Abstract

This research intends to discover gender differences in the usage of linguistic features in text messages by Pakistani students. Herring's approach to Computer-Mediated Discourse Analysis is used as the backbone of this research. In this qualitative research, a sample of 100 university students was selected. The sample provided a corpus of 300 text messages. Content analysis was used for coding and classification of the data, whereas descriptive statistics were used to find out percentages and frequencies. The data was classified as the messages sent by the males and those by females. Lexical features are classified as contraction, letter and number homophones, and initialism. Male students use more contractions, initialisms and clippings while female students use letter and number homophones more than the male students do. This study is important in terms of genderlects and their differences.

Key Words

Gender differences, Lexical features, SMS Text messaging

Introduction

Language has a noteworthy role in our culture and society. People use language to convey their emotions, feelings, messages and ideas. Most of the time, people are easily judged by the way they talk and none is identical in the way of talking. Everyone has his/her idiolect which differentiates his speech from that of others. Since both the genders in society use the language hence the relation between language and gender is inseparable (Coates, 1993). The variation between male and female talk exists in every community. These differences encompass pronunciation, vocabulary and morphology (Herring, 1994).   

 ‘Language and gender are one of the most discussed concerns of the contemporary era. Previous studies on gender differences are mostly on the spoken level. Only a few studies are available that cover the gender differences in written discourse. Herring (2003) states that gender differences are spotted in CMC i.e., on blogs, chatrooms, messengers, online discussion forums and SMS texts. Gender-based linguistic variations are easily detected in texting. (Anis, 2007). The same differences are found in face-to-face communication as well.

Face-to-face interaction is the verbal exchange of thoughts and opinions between two or more people. (Kaul, 1998). Both genders employ the use of linguistic choices in their conversation and many studies have dealt with this issue. Lakoff (1975) was among the pioneers who debated on this study. Poynton(1989) further discussed the issues of gender-based face-to-face communication. Tannen (1990), Gray (1992), Coates (1993), and Holmes (2008) have discussed the choices of articles, hedges, qualifiers, personal pronouns and by males in females in their communications.

According to all the previous researchers, there have been significant and visible gender-based linguistic differences. The same differences are exhibited in their written conversation. The difference in gender-based written conversation is the burning issue of the present era because CMC has left an overwhelming influence on the English language. Susan Herring, the leading linguist, has presented many theories on gender differences. (Herring, 1992, 1993, 1994, 1995, 1996, 1999, 2000s, 2002, 2003). She is of the view that there still exist many gender differences. 

Herring (1992, 1993 &1994) presented two sets of features differentiating the conversational styles of both males and females i.e., the adversarial style versus the attenuated style. The argumentative style of males is labeled by forceful statements, self-promotion, ridicule, haughty questions, the dominant form of verbs and insulting their opponent’s point of view. The women’s alleviated style is branded as weakened declarations using exhortations phrased as proposals, acknowledgements qualifiers, inclusive first-person plural pronouns, hedges and questions as a means to get an answer.  

Herring and Zelenkauskaite (2008) explored that the longer texts are mostly written by females because they like details and want to explain things in detail. Apart from these details, the use of non-standard English was also explored. They also investigated that females write longer texts using contractions in language. Herring and Zelenkauskaite (2008) further discovered that clippings, homophones, and phonetic spellings were more used by females as compared to males. Males, on the other hand, gave less importance to punctuation.

Crystal (2008) considers logographic components like “b” for “bee," etc., as the most noticeable characteristics of written spellings. Thurlow and Poff (2011) state that text (SMS) has very exclusive linguistic forms such as contractions, acronyms, shortenings, initialism, letter and number homophones and clippings and etc. 

In lexical features, punctuation is the most noticeable feature of texting. Baron (2008) argues that almost all the texts either don't have proper punctuation marks nor proper punctuation is not used. Bosco (2007) refers to this as creativity. According to him, the texters employ unique ideas and bring novelty to their written patterns in text messages. 

Kapidzic and Herring (2011), in another research, have discovered that males used more 1st person pronouns and articles whereas females used more emoticons. In addition, Kapidzic and Herring (2011, p. 57) suggested that, in CMC, young girls tend to be more reactive, emotional, friendly and good listeners whereas males are more assertive, initiating, leading and controlling. 

In the Pakistani context, Rafi (2008) discovered the morpho-syntactic and lexical selections of both genders in Pakistan. He discovered that both the genders varied in the intricacy of their SMS. Females’ SMS texts were more incomprehensible, longer and lexically denser than the texts of the males. Less use of emoticons was discovered in their chats with females and more use of emoticons was found in their chats with males. But in the case of men, more emoticons were used in their chats with men and less emoticons were used in their chats with women.

The Theoretical Framework of the Study

Herring (2004) developed a framework for the investigation of online texts. She called it "Computer-Mediated Discourse Analysis (CMDA) ."She coined the term CMDA in 1995 (Herring, 2001). CMDA helps researchers to hypothesize, design, understand and explain a CMDA research project. Explicitly, CMDA explains: 

a) How to pen worthy research questions; 

b) How to choose appropriate and adequate data; 

c) How to select appropriate sampling techniques; 

d) How to devise significant notions; and 

e) How to examine, understand, analyze and interpret the data

CMDA assists in explaining the internet chat as either synchronous or asynchronous. Hence

chat on online messengers is synchronous and SMS texting is asynchronous (Baron, 2004; Herring, 2004). 

Methodology

The present study is descriptive and quantitative in nature. In this study, the purposive sampling method is used to select the participants. 50 male and 50 female students (a total of 100 students) are selected using the purposive sampling method. The sample is confined to young male and female university students. The owning of a cell phone for minimum of three years was one of the criteria used in the selection of the students. The participants were relatively homogenous with respect to their cultural background (Pakistanis), academic background (postgraduates), and age background (21-24years old).In this study, 300 text messages collected from these 100 students were used for analysis. The respondents were requested to keep a record of the SMS chats which they had with their friends and relatives over a period of three days. The students were then requested to forward the same messages to the researchers on their mobile phones. Each participant was requested to send 3 messages from his/her shipped items; thus, 300 text messages were sent by the respondents to the researchers' mobile phones. 

Data Analysis

Data was analyzed quantitatively. Two methods of data analysis that were employed in this study were Content analysis and descriptive statistics.  




Content Analysis

According to Herring (2004), Content analysis is considered a key methodological tool for the analysis of electronic-mediated discourse. Coding is used for content analysis. Coding is a procedure of placing tags, lines, labels or names against the data. Data was first classified under two groupings i.e., the messages composed by males and messages composed by females. Lexical features were categorized into initialism, contraction, clipping, and letter and number homophones. The researcher assigned the codes to each lexical feature. 




Descriptive Statistics 

According to Payne & Payne (2004), descriptive statistics permit the researcher to define acquired info in simple, readable results. Hence, quantitative analysis in the shape of a frequency distribution table and simple percentages is used for the explanation of the occurrences of linguistic features of text data. 

Results and Interpretation

Table 1: Lexical Features in the Text Messages of Young Pakistani University Students

			Males		Females
Linguistic features			Frequency	%	Frequency	%	Total
Lexical Features	Initialism	Alphabetism	14	(58%)	10	(42 %)	24 (100%)
		Acronyms	6	(55%)	5	(45%)	11 (100%)
	Clipping		68	(52%)	64	(48%)	132(100%)
	Letter & Number Homophone		67	(29%)	167	(71%)	234(100%)
	Contraction		212	59%	150	(41%)	362(100%)

 




Initialism




Table 1 shows that the frequency of initialism was 20 (57%) in males' text messages whereas 15 (43%) in females' text messages. Both types of initialisms which are alphabetisms (like AOA, OMG and Fb) and acronyms (like lol, lmao), have been observed in the text messages data. The frequency of alphabetisms and acronyms in the text messages of males is higher than the frequency of alphabetisms and acronyms in the text messages of females. Females used alphabetisms and acronyms in 58% (10) and 42% (5) of their text messages while males used alphabetisms and acronyms in 55% (14) and 45% (6) of their text messages.

Initialisms that occurred most frequently in text messages data of male and female students are Lol for (laughing out loud), Aoa for (asslam o alaikum), Ppsc for (Punjab Public Service Commission), Sms for (Short Message Service), UE for (University of Education),  Hru for (how r u), OMG for (oh my God), Tc for (take care), TTYL for (talk to you later), FTF for (face to face),  AC for (air conditioner), FB for (Facebook), A.A or AoA for (assalam-o-Alaikum), IA for (Inshaa Allah) and Btw for (by the way).

Data reveals that words are adapted as initials from both English and Urdu languages. Texters have used Initialism like AoA (Assalam o Alaikum) and IA (InshaaAllah) from the Urdu language in their text messages. Results indicate that the phenomena of acronyms and alphabetism are not limited to the English language only.

The most famous and frequently occurring acronym noticed in the data is Lol for laughing out loud which is used for expressing mild amusement and the most commonly used alphabetism is AOA for Assalam alaikum. Omg, as the typical exclamative ?oh my god which represents surprise or shock was also used by both genders. Both genders mostly used initials for phrases in their text messages. Initials for sentences were rare.

Everyday expressions like 'take care,' 'assalam-o-alaikum' and 'peace be upon him' have also been used as an initialism. Such findings reveal that young males and females prefer abbreviated spellings to standard spellings which indicates the importance of brevity in SMS text messages.

Below are examples of initialism from students' text messages. An initialism is followed by the target expression in round brackets:

Example 1 (F): BTW (by the way) Y did U snd me a request on ma FB (facebook)????

Example 2 (M): OMG (oh my God) I cnt beliv ths.

Example 3 (F): Aoa (Assalam alaikum) I talked to mis amna wasif right now.

Example 4 (M): GTH (Go to hell) Waseem you are always out of shittttt.

Example 5 (F): Ttyl (talk to you later) wait plz

 

Clipping

Clipping is another lexical feature that is mostly used by texters to save time and space. Results of the study reveal that clipping was used in 52% (68) of the text messages of males. In contrast, it was used in 48% (64) of the text messages of females. The most frequent clippings that occurred in both genders' SMS text messages are given below:

ND, Nd, for the word ‘And’ (first letter a is clipped)

Ok, OK, oka, Oka, for ‘Okay’ (last letters are clipped)

Wil, WIL, wil for the word 'Will' (the last letter is clipped)

hav, Hav , for Have  (last letter e clipped)

Uni, UN, uni, univ for University (last letters are clipped)

comin for (coming), goin for (going), gatherin for (gathering), thinkin for (thinking) ( G is clipped)

ur, Ur, UR for the word ‘Your’ (first two letters ‘yo’ are clipped)

The results of the study show that (wil, uni, hav) are three most frequently used clipped words which fall under the category of back clipping and two (nd, ur) words under the category of fore-clipping. Another important finding is that in most of the cases only vowels have been clipped. Mostly contractions have been made by omitting vowels e.g vry (very), knw (know), nvr (never), hv (have), gd (good).

Consonants have also been omitted in the words like msgs (messages), wl (will), colg (college), aniversry (anniversary) and tomoro (tomorrow).

Examples of clipping from the text messages of males and females are given below:

Example 1 (M): welcome (welcome)! God bless u wth a healthy wealthy nd (and) prosperous life :)

Example 2(F): nd (and) even tht (that) more she has done well in studies. My lil sis (sister).

Example 3(M): M havin (having) lunch at Ashuu Murgh chany. Comin (coming) within few mints

Example 4(F): I mean as in ad (advertisement) it was written if u r nt intimated by ltr go to ur Dep (department) n cnfrm it.

Example 5 (M): train ur (your) eyes 2 see good.hav (have) a nice day.

 

Contraction       

Contraction is used 59% (212) in males’ text messages and 41% (150) in females’ text messages. The frequency of use of contractions in males’ text messages is higher than in females’ text messages. The collected data exhibits that males employ contractions in abundance in their SMS text messages. The most common contractions used in SMS text messages data by males and females are can’t, cant for (Cannot), thats, that’s for (That is), hw for (How), frm, Frm for (From), Ill, I ll, i’ll, for (I will/I’ll), bt, Bt for (But), Im, im,  I’m for (I am/I’m), Wth for (with), Ws for (was), Shud, shoud for ( should), Vry for (very), dont, dnt, Dnt, don,t for (Do not/don’t), its, ITS, Itz, for (It is /It’s), Nt for (Not), wht, wt, Wht, Wt for (What), abt for (about) and  yu for (you). Single-word contractions and two-word contractions are observed in both genders' text messages. Females have used an apostrophe in contractions whereas males have rarely used apostrophe marks.

Here are some examples of contractions from the text messages of males and females:

Example 1(M): hw (how) r u?

Example 2 (F): sm (some) ppl (people) in our lives are jst (just) like unwanted burden.

Example 3 (M): do smthng (something) abt (about) presentation.

Example 4 (F): there isnt (is not) any me. Im (I am) you. Dnt (do not) make up a separate me)

Example 5(M): wt (ahat) to do nw (now) dude?

 

Letter and Number Homophones

Letter and Number Homophones have been

 abundantly used in text messages by both genders. Letter homophone is a very common phenomena in today's SMS communication. Sometimes, letter and number homophones are mixed together in words. Where one part of a word is occupied by one category of homophones and other parts of the word is occupied by another category of homophones. Data shows that there is a trend that females use more letters and numbers of homophones than males. The percentage of letters and number and number homophones in the text messages of females is 71% (167) compared to 29% (67) of males' text messages, which is quite higher. Some examples of the combined/mixed-use of letter and number homophones are 'f9' for 'fine', 'w8' for 'wait', and 'b4' for 'before' are observed in the data. The significant numbers/digits used in SMS-Corpus as number homophones are "2", "4", "8", and "9". Only these four numbers have been frequently used as number homophones or parts of words.

The most frequently used letter and number homophones in the SMS text messages of males and females are given below:

R for (are), u for (you), b for (be), d for (the), v for (we), m for  (am), n for (and), y for (why), c for (see), 4 for (for, four), 2 for  (to, too, two), w8 for (wait), 4m for (from), in2 for (into), 2nite for (tonight), f9 for (fine), 2moro for (tomorrow), 2day for (today), b4 for (before) and 4wd for (forward).

Here are the examples of the number of homophones taken from males' and females' text messages data:

Examples 1 (M): yup we r on motorway 2 (to) Islamabad right now

Example 2 (F): Mine was 2 (too) good. Books were excellent? These gifts show us love and concern 4 us. Say thanks 2 aunti and uncle\Example 3(M): U r 2 (too) sweet and 2 (too) good bro. stay blessed

Example 4 (F): 4 [for] God sake! Shut ur mouth nd GO 2 [to] HELL!!!!

Example 5 (M): Aoa. Train ur eyes 2 (to) see good. Have nice day. Stay blessed. Subah bakhair.

Concerning the lexical features used by the students, except for letter and number homophone which appeared to be used more by the females than males, all of the other lexical features occurred more in the males’ text messages. The results have shown that initialism, contraction and clipping are used more by the males than their female counterparts. Males appeared to be common users of initialism including (acronyms and alphabetisms), clipping and contraction, while females appeared to be common users of letter and number homophones in their text messaging.




 

Table 2. Most Frequently used Lexical Features in the Text Messages of Males and Females

			Male		Females
Linguistic Features			Frequency	Percentage	Frequency	Percentage
Lexical Features	Initialism	Alphabetisms	14	3.8%	10	2.5%
		Acronyms	6	1.7%	5	1.3%
	Contraction	212	57.8 %	150	37.8%
	Clipping	68	18.5 %	64	16.2%
	Letter & Number Homophone	67	18.2%	167	42.2%
	Total	367	100%	396	100%

 




Table 2 reveals that in the text messages of males, the most frequently occurred lexical feature is contraction as compared to other lexical features. It was used by 57.8% of males in their text messages. Letter & number homophone occurred 18.2%, clipping 18.5%, alphabetisms 3.8 % and acronyms 1.7% in males' text messages. In the text messages of females, letter & number homophones were used 42.2 %, whereas contraction was used in 37.8%, clipping was used in 16.2 %, alphabetisms occurred in 2.5 % and acronyms appeared in 1.3%. Initialism which include alphabetisms and acronyms, was less in frequency and percentage as compared to other lexical features in both genders text messages.

Discussion

Data analysis reveals that there are obvious gender differences in the use of lexical features in SMS text messages of young Pakistani male and female students. One of the obvious gender differences is in students' initialism. Initialism which includes alphabetisms and acronyms, is a strong marker of gender differences in the students' text messaging. Males in this study used more of this feature in their text messages than their female counterparts. Even though brevity in text messaging does not allow the use of a complex and formal style of language, it has become a common feature of text messages owing to its ease of use and mutual intelligibility across the board among the texters. As such, initialism saves both time and space and focuses on two important aspects. Firstly, it explains that texters are conscious of the fact that they have limited space and characters available in one single text message. This knowledge of limitation makes them use initialism to say maximum in a single text message. Secondly, the receivers of the text messages are also at home with the use of initialism, so they can understand the context and content very well. This is because the sender and receiver co-share discursive practices and mutual interests. Some of the acronyms which appeared in the SMS text messages data were somewhat different from those appearing in previous literature. This supports Bodomo and Lee’s (2002) findings that there isn’t any fixed set of acronyms to be used by all texters in the world because acronyms are linked with the linguistic background of texters. This variation in acronyms emphasizes the role of setting or context in language use. 

Abbreviations, including clippings and contractions, are regarded as the most typical linguistic feature in the CMC language (Crystal, 2001). The males in this study used clippings and contractions more than female texters. The finding goes in accordance with the previous studies that prove that males use more abbreviated terms as compared to females (Baron, 2004; Hård af Segerstad, 2002; Ling, 2005; Rafi, 2008). However, this finding contradicts Herring's and Zelenkauskite's (2008). This finding also shows that students prefer using the contractions and the clippings, ignoring the standard spellings which specify the prominence of conciseness in SMS. Contraction is a common practice even on social websites where no restriction is placed on the word limit. But still, people prefer contractions. This may be assumed to be the core reason for using contractions in SMS text. Contractions not only include legitimate and conventional contractions which are allowed by the English language i.e. contracted negative and auxiliaries. Data shows that texters have also devised their own set of short forms or contractions. Therefore, the message becomes 'msg’ and the text has become 'txt.' 

Vowel dropping has been seen as a frequent phenomenon in SMS lexical short forms. It s also worth noting that history is repeating itself. Like the Hebrew language, consonants in present online communication are dominant and vowels are missing. People nowadays seem to omit vowels and focus on consonants for example,txt (text), fr For), yr (Your), pls (Please)  and changd (Changed). Such aspect of findings corresponds to Crystal (2008, p26), where states that texters know the basic principle of information theory that "consonants carry much more information than vowels do." This shows that vowel letters carry less information as compared to consonant letters. Therefore, vowels can be omitted from words without any loss of lexical and semantic information. Deletion of vowels is not only a strategy to save space and time but also exhibits the creativity of the users. Deletion is not only limited to vowels but consonants were also omitted like 'g' clipping. This finding also corresponds to Crystal's (2008, p. 46) theory that "final consonants are often dropped too. "As the last consonants are usually silent and their clipping doesn't cause a loss of information. The data maintains Crystal’s (2008) opinion that omission appears in texts when texters erase letters from the center of a word or drop the ending letter using the practice of clipping or contraction. It may be witnessed that texters missed/deleted either a letter from a word (e.g. yr, fr) or letters from a word (e.g. bday, govt, undstand). The data explains the fact that conciseness is the consequence of texting.

Despite the fact that contractions and clippings save time and effort, speed up the process of typing, and don't change the semantics of communication, still female texters don't seem to use them in their text messaging as much as male texters do. This may suggest that females tend to be more careful when they construct their messages than males. This may also indicate that females' language is more polite than males', a suggestion that concurs with previous literature on language and gender, such as the studies of Lakoff (1975), Tannen (1990), and Herring (1993, 1994).

Females in this study have shown a tendency towards employing more punctuation marks in their text messaging than males. This finding is consistent with Herring and Zelenkauskite's (2008) and Ling's (2005) findings that young Italian and Norwegian females employ more punctuation in their text messaging than males do. This shows that females tend to be more accurate and clear in their communication than males. In other words, they adhere more to standards and norms of the language in their text messages than their male counterparts. 

Some of the females have also made excessive use of punctuation marks in an unconventional way. Excessive use of punctuation is a new convention that has been brought about by electronic discourse (Brown & Yule, 1983). The use of these graphic features may indicate a sense of solidarity, closeness and intimacy. This finding is also in line with Herring and Zelenkauskite's (2008) claim that females are more expressive and emotional than males are. This concurs with previous literature that females are more concerned with relationships than their male counterparts (Herring, 1993; Tannen, 1990).

Communication.

Conclusion

Gender differentiation in the lexical features of SMS text messaging is a significant phenomenon. As there was a gap in the related literature on gender and SMS language, the goal of this study was to fill this gap by focusing on findings whether there is any difference in the language of SMS text messages used by males and females. This study concludes that Pakistani males and females use different lexical features.

Brevity is the most popular feature among the texters. The data shows that the informal and abbreviated language is used by the young students. While texting, the students tend to shorten their words and sentences as much as possible. However, the text messaging of the male and female students differs in lexical reduction and shortening. Males employ more initialisms, clippings and contractions in their messages than females. On the other hand, females have the tendency to use letters and number homophones more than males. This may indicate that the females are more sophisticated users of text messaging than the males. It may also indicate that the males are more experienced in writing text messaging, which requires speed and economy.  

This study demonstrates that gender has a very significant role to play in the process and that there exist noticeable differences in the use of linguistic features (lexical and typographical features) in SMS text messages.

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