others argue that speech acts are culture-bound notions that vary across cultures and languages (Allwood 1977; Rosaldo 1982; Wierzbicka 1985). This investigator finds that this criticism is well founded in that studies of speech acts in other cultures (Rosaldo 1982) can only be interpreted within the context of prevailing “situational and cultural constraints on forms of language use (Rosaldo 1982: 203). Additionally, Searle’s categories for analyzing speech acts have been criticized by scholars such as Burkhardt (1990) and Clark (1996) because of his assumption that each speech act can be neatly placed in one category, ignoring the multiple functions of language. Understandably, this is not always possible, especially with respect to SMS text messages since the intended meaning of illocutionary acts can be ambiguous to an outsider examining text messages from a particular SMS social network of which he/she is not a member. Thus, inferring meaning and pragmatic functions from SMS text messages is a challenging undertaking.
4. Analysis of the data
4.1 Classifying illocutionary acts
Searle’s (1969, 1979) basic taxonomy of five types of illocutionary acts is used in this study in order to identify, classify, code, and subsequently tag speech acts for processing using MonoConc Pro 2.2 (Barlow 2002), a software tool. The text message as an illocutionary act is defined as a propositional unit, which sometimes includes punctuation. Linguistic routines such as greetings and leave-takings, expressives, phatic, and conative interjections, and onomatopoeic speech act verbs, a subset of interjections, are also categorized as speech acts (Tsai & Huang 2003). Thus, notwithstanding their nonsentence status, greetings and leave-takings that consist of more than one word (hi how are you), emoticons and some common acronyms, initialisms, and abbreviations (e.g., LOL, Pls, idk, flmao, kk) were coded depending on the context of the exchange as either part of expressives, assertives, or some other category. Digital communication researchers have shown that these linguistic forms are considered part of a global SMS language (e.g., Ling 2007; Thurlow & Poff 2011; Deumert & Masinyana 2008). Table 1 illustrates how Searle’s five types of illocutionary acts (assertives or representatives, directives, commissives, expressives, and declarations/declaratives) were used to code and analyze the SMS texting data.
|Type of illocutionary act
||Definition and properties
||Examples from text messaging corpus
Statements or expressions that represent a state of affairs
or commit the texter to the truth of an expressed proposition.
“dave, im not a bad person.”
“I never said you were.”
“Minors are allowed to work anything under 40 hours.”
“Didi is mad funny because she is mad cool”
“Hey im not going 2 skool”
“But I have to go to the police department tomorrow”
a. outright command, request, offer, order
b. Indirect request, order
The texter uses this type of statement/expression in order to
get the textee (person addressed) to do something.
a.“get me some cranberry juice and tuna fish cans in water.”
a. “Focus on your own problems & how you plan on solving them.”
a. ”don't give my cell# out 2 people.”
a. “You better go to sleep.”
b. “Please invite Margaret and her family”
b. “Just tell Andy your free on certain days.”
Text message through which texter commits him/herself to
something or some future course of action.
“Home by 630ish.”
“Will be home by 4:30ish...”
“I can help you at 3:00 pm”
“Let me look for that...”
“ and I'll send it asap.”
Texter expresses psychological state toward a particular state
of affairs or someone. Because of their illocutionary force, routine
texting expressions such as LOL, which often precede messages,
and emoticons, which follow expressives, are included in this category.
“G. thanks for the brilliant lesson is sweat equity
“And S. thank YOU for helping B get his own line.”
“Sorry i was so cranky in my msg.”
“but i am getting tired of doing Barney's work.”
“I'm mad beat”
“I love you <3 if that counts”
- | - J L :o ;) :-D :-x :-<> :-( )
These types of illocutionary act bring about changes in an institutional state
of affairs or in reality. Well-known examples include:
“I pronounce you man and wife.”
“Take your stuff and get out!”
No examples of declarations were found in this subsample.
Table 1. Coding scheme for the analysis of illocutionary acts in SMS texting corpus
Adapted from Nastri, Peña, & Hancock (2006). All examples are from a corpus of 1,271 actual sent and received unedited SMS text messages downloaded by contributors.
4.2 Tagging and analysis of illocutionary acts
Downloaded text messages were manually coded and tagged according to the categories described in Table 1. Initially, we sought to identify performative verbs in the text messaging data based on Vanderveken & MacQueen’s (1990) analysis of performative verbs by generating lists of verbs using MonoConc Pro2.2. However, this was not a productive endeavor as few of the performative verbs identified by Vanderveken & MacQueen were found in the subsample (e.g., agree, invite, promise, tell). The illocutionary act or intended meaning of speech acts in text messages had to be inferred from context. Text messages coded and tagged as illocutionary acts represented propositional units carrying the intended message and were often but not always separated into different units of communication by punctuation: <ASS>Just hd Palm Dsktop pblm</ASS> <ASS>& gt gd hlp fm lady tech-in the Philippines!</ASS> <DIR>Ask her about the software to save cell text messages.</DIR>. Each text message was examined carefully since some contained two or more propositions. For example, “hates Kenny, etc in Belleville” “husband was R's aide.” “I guess he's back on staff.” Though these constitute three different illocutionary acts, they formed part of one long text message. In general, it was easier to code mutually exclusive categories when unambiguous examples could be found (e.g., directives vs. expressives): <DIR>Please do not go down this road right now.</DIR> versus <EXP>thanx bro</EXP>.
Once text messages in this subsample were coded and tagged, lists were generated for further analysis. Since IRB guidelines required that the investigator remove all identifying information (e.g., cell phone numbers, email addresses, first and last names or other indentifying information), coding for illocutionary acts in this subsample was at times very difficult because adjacent and functionally related turns were not easy to identify. Nevertheless, sequences of related messages by different texters were found primarily in text messages donated by one the three teenagers and in those of most adults. (see untagged mini example)
Text messages representing propositional units ranged from six to 75 characters because only 160 characters are allowed per message. Thus, if a texter sent a very long message that included “if-then” clauses or several propositional units, these were coded separately as illocutionary acts and often appeared as two or three consecutive text messages. There were 10,840 words in the 1,271 text messages analyzed, which yielded an average of 8.53 words per text message in the corpus after removing punctuation and treating contracted words as one (e.g., “we'll,” “can't”). Also, an average of four intervening messages were found between a question or request sent by a texter and the recipient’s reply, except for the messages contributed by a 38-year old male. In his SMS data there were 21 intervening text messages between a request for information by a member of his own SMS social network and the answer he subsequently provided.
As with most high-inference categories, a certain degree of ambiguity in the definition of speech acts/illocutionary acts categories is present and this calls for insider cultural knowledge. This complicates the coding task as some illocutionary acts overlap and could be coded as belonging to two different categories. Also, critics of SAT point out that placing utterances, in this case, text messages, into mutually exclusive categories ignores the multiple functions of language use.
Two trained raters and the researcher initially coded all text messages in the subsample as belonging to one of five categories, but modified these to four because no examples of declarations were found in the data. Though there were disagreements with respect to the classification of illocutionary acts in some of the text messaging data, inter-rater reliability was statistically significant at p <.001) (Kendall’s Coefficient of Concordance=80). Illocutionary acts that were difficult to assign to either one or another category were discussed in face-to-face meetings until a resolution was reached.
4.3 Analysis of communicative intent-functional orientation
Communicative intention as defined by Grice (1969) was understood as the intended effect on a hearer or audience, and awareness of this intention that someone’s utterance had but this notion was criticized by Strawson (1964), Searle (1969), and others working within a formal mentalistic approach. For our purposes we define communicative intention as the intended function or purpose texters sought to accomplish through specific illocutionary acts (e.g., inform, order, complain, criticize, request personal favors, commiserate, or change behavior through perlocutionary acts). Sequences of text messages classified as assertives, expressives, directives, and commissives in this corpus were examined by the researcher and two graduate students and coded according to the specific communicative intent-functional orientation we inferred. After examining 57 pages of text messages or 1,391 lines of text, we came up with the following coding scheme modeled after Thurlow and Brown’s (2003) communicative intent-functional orientation framework: Information Sharing, Requests, Scheduling and Planning, Friendship and Intimacy, and Social Network Maintenance. Those that were ambiguous were not coded because it was impossible to reach agreement. These are described below.
Information sharing: These were classified as illocutionary acts instantiated in text messages that focus on sharing specific information in response to a texter’s request or based on statements that need further elaboration (T stands for texter and numbers indicate different participants):
||T1: r u working 2day?
||T2: probably but I got school tomorrow.
||T2: near the pond, gab picked u up one day and i remember
||T3: M U have a horrible hornet's nest on the strip of grass next to Lorry's.
||T4: Funny you say that. They are in the back too.
Requests: These illocutionary acts dealt with requests for personal favors (indirect requests) and direct orders or commands from family members, social network friends, or acquaintances from work that the message recipient do or not do something:
||T1: BB would you be able to work this Friday and I cover your Saturday?
||T2: Alright ill let you know cus its my sisters birthday
||T5 Please print a copy of 6 slides per page
||T7: I need access to your lab to identify which connections to move for Thursday.
Scheduling & planning: These consist primarily of illocutionary acts that texters use to coordinate meetings at work, plan lunch or dinner dates, arrange shopping trips or pick-up times, and invite friends and acquaintances to local functions:
||T8: hay you coming with me today? Polycom HD
||T9: Can't, I have that hardware meeting.
||T8: I'm in..wanna take a ride to Target?
||T10: Tomorrow night (Sat.) at 7:30 at the KofCs, Johan is being honored at the Fops organization's dinner...
||T11: OK I'll be there if U still have tickets.
||T8: I'm here gotta pee
||T9: RE:Safari Post Try http? im at da beach!
||T8: Leaving garage now
Friendships and intimacy: These are illocutionary acts focused on emotionally loaded issues discussed with intimates, and subsumes text messages of a romantic nature with sexual overtones found primarily in the teenagers’ SMS social networks:
||T12: Yo. I'm going to apologize to you because I have a feeling I'm going to do something terrible.
||T12: Because she only calls me when she needs me. I feel used...
||T12: I'm fine physically. Just really sad : (
||T14: Well back on my grind love you sexy bitch
||T15: okay stop hittin on me and go study for ur drivin exam
||T15: stop picturing me without clothing
||T4: Foreal ppl are mad nosey
Social network maintenance: These consist primarily of text messages sent by the SMS social network owners for the purpose of keeping in touch with family, friends, and acquaintances or with relatives living in other cities or states.
||T8: How are you doing
||T10: Happy Thanksgiving to u and the fam. Send our wishes to R. & S. as well.
||T11: M! Hi! I'm going to be on America west 683/us airways 8121 arriving at 1048 pm.
||T11: On time so far.
Ambiguous: This category included illocutionary acts instantiated in text messages where the inferred function or purpose could not be easily categorized. For example, the following assertions could be classified as information sharing, but their intended communicative function appears to be didactic. It seems as if the political operative making these assertions is not just sharing information with others, but is also assigning blame for political losses and teaching a lesson: <ASS>In every campaign, lessons are learned. </ASS> <ASS>I'm sure B learned that he should have been holding fundraisers for the two years that he was telling anyone who would listen that he was running for freeholder.</ASS> <ASS>The other lesson is that nowadays there is no such thing as volunteerism in campaigns.</ASS> <ASS>People need an incentive if you expect them to provide quality help in an election. </ASS>
The following SMS exchanges also illustrate that it is possible to place these messages in more than one category:
||T13: Damn this early that's sucks (information sharing or personal request to exchange work schedules)
||T2: LMFAO. I know he's been at our table too damn long (information sharing or request to ask him to leave).
||T3: it takes a shit to know a shit ! thanks love u too (friendship (sarcasm) or information sharing)
||T2: Coming back from medusa. You? (personal request or information sharing)
||T4: I dont know yet. You? (information sharing or response to request)
However, 66 % of the communicative units examined in this subsample were successfully classified as to their intended functional orientation by all three raters.
Research question 1 sought to investigate the types of illocutionary acts found in the SMS text messages of members who formed part of six different SMS social networks. Table 2 presents frequency counts for each of the four types of illocutionary acts that were identified and coded. Though Searle’s classification scheme consisted of five mutually exclusive categories, we only identified four since there were no declaratives/declarations or verdictives as these are speech acts that can only be uttered, performed, or written by individuals in positions of authority representing institutions, such as judges, police officers, or employers.
||Directives: indirect & outright orders
||Expressives: words & emoticons
||Speech act Totals
150 | 246
532 | 135
Table 2. Illocutionary acts in text messaging subsample
Total No. of words: 10,840 (tokens) Total number of types: 2,493
Figure 1 illustrates the percentage of each illocutionary act category out of a total of 2,020 illocutionary acts identified, coded, and tagged in 1,271 text messages. Assertives account for 39% of all illocutionary acts, followed by expressives (33%), directives (20%), and commissives (8%).
Figure 1. Types of Illocutionary Acts
Figure 2 shows the distribution of illocutionary acts by owners and members of each of the six SMS social networks. Of the four categories of illocutionary acts, teenagers used assertives 51.64% of the time, expressives, 34.57%, followed by directives and commissives (10.38% and 3.41%, respectively). The distribution of illocutionary acts in the sent and received text messages contributed by a 62-year old SMS social network owner was as follows: 44.54% expressives, 25.21% assertives, 22.69% directives, and 7.56% commissives. One of the adult SMS social networks included a number of political operatives who sent SMS texts to the network owner and multiple recipients. This group showed the following distribution: 51.16% assertives, 21.19% expressives, 17.57% directives, and 10.08% commissives. Another adult SMS social network was made up of IT specialists whose distribution of illocutionary acts was as follows: 46.66% assertives, 22.95% directives, 22.32% expressives, and 0.08% commissives.
Figure 2. Illocutionary Acts by SMS Social Network Membership (Age and Occupation)
Assertives were used to a greater extent by teenagers (51.64%), political operatives (51.16%), and IT specialists (46.66%). In contrast, members of a mature adult’s SMS social network used fewer assertives (25.21%) and directives (22.69%), but made significant use of expressives, which consisted primarily of emoticons and terms of affection, (44.54%). Directives were used primarily by IT specialists (22.95%), mature adults (22.69%), and political operatives (17.57%). Teenagers used fewer directives than all the other groups (10.38%). Commissives were used to a greater extent by political operatives (10.08%) and rarely by IT specialists (0.08%).
Research question 2 sought to uncover the communicative intent or intended functional orientation of illocutionary acts identified in the text messaging practices of members of six different SMS social networks. An adaptation of Thurlow and Brown’s (2003) framework was used for classifying communicative intent or functional orientation. Frequency counts and percentages are displayed in Figure 3 and Table 3.
Figure 3. Communicative Intent-Functional Orientation of Illocutionary Acts in SMS Texting
Table 3. Communicative intent-functional orientation of illocutionary acts
As shown in Figure 3, the communicative intent-functional orientation of these SMS texting exchanges was as follows: Information sharing (24%); requests (19%); social network maintenance (8%), friendship & intimacy ( 8%), and scheduling and planning (7%). It was not possible to reach inter-rater agreement concerning the intended function or purpose of 680 text messages classified as various types of illocutionary acts because these could be placed in more than one category.
The present study investigated sent and received SMS text messages by examining the types of illocutionary acts produced by owners and members of each of six SMS social networks. It also examined the communicative intent or function of these illocutionary acts using Thurlow and Brown’s (2003) framework to infer the intended functional orientation of these SMS texts. This study complements previous studies of SMS texting (i.e., Baron 2008; Thurlow and Brown 2003; and Nastri, Peña, & Hancock 2006) by providing a careful analysis of a corpus of 1,271 sent and received text messages using Searle’s speech acts taxonomy and subsequently classifying the pragmatic functions of SMS texting by employing a modification of Thurlow and Brown’s (2003) communicative intent-functional orientation scheme.
Despite the limitations of assigning text messages to mutually exclusive speech act categories, Searle’s (1969) taxonomy is a valuable tool for understanding the meaning and functions of this variety of natural language, SMS texting. Speech act analysis has also been used productively in previous studies of computer-mediated communication, and its use in the present SMS texting corpus has yielded some noteworthy results that could be explored further by language and communication scholars. These are discussed in the following sections.
The results of this study, which included SMS texts contributed by individuals who vary in age, education, social status, and occupation, partially confirm findings by Nastri, Peña, & Hancock (2006) that assertives, followed by expressives, were found instantiated in these SMS text messages. However, directives numbered twice as many as commissives, which is the opposite of what Nastri et al. (2006) found in “away messages.” Furthermore, the use of assertives, expressives, commissives, and directives varied by age and occupation as shown in Figure 2. Directives, which were of two kinds, indirect and direct requests or orders, were often sent to family members instructing them to buy groceries or to arrange to pick up a child after school or sports practice. Polite requests, on the other hand, sought to convince the message recipient to do something with or for the texter. Work-related directives with no mitigation were present in the IT specialist’s SMS social network, which included requests that required an immediate response: “Tech coord,” “Where is it”; “Where is tech coord?*228.” These were sent to co-workers by the IT specialist or from supervisors ordering subordinates to perform a specific task or to schedule a meeting.
As instantiated in their text messages, teenagers used assertives more often than expressives, commissives, or directives. They actively asserted their identity when being criticized or challenged by their peers. Assertions were also used among teenagers to share relevant information with friends and acquaintances and to pass judgment on others. In contrast, members of the 62-year-old male’s network used expressives almost twice as often as members of the teenagers’ SMS social networks, and to a greater extent than other illocutionary acts. Some examples include the following: “Querida, I love U! Besos, G :-x”; “D never called me back. L”; and “Querida On my way home. Besos G.” A thorough analysis of the SMS text messages sent and received by this 62-year-old male to members of his own SMS social network showed that he often interspersed his messages with emoticons or expressions of affection (love). This is a pertinent finding in light of what has been reported in previous studies of SMS texting about the scarcity of emoticons and lexical shortenings in the text messages of teenagers and young adults (Ling 2005; Ling and Baron 2007; Thurlow & Brown 2003; Thurlow and Poff 2011). These empirical studies have debunked claims made by media pundits and journalists that teenagers and young adults use emoticons, abbreviations, acronyms, and misspellings extensively in their SMS texting practices. As the results of this study show, mature adults used almost twice as many emoticons and expressions of affection in their text messages than teenagers and other adult texters. A possible explanation inferred after examining the SMS texting data contributed by the 62-year-old male is that he is sending text messages to members of his immediate family, which include adult children and grandchildren, and to a small circle of close friends. Thus, the closely-knit SMS social network of this texter accounts for his extensive use of expressives.
Both assertives and commissives were more frequently used by individuals involved in political work who were members of an adult SMS social network. These texters were involved in local politics and were often instructed via text messages to attend political meetings, recruit new voters, and monitor polling places on the day of the election. The political operative organizing get-out-the-vote activities texted lengthy messages, some of which were 29 words long, though the average number of words per text message in this subsample was 8.53. This texter often promised future rewards to those who helped with the logistics of a political campaign, which accounts for the frequent use of commissives (10.08%) in this SMS social network. In contrast, commissives were almost non-existent in the IT specialist’s SMS social network (0.08%), and rarely used by teenagers (3.41%). Based on the text messages analyzed in this SMS social network, we inferred that IT specialists are not in a position to make promises concerning immediate attention to a technical problem a friend or co-worker is experiencing or to problem solving on the fly.
As to the relational or sociable nature of text messaging as reported by Thurlow and Brown (2003) and Thurlow & Poff (2011), this study found that most individuals in all six SMS social networks texted primarily for personal and social reasons, which partially confirm previous findings reported by Thurlow and Brown (2003), though their results were based on SMS texting data collected solely from young adults. However, the functional orientation framework that classifies various subcategories along a continuum from low intimacy, high transactional orientation to high intimacy, high relational orientation is too simplistic for adequately analyzing and explaining SMS texting data contributed by individuals who vary in age, social status, education, and occupation. Inter-rater agreement was not reached with respect to 34% of the texting data analyzed because it was not always possible to infer unambiguous functional orientation. Thus, the inferred functional orientation of the SMS text messages analyzed ranged from personal-relational texting (e.g., personal requests, friendship and intimacy, and social network maintenance), which represented 53% of all SMS texting in this corpus, to transactional-informational texting (e.g., information sharing and scheduling and planning), which accounted for 47% of all texting. This continuum is shown in Figure 4.
Figure 4. Inferred Functional Orientation of SMS Texting
Despite the shortcomings of this framework, our results show that slightly over 50% of all texting was of a personal-relational nature. The most frequent functional orientation classification at this end of the continuum was personal requests, followed by social network maintenance, and friendship and intimacy. Friendship and intimacy appear to be more important functions of texting for teenagers who are in the process of constructing their own identities, exploring sex, maximizing social bonding, or extending their social networks online and offline. In the case of adults, expressions of intimacy were used primarily to reinforce family ties, long-standing relationships, or to maintain long-distance friendships.
To summarize, based on speech act analysis (Searle’s taxonomy) and a modification of Thurlow and Brown’s (2003) framework, this study based on a corpus of 1,271 text messages contributes the following to the extant literature on SMS texting practices:
- assertives, followed by expressives, directives, and commissives are more frequently used by members of all but one of the SMS social networks analyzed. Thus, differences in stages of life rather than social status, education, or occupation may explain the fact that expressives were used to a greater extent in the SMS social network owned by a 62-year-old male.
- slightly over 50% of sent and received text messages in the SMS texting corpus analyzed point to a personal-relational functional orientation, but texting of a transactional-informational nature is also evident in these texting practices.
- although brevity was evident in the SMS text messages analyzed, with an average of 8.53 words per text message, some were 29 words long, especially those sent by adult texters engaged in local politics. Thus, occupation may account for length of message in the text messages analyzed that were sent and received by members of different SMS social networks.
- SMS texting represents a localized variety of natural language because the use of certain conventions (e.g., abbreviations, shortenings, acronyms, emoticons, misspellings, jargon) varies by age, social status, education, and occupation. Though gender differences were not taken into consideration in this study, it is possible that they could have accounted for variation in pragmatic functions and types of illocutionary acts.
- creativity is apparent in the teenagers’ text messages as shown by their use of expressives, assertives, and other illocutionary acts, though variation in linguistic form and lexical features was not the focus of this study.
7. Limitations and conclusion
Since this is a qualitative study of localized text messaging practices of owners and members of six different types of SMS social networks, it is not possible to generalize these findings to other texter populations. The illocutionary acts identified in these text messaging practices reflect the meaning and intentions of individuals who share extensive background knowledge. The use of speech act analysis on a much larger corpus of thousands of SMS text messages would probably yield qualitatively and quantitatively different results. However, the intended meaning or conventional force of the text messages investigated in this study conforms to Searle’s (1969) conceptualization of language as a type of social activity. The use of speech act analysis contributes to our understanding of texting as an efficient, speedy, and dynamic form of human communication despite the fact that both Austin and Grice would have classified many of the abbreviations, emoticons, jokes, G-clippings, letter/number homophones, typographic symbols, lexical shortenings, alternate spellings, and fixed expressions that convey meaning in texting as types of parasitic speech acts.
The findings of this study have implications for texting practices among members of other types of SMS social networks. Since text messaging is now commonly used by academics, emergency medical technicians, physicians, and police officers to reach different groups, it should be more extensively studied from a variety of approaches, including ethnographic research, for its socio-cultural context, information-sharing potential, and community-building purposes. It would be desirable to collect and anonymize thousands of sent and received text messages, using special smartphone software developed for this purpose, from individuals living in different geographic regions of the United States that represent vastly different socioeconomic and cultural backgrounds. This would yield valuable information on the types of intended meaning and pragmatic functions of illocutionary acts found in culturally and linguistically diverse SMS social networks, a task currently being undertaken by Chen and Kan (2011). Large databases of SMS text messages would make it possible to study not just syntactic, orthographic, or stylistic features of texting, but also textual features, pragmatic functions, and socio-cultural aspects of texting, including code-switching. This would significantly advance our understanding of this variety of naturally occurring language.
In conclusion, this exploratory study confirms and expands findings of previous studies of SMS texting that have utilized speech act analysis of a qualitative and quantitative nature. The study explains the frequent use of assertives, followed by expressives, directives, and commissives by texters participating in the six SMS social networks examined. The meaning inferred from these illocutionary acts reveals the texters’ communicative intention and concomitant pragmatic functions. There is a continuum with respect to the functional orientation of these localized texting practices from highly personal-relational to decidedly transactional-informational, which involves more formality in texting. Through texting, teenagers can assert their identity, express their creativity, strengthen their bonds, and expand their social networks. This technology also allows adult texters to strengthen emotional bonds and friendships within their own SMS social networks, while accomplishing numerous personal and professional or occupational goals. Although all technologies evolve and change, as Baron (2008) claims, SMS texting appears to be altering interactional and communicative patterns beyond our own private SMS social networks. For this reason, it is important to encourage further research on texting from a variety of perspectives and methodologies.
Untagged mini example: Sotillo_Untaggedminisample.pdf.
ABIresearch (technology market intelligence). 2012. https://www.abiresearch.com.
Allwood, Jens. 1977. “A critical look at speech act theory”. Logic, Pragmatics and Grammar, ed. by P. Dahl, 53–99. Lund. Studentlitteatur.
Austin, John Langshaw. 1962. How to Do Things with Words. Oxford: Oxford University Press.
Barlow, Michael. 2002. MonoConc Pro (MP 2.2) [Computer software]. Houston, Texas: Athelstan.
Baron, Naomi. 2008. Always On: Language in an Online and Mobile World. Oxford: Oxford University Press.
Baron, Naomi, Lauren Squires, Sara Tench, & Marshal Thompson. 2005. “Tethered or mobile? Use of away messages in instant messaging by American college students”. Mobile Communications: Re-Negotiation of the Social Sphere, ed. by Richard Ling & Per E. Pedersen, 293–311. London: Springer-Verlag.
Betti, Silvia. 2008. “He escrito te quiero en la pequeña pantalla (del móvil)”. Cuadernos Cervantes 12: 1–9.
Brown, Penelope & Stephen Levinson. 1978. “Universals in language usage: Politeness phenomena.” Questions and Politeness: Strategies in Social Interactions, ed. by Esther. N. Goody, 56–289. Cambridge: Cambridge University Press.
Bryant, J. Alison, Ashley Sanders-Jackson & Amber M. K. Smallwood. 2006. “IMing, text messaging, and adolescent social networks”. Journal of Computer-Mediated Communication 11(2): article 10. http://onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.2006.00028.x/full.
Burkhardt, Armin. 1990. “Speech act theory: the decline of a paradigm.” Speech Acts, Meaning, and Intentions: Critical Approaches to the Philosophy of John R. Searle, ed. by Armin Burkhardt, 91–128. New York: Walter de Gruyter.
Chen, Tao & Min-Yen Kan. 12 Dec. 2011. “Creating a live, public Short Message Service corpus: The NUS SMS Corpus”. Submitted to Language Resource and Evaluation Journal. https://arxiv.org/abs/1112.2468.
Clark, Herbert H. 1996. Using Language. Cambridge: Cambridge University Press.
Deumert, Ana & Sibabalwe Oscar Masinyana. 2008. “Mobile language choices. The use of English and isiXhosa in text messages (SMS): Evidence from bilingual South African sample”. English World-Wide 29(2): 117–147.
Fairon, Cédrick, Jean R. Klein & Sébastien Paumier. 2006. Le langage SMS. Étude d’un corpus informatisé à partir de l’enquête “Fáites don de vos SMS à la science”. Louvain, Belgium: CENTAL, UCL, Presses Universitaires de Louvain.
Fuhse, Jan A. 2009. “The Meaning Structure of Social Networks”. Sociological Theory 27(1): 51–69.
Grice, H. Paul. 1969. “Utterer’s meaning and intention”. Philosophical Review 78(2): 147–177. Reprinted in H. Paul Grice Studies in the Way of Words, 86–116. Cambridge, Mass.: Harvard University Press. http://www.jstor.org/stable/2184179?seq=1#page_scan_tab_contents
Habermas, Jürgen. 1976. “Was heißt Universalpragmatik?” Sprachpragmatik und Philosophie, ed. by K.-O. Apel, 174–272. Frankfurt am Main: Suhrkamp. [English, 1979, chap. 1] “What is universal pragmatics?”
Halion, Kevin. 1989. Deconstruction and Speech Act Theory: A Defence of the Distinction between Normal and Parasitic Speech Acts. PhD Dissertation, McMaster University, Canada. 11 Jan. 2011. http://www.e-anglais.com/parasitic_sa.html.
Hård af Segerstad, Ylva. 2005. “Language in SMS-a socio-linguistic view”. The Inside Text: (Social, Cultural and Design Perspectives on SMS), ed. by Richard Harper, Levsia Palen & Alex Taylor, 33–51. New York: Springer.
Ling, Richard. 2005. “The sociolinguistics of SMS: An analysis of SMS use by a random sample of Norwegians”. Mobile Communications: Re-negotiation of the Social Sphere, ed. by Rich Ling & Per E. Pedersen, 335–349. London: Springer Verlag
Ling, Richard. 2007. “The length of text messages and the use of predictive texting: Who uses it and how much do they have to say?” American University TESOL Working Papers, Number 4. 6 June 2009. http://www.american.edu/tesol/CMCLingFinal.pdf.
Ling, Richard & Naomi S. Baron. 2007. “Text messaging and IM. Linguistic comparison of American college data”. Journal of Language and Social Psychology 26(3): 291–298.
Ling, Richard & Donner, Jonathan. 2009. Mobile Communication. Cambridge, UK: Polity Press.
Lloyd, Clare & Patricia Gillard. 2010. “Discursive practices and creation of identity using the mobile phone”. Handbook of Research on Discourse Behavior and Digital Communication: Language Structures and Social Interaction, ed. by Rotimi Taiwo, vol. I, 1–17. InfoSci-on Demand: IGI Global.
Nastri, Jacqueline, Jorge Peña & Jeffrey T. Hancock. 2006. “The construction of away messages: A speech act analysis”. Journal of Computer-Mediated Communication, 11(4). article 7. 16 April 2011. http://onlinelibrary.wiley.com/doi/10.1111/j.1083-6101.2006.00306.x/full.
Plester, Beverly, Clare Wood & Victoria Bell. 2008. “Text Msg in school literacy: Does texting and knowledge of text abbreviations adversely affect children’s literacy attainment”? Literacy 42(3): 137–144.
Plester, Beverly, Clare Wood & Puja Joshi. 2009. “Exploring the relationship between children’s knowledge of text message abbreviations and school literacy outcomes”. British Journal of Developmental Psychology 27(1): 145–161.
Rosaldo, Michelle. 1982. “The things we do with words: Ilongot speech acts and speech act theory in philosophy”. Language in Society 11: 203–237.
Searle, John. 1965. “What is a speech act?” Language and Social Context, ed. by Pier PaoloGiglioli, 136–154. Harmondsworth, England: Penguin Books.
Searle, John. 1969. Speech Acts: An Essay in the Philosophy of Language. Cambridge: Cambridge University Press.
Searle, John. 1975. “Indirect speech acts”. Syntax and semantics, ed. by Peter Cole & Jerry Morgan, vol. 3: Speech Acts, 59–82. New York.
Searle, John. 1979. Expression and Meaning: Studies in the Theory of Speech Acts. New York, New York: Cambridge University Press.
Smith, Barry. 1990. “Towards a history of speech act theory.” Speech Acts, Meanings and Intentions. Critical Approaches to the Philosophy of John R. Searle, ed. by Armin Burkhardt, 29–61. Berlin & New York: Mouton de Gruyter.
Sotillo, Susana. 2010. “SMS texting practices and communicative intention.” Handbook of Research on Discourse Behavior and Digital Communication: Language Structures and Social Interaction, ed. by Rotimi Taiwo, vol. I, 252–265. InfoSci-onDemand, IGI Global.
Spilioti, Tereza. 2009. “Graphemic representations of text messaging: alphabet choice and code-switches in Greek SMS”. Pragmatics 19(3): 393–412.
Spilioti, Tereza. 2011. “Beyond genre: Closing and relational work in text messaging”. Digital Discourse, ed. by Crispin Thurlow & Kristine Mroczek, 67–87. Oxford University Press.
Strawson, Peter Frederick. 1964. “Intention and convention in speech acts”. Philosophical Review 73: 439–460.
Tagg, Caroline. 2009. A Corpus Linguistics Study of SMS Text Messaging. Ph.D. dissertation, University of Birmingham.
Tagliamonte, Sali A. & Derek Denis. 2008. “Linguistic ruin? LOL! Instant messaging and teen language.” American Speech 83(1): 3–34.
Thurlow, Crispin & Alex Brown. 2003. “Generation Txt? The sociolinguistics of young people’s text-messaging”. Discourse Analysis Online 1(1). 7 Dec. 2007. http://extra.shu.ac.uk/daol/articles/v1/n1/a3/thurlow2002003-paper.html.
Thurlow, Crispin & Michele Poff. 2011. “The language of text messaging.” Handbook of the Pragmatics of CMC, ed. by Susan C. Herring, Dieter Stein & Tuija Virtanen, 1–22. Berlin & New York: Mouton. 6 Sept. 2011. http://nl.ijs.si/janes/wp-content/uploads/2014/09/thurlowpoff11.pdf.
Tsai, I-Ni & Huang, Chu Ren. 2003. ”The semantics of onomatopoeic speech act verbs”. Institute of Linguistics, Academia Sinica. Language, Information and Computation: Proceedings of the 17th Pacific Asia Conference, 1–3 October, 2003, Sentosa, Singapore: COLIPS Publications.
Tsirulnik, Giselle. 2010. More than 7 trillion SMS messages will be sent in 2011: ABI Research, Mobile Marketer. 11 Jan. 2011. http://www.mobilemarketer.com/cms/news/research/8631.html.
Twitchell, Douglas P. & Jay F. Nunamaker, J. F. 2004. “Speech act profiling: A probabilistic method for analyzing persistent conversations and their participants”. Proceedings of the 37th Hawaii International Conference on System Sciences (HICSS-37). Los Alamitos: IEEE Press.
Vanderveken, Daniel & Kenneth MacQueen. 1990. “Lexical analysis of English performative verbs”. Meaning and Speech Acts, Volume 1: Principles of Language Use, 166–220. Cambridge University Press.
Wierzbicka, Anna. 1985. “Different cultures, different languages, different speech acts: Polish vs. English”. Journal of Pragmatics 9: 145–178.
Zarantonello, Gianluigi. 2001. “Nuovi media ed italiano parlato: gli sms (1) & (2)”. Comunitàzione.it. 2 Jan. 2007. http://www.comunitazione.it/leggi.asp?id_art=88&id_area=9.