







































English Language Teaching,  
Applied Linguistics and Literature 

Vol. 5 No. 1 (2024) 
Available online at https://jurnal.iainponorogo.ac.id/index.php/eltall 

 
 

85 

ELTALL 

 

A DISCOURSE ANALYSIS OF CYBER SOCIALISING 

INTERACTIONS IN ENGLISH AMONG STUDENTS 

 

 

Tiyiselani Ndukwani 

University of Johannesburg, South Africa 

ndukwanit@uj.ac.za 

 

Runash Ramhurry 

University of Johannesburg, South Africa 

runashr@uj.ac.za 

 

 

ABSTRACT 

The influence of modern technology and engagement in cyber socialising have become a 
prominent part of modern communication. A new learning pedagogy with proper 
guidelines is needed to assist users to engage with social networking platforms 
efficiently. The researcher investigated discourse analysis involving participants to 
answer questions about both the contextual application of the language, and the 
functions and results of aspects pertaining to discourse such as diction, cohesion, and 
metaphors. The researcher employs a qualitative approach in this study. The study 
randomly sampled 80 students from a University of Technology (UoT) in Gauteng to 
participate in qualitative discource analysis of communication using Facebook, 
WhatApp and Twitter texts. The methods of data elicitation embraced extracts from 
Facebook, WhatsApp and Twitter texts provided by 80 participants. Statistics were used 
to present the findings of the quantitative data which included mainly frequency of 
certain aspects pertaining to discourse. Data were collected via email and texts were 
numbered according to the participants. These texts remain anonymous and the 
identities of the participants were concealed. The study found that the language used on 
Facebook, WhatsApp and Twitter was characterised by the use of emoji, low register 
words, code-switching few spelling errors and the modern tendency to shorten words by 
using clipping and number homophones which are not seen as errors but a unique style 
of writing. Facebook, WhatsApp and Twitter remain three popular communication sites 
and discourse surfaces since it is important for users to communicate meaningfully even 
when using excessive punctuation to indicate excitement and emoji to communicate 
emotions.  
 

 

Keywords: Technology, social media, Internet, cyber socialising, discourse, content 

analysis, Facebook, WhatsApp, Twitter 

 



A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 

 
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INTRODUCTION 

The use of technology to communicate is very popular among students. A 

new pedagogy is needed to help students to use social platforms for 

educational purposes (Karal, Kokoc & Cakir, 2017:677). This study endeavored 

to provide in the pedagogical and academic needs to use the platforms 

responsibly and effectively, identifying cohesion and coherence of language 

used in social context as part of the focus on discourse (Gee, 2010:5). The world 

is dynamically influenced by the advancement of modern technology and its 

effect on language development and language usage as it is involved not only 

in social informal interaction, but for business purposes. Electronic devices 

embracing tablets, smartphones and computers have granted students the 

opportunity to engage in communication even for entertainment purposes and 

Kumar and Sharma (2016:52) are of the view that English is increasingly used 

by these users globally, since the various language speakers of diverse 

languages can connect with one another to share knowledge (Kumar & Sharma, 

2016:52). 

On virtual, social platforms, users do not only communicate, but also 

share personal experiences, and respond to the posts of other users. Internet 

platforms such as Facebook, WhatsApp and Twitter are not only used to 

communicate informally, but they are also used as promotion tools by 

marketers, to share information. The language used on the se platforms can 

affect the e-reputation and correctness and appropriateness are thus also 

aspects that must be considered (Kumar & Sharma, 2016:52). 

As a lecturer, it is important to examine how students make use of cyber 

socialising, because students’ reflection on using discourse as part of cyber 

socialising can influence the way they communicate academically. The content 

of their communication is also a source of interest to determine whether they 

use trolling, why they use it and the frequency of this phenomenon. Trolling is 

defined as an act of posting inflammatory information, and extraneous 

messages on a social network site to provoke readers and solicit an emotional 

response disrupting the obvious topic of discussion. A troll creates discord by 

starting a quarrel, posting controversial information to cause emotional 

response (Merritt, 2012:3). This is underscored by Bock (2014:68) who asserts 

that conventionalised genres should be interpreted from a discourse-analytical 

perspective. 

Literature has highlighted several reasons why we study discourse 

analysis. Previous studies of Stubbs (1983: 98) focused on how language is used 

and how humans use language to communicate. Lecturers focused on how they 

could teach their students to improve their writing. Surveys such as those 

conducted by Zappavigna (2012:3) found that cyber socialising is user-



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generated content that is self-publicised and it supports ambient, interpersonal 

connection. Since it is length delimiting communication, the use of language is 

affected, and a new way of self-expression occurs. Users need to be equipped to 

use the language in a succinct way correctly as this communication can exert an 

influence in information generation, linguistic self-expression and the 

involvement of electronic devices such as smartphones focuses attention on the 

importance of corpus linguistics, as information can be spread widely and 

instantaneously. Internet users enjoy being part of the peer in-group and if the 

group enjoys using the Internet platform, there will be those who follow and 

interact (Thurlow & Poff, 2012). 

Apart from focusing on the use of the modern technological Internet 

communication sites, the focus is also on the English language used in 

discourse. It has also been observed that the poor English proficiency in 

speaking and writing impacts academic performance and that language 

learning central to meaningful interaction whether spoken or written (Van der 

Walt, Evans & Kilfoil, 2010:97). It should however be noted that the idea was 

not to conduct an Error Analysis (EA) by analysing the language errors since 

these are an undeniable part of cyber chatting (Bock, 2014). The focus was more 

on discourse and aspects pertaining to discourse as well as content. 

Recent research in promoting English language proficiency skills (Sadeghi 

& Richards, 2015:210) has focused renewed interest in upgrading learners’ 

speaking and writing skills. English is used globally to connect and it facilitates 

communication when trading and marketing. Language is socially constructed, 

and the construction of meaning is biased and defined relative to the Internet 

users’ social and cultural experiences, involving relations of power. The use of 

these Internet platforms thus also involves social expression and using 

language to influence users by deliberately misleading people or coaxing them 

to react in a certain manner (Saichaie, 2011:2). 

 

METHODS 

This study uses qualitative approach. Kumar (2016:12) concurs with the 

fact that a study is classified as a qualitative study when the researcher wants to 

quantify the variation of phenomena. Creswell (2009:55) maintains that 

quantitative research methods are of paramount importance, because it delimits 

the focus of the research study, with regard to the sample size and semi-

structured interviews which are inclusive. In quantitative research analysis does 

not begin until all data have been collected and converted into numbers. 

Quantitave research tends to rely more on deductive, moving from the general 

to the specific. In this study, the researcher aimed at statistical results in order to 



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88 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 

 

get answers for the research questions. The study involved statistic gained from 

the frequencies of internet discourse use. 

The study was conducted at a UoT in Gauteng. Most of the participants 

reside in Soshanguve which is a township found in the north of Pretoria. 

Soshanguve was a town where Black people from different backgrounds were 

forced to reside together, far from urban areas. The City of Tshwane (2008) 

maintains that Soshanguve was established during the Apartheid era in 1974. 

The name Soshanguve comes from the first letters of the languages spoken in its 

township, namely; So (Sotho), Sha (Shangaan), Ngu (Nguni), and Ve (Venda). 

The Soshanguve Township is mainly a residential area with education 

facilities and shops. According to the figures from the GDE (2003), the township 

has about 50 schools which fall under the Tshwane North District. It includes 27 

primary schools, 13 middle schools and 10 secondary schools. The selected 

University of Technology (UoT), previously known as Technicon Northern 

Gauteng (TNG) is based in Soshanguve. 

The participants who submitted the Internet platform texts consisted of 80 

participants, 45 female (56%) and 35 male (44%). Their ages ranged from 20 to 

35. The participants were all enrolled students at a UoT in South Africa. The 

participants came from three different courses and different levels of study, 

starting from level 1 to level 3 and also from different cultural orientation. They 

were randomly sampled for the extract analysis participation. Only students 

who were active on the three SNSs involved in this study were sampled. The 

researcher made use of personal invitations to approach the participants who 

participated voluntarily. 

The researcher wrote letters to acquire consent from the university and 

participants before data collection. The researcher aimed for transparency and 

assured the participants that they could withdraw at any time would they wish 

to do so (McAreavey & Muir, 2011:394). Furthermore, the researcher explained 

to the students their typical roles in this study. No student experienced harm in 

this study as a result of their participation. The researcher made sure that all 

participants were safe and are not at risk. Honesty and respect were key in the 

study. Adhering to all the ethical guidelines serves as standards about the 

honesty and trustworthiness of the data collected and data analysis (Silverman, 

2000:201). Participants and texts remained anonymous. Photos were deleted or 

covered to protect their identity. All the data sheets have been collected and 

will be stored in a secure place in the researcher’s office for three years and 

deleted after that period. Any information that was obtained in connection with 

this study and that could be identified with the participants remain 

confidential. 

 

 



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FINDINGS AND DISCUSSION 

 It must be noted that the frequencies derived from the text refer to the 

number of users that used that specific phenomenon and not the number of 

occurrences of the phenomenon within the text as the focus was more on the 

use of the discourse as phenomenon. Because the length of the text varied, it 

also made the counting of the phenomenon within the texts unnecessary as a 

longer text will obviously provide the user the opportunity to use the 

phenomenon more. These salient aspects are discussed next. It is an estimate of 

internal consistency reliability. All reliability estimates are estimates of 

reliability. Figure 1 below provides a summary of the statistics of the three 

technological platforms and the frequencies. 

 
Figure 1. Total scores for the various aspects pertaining to discourse 

 



A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 

 
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Figure 2. Referencing 

 

The researcher investigated the use of referencing on social networks. 

Referencing in this instance refers to how the writer introduces participants, 

and keeps track of them throughout the text (Eggins, 1994:95). It is a 

relationship that exists on the semantic level. All referencing types were taken 

into consideration. The results indicated that students mostly used anaphoric 

referencing on WhatsApp (72,5%), followed by Facebook (60%) and very little 

on Twitter (56,25%) as indicated in the graph above. Anaphoric references are 

explained by Taylor (2020) as words in texts that refer back to other aspects 

within the text to create meaning. Little evidence was found on exophoric 

references. Exophoric references refer to aspects outside the discourse or shared 

knowledge between the interlocutors (Taylor, 2020). The evidence of 

referencing is crucial in that it testifies to the fact that the anaphoric referencing 

used pertains more to the relationship within the specific piece of 

communication. Users thus did not refer to other participants outside the text, 

but kept to a closed group when communicating designating an atmosphere of 

intimacy. This finding also confirms the finding by Bock (2014). The 

communication stays linked with the interlocutors within the text and they 

focus on the topic they discuss. 

 
Figure 3. The use of clipping in Social Networking Services (SNNs) 

 

The results showed that only 8,75% of the students used clipping on 

WhatsApp, 3,75% on Facebook and 5% on Twitter. Clipping was used as a 

means to create a shorter text and to be concise and communicate the text using 

as few characters as possible. It is interesting to note that clipping was used by 

% Facebook % WhatsApp % Twitter

Referencing 60 72,5 56,25

0

20

40

60

80

Referencing

% Facebook % WhatsApp % Twitter

Clipping 3,75 8,75 5

0

5

10

Clipping



A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 

 
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the SNS users the most on WhatsApp, and this is in line with the general 

description of Twitter using the smallest number of characters since it is a 

medium that is used for a different purpose than e.g. Facebook and WhatsApp. 

The nature of Twitter to provide shorter tweets limit the user to use only a few 

characters. The word ‘res’ is used to refer to residence. Another example is the 

use of ‘u’ for ‘yo. 

 
Figure 4. The use of substitution on Social Networking services (SNSs) 

 

Substitution is used to avoid repetition in a text, and it is a relationship 

that exists on the lexicon- grammatical level between linguistic items, such as 

words or phrases. According to Bloor and Bloor (1995: 96), the main reason for 

using substitution is to fight monotony and to avoid repetition. The use of 

substitution by students on WhatsApp was at 7,5%, students do not use 

substitution on Facebook and Twitter as reflected in the graph above. This 

finding corresponds with the need to keep the text short and concise.  

 
Figure 5. The use of ellipsis in Social Networking Services (SNNs) 

 

The researcher investigated the use of ellipsis on social networks. Ellipsis 

is the act of deliberately removing a linguistic unit from a piece of discourse. It 

has the function of replacing words, sentences and stimulating thinking. Ellipsis 

are “words deliberately left out of a sentence when the meaning is still clear” 

(Harmer, 2004:24). The results indicated that ellipsis was not used consistently 

by students on WhatsApp, Facebook and Twitter as indicated in the graph 

below. It is interesting to note that this phenomenon is not well represented in 

Internet communication. The absence of the use of ellipsis can probably be 

ascribed to the need to stay short and to the point. 

% Facebook % WhatsApp % Twitter

Substitution 1,25 7,5 1,25

0

2

4

6

8

Substitution

% Facebook % WhatsApp % Twitter

Ellipsis 2,5 0 0

0

1

2

3

Ellipsis



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Figure 6. The use of number homophones Social Networking Services (SNSs) 

 

Crystal (2008) is of the opinion that texting contains examples of number 

homophones. She explains  this phenomenon as laziness and she says this 

nonstandard way of writing is criticised yet it has become a cool feature that 

has become part and parcel of daily communication. Messages on Facebook, 

WhatsApp and Twitter are also part of texting and are a succinct way of sharing 

messages     and information. She claims that abbreviations such as lol (laughing 

out loud) and brb (be right back) are evidence of an awareness of sensitivity 

towards other users’ needs. She avers that the potential benefits of texting are 

ignored and purists complain about poor literacy. Instead she is of the view that 

new opportunities to communicate and use the language even in modern form 

with abbreviations and shortening by omitting letters must be seen as 

additional opportunities to hone writing skills. Students can develop a strong 

sense of when it is appropriate to use the abbreviations and when not and they 

must just concentrate to use these appropriate to the context. 

The results of this study showed that only few students made use of 

number homophones on Facebook (7,5%), WhatsApp (7,5%), and Twitter (5%) 

as indicated in the graph above. It was interesting that WhatsApp users were 

recorded to be more frequent users of number homophones. This finding can 

possibly be explained by stating that since WhatsApp communication often 

embraces an opening of content and a closing section; there is a need to keep 

the conversation short. One would expect Tweets to have more examples of 

number homophones but in this case, WhatsApp and Facebook users used this 

phenomenon more.  

 
Figure 7. The use of trolling in Social Network Services (SNSs) 

% Facebook % WhatsApp % Twitter

Number homophones 7,5 7,5 5

0

2

4

6

8

Number homophones

% Facebook % WhatsApp % Twitter

Trolling 37,5 11,25 33,75

0

10

20

30

40

Trolling



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Internet trolls refer to an online subculture who posts upsetting or 

shocking content, and spreads false information for their own enjoyment 

causing quarrels that upset readers. Trolls deliberately annoy others to get 

reaction (Merrit, 2012:54). Shringapure and Dharam (2019) conducted research 

on trolling and found that there are specific reasons for trolling such as doing it 

for fun and crossing limits; trolling due to boredom, because of a need to take 

revenge or to be amused; self-assertion, in an attempt to assert themselves and 

is a characteristic of mentally weak people; lack of legal knowledge, ignoring 

that there is a limit to self-expression; false assurance of security, as they think 

they can even use a false name as nobody will catch them which is a false 

assumption; violation of privacy, ignoring The Information Technology Act 

2000 Section 66E which was created to protect users’ privacy; and publishing 

offensive material that is punishable according to Act 2000 Section 67. 

Lascivious appeals are used to corrupt Internet users and also embrace 

offensive comments regardless of whether these are sexual in natu  

From the research findings, trolling occurs mostly on Facebook (37,5%) 

and Twitter (33,75%). Only few students did trolling on WhatsApp (11,25%). 

This is an interesting finding in that WhatsApp is viewed as a more 

conversational medium.  

 
Figure 8. The use of emoji in Social Networking Services (SNSs) 

 

The use of emoji is very high in all the SNSs investigated. The results 

showed that 52,5% of students made use of emoji when communicating on 

Facebook, 43,75 % of student participants made use of emoji on WhatsApp and 

31,25 % of students used them when engaging on Twitter. The following extract 

is an example of how emoji are used in SNSs. It was revealed that of the three 

SNSs involved Facebook had the most emoji use. Twitter relied more on written 

words. This is an interesting finding in that it can be asserted that Facebook and 

WhatsApp communication have a more conversational nature, and emoji are 

used more frequently. The character limitation might also influence the 

limitation to emoji use on Twitter. 

Emoji add an additional emotional appeal to confirm the content of the 

text as can be seen in the following text where the praying hands and face with 

% Facebook % WhatsApp % Twitter

Emoji 52,5 43,75 31,25

0

20

40

60

Emoji



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the heart were used, to create a pleading atmosphere adding some soul to the 

text. The finding that this phenomenon when compared to other discourse 

features, was so prominent, proves that emoji have become an integral part of 

communication on Internet platforms and is a new way of incorporating 

pictures to strengthen messages. They are fit-for-purpose features as part of 

digital textspeak, but their function is not to usurp language, but to add 

emotional impetus and cues. Furthermore, they also link with the more cryptic 

way of writing (Alshenqeeti, 2016). 

Alshenqeeti (2016) asserts that emoji can represent a feeling or even a 

word and are strung together with words to create a sentence carrying 

meaning. He asserts that the assumption that emoji are   devolving language 

ignores the humans’ need for non-verbal information, as emoji are used by 

technologically savvy users. In addition, they are universal and can be 

understood by speakers of different languages. This is of particular interest in 

this study as the users involved as participants were all from different cultural 

denominations and communicated with people who did not always share the 

same home language. In this study the researcher found emoji to be a means of 

reaching people of other cultural denominations. Emoji were also excessively 

used by those who incorporate them in their discourse and this tendency links 

with the excessive use of punctuation to communicate strong emotions. 

 
Figure 9. The use of excessive punctuation in Social Networking services (SNSs) 

 

Beck (2018) asserts that digital communication is undergoing 

“exclamation-point inflation”, referring to the use of excessive punctuation. It is 

deemed a quirk of social media to use excessive exclamation points, all caps and 

repetition of letters. Garber (2014) advocates the use of exclamation points to 

indicate emotional colouring, enthusiasm and excitement. She mentions the 

movement from purely lexical-based communication to image-based 

communication in modern times and claims that the use of punctuation is 

strongly linked with visual communication. 

The use of excessive punctuation in SNSs was investigated. The graph 

above (Figure 9, provides the results of how excessive punctuation is used on 

social networking platforms. The use of excessive punctuation (repetition of a 

% Facebook % WhatsApp % Twitter

Excessive punctuation 22,5 16,25 10

0

10

20

30

Excessive punctuation



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single punctuation marks) was recorded on WhatsApp as 16,25% compared to 

22,5% on Facebook and 10% by Twitter users. It emerged from the analysis that 

Facebook posts revealed the most instances of use of excessive punctuation. It 

can be deduced that excessive punctuation has become part of the Facebook 

and conversational communication. 

 
Figure 10. Code-switching in Social Networking Services (SNSs) 

 

Cardenas-Claros and Isharyanti (2009) investigated code-switching and 

the influence of culture in Computer Mediated Communication (CMC) and 

they report that the use of English on Internet platforms has increased 

considerably. They claim that English is used to communicate especially in the 

case where the Internet users belong to different cultural groups and have 

different home languages. Code-switching occurs from the mother tongue to 

English. Language diversity is a characteristic of South African Internet users 

who can belong to one of the 11 official languages in South Africa (Da Costa, 

Dyers & Mheta, 2014). The participants incorporated in this study are all 

English second language speakers and they showed the tendency to code-

switch. 

When students attempted to connect on Facebook, WhatsApp and Twitter, 

code-switching was also recognised, since all users did not belong to the same 

mother tongue. Different ethnicities are recognised as they all connect using 

English. Comparing the three SNSs, code-switching was used mostly on 

WhatsApp (31, 25%), followed by Facebook (27,5%), and Twitter (21,25%) 

revealed the lowest percentage. Interesting to note that code-switching did not 

surface as a prominent theme in the qualitative data pertaining to all three the 

platforms in Chapter 4 (Responses on code-switching on Twitter were silent). 

Since WhatsApp leans more towards having conversations, it did not 

come as a surprise that code- switching was more prevalent on WhatsApp as 

Internet communication platform. This finding was confirmed by Andújar-Vaca 

and Cruz-Martínez (2017) who maintains that WhatsApp is useful 

communication tool to socialise and become educated. It also echoes the 

opinion of Kwon and      Schallert (2016:138) that code-switching enables 

% Facebook % WhatsApp % Twitter

Code-switching 27,5 31,25 21,25

0

10

20

30

40

Code-switching



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Internet users of various digital platforms to connect and understand one 

another. 

 
Figure 11. The use of conversational opening and closing on social network Services 

(SNSs 

 

Yule (2018) discusses conversational analysis as part of discourse. 

Conversational analysis involves turn-taking during conversations that are 

opened and closed. In written communication the moment of silence is not so 

obvious, but can be observed in the time taken to respond. Alli and Kootbodien 

(2017) maintain that WhatsApp is the leading Internet communication medium 

and they also assert that Facebook and Twitter take a backseat to WhatsApp 

communication as preferred medium. Communication barriers also ensue when 

messages and pictures sent are interpreted differently, nevertheless they 

consider WhatsApp an effective communication medium. 

The results presented in Figure 5.11 above show how conversational 

opening and closing are used on SNSs. Facebook users (13,75%),WhatsApp 

users (16,25%) and Twitter (5%) users all used the conversational opening and 

closing. WhatsApp had the most instances of opening and closing of 

conversations. This finding can be explained by viewing WhatsApp as instant 

message service and the conversational nature allowing more characters than 

Twitter. Interesting is that Facebook and WhatsApp scores were close. It was 

revealed that Facebook users also sometimes tend to use opening. 

 
Figure 12. Sequencing in Social Networking Services (SNSs) 

 

Yule (2018) asserts that sequencing also deals with coherence of messages, 

since it is all about how users make sense of what they hear. In order to make 

% Facebook % WhatsApp % Twitter

Conversational opening
and closing

13,75 16,25 5

0
5

10
15
20

Conversational opening and closing

% Facebook % WhatsApp % Twitter

Sequencing 12,5 20 11,25

0

10

20

30

Sequencing



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sense there must be order and a sequence to follow including a beginning 

middle and end. Turn-taking takes place and pauses were also observed. 

The use of sequencing on social network discourse was investigated by the 

researcher and the findings showed that there is more instances of sequencing 

on WhatsApp discourse when compared to Facebook and Twitter as shown 

above. Conversations on WhatsApp revealed that there was turn- taking and 

order is clearly observed of the opening, the content and the closing in most of 

the instances. Facebook communication revealed that the pauses to respond 

were not always followed up immediately except for when the Facebook 

messenger is used. As for Twitter, the responses were more cryptic because of 

character restriction. 

 
Figure 13. Metaphors and similes in Social Network Services (SNSs) 

 

Herrmann (2016) assert that metaphors are highly important as 

communicative devices. Metaphors are often linked with power interests and 

there is a comparison between two aspects where one is assigned power. 

Metaphors are obscure and can hide and limit perspectives. CMC promotes a 

sense of belonging togetherness and participation and bolsters ties via 

communication. Online platforms must also be culturally relevant and it stands 

to reason that metaphors that are used must be interpretable by the parties 

involved to create a platform of shred meaning. These platforms demand 

fellowship, tolerance and patience, since cyberbullying discrimination and 

intimidation are obstacles to sound Internet communication. 

The researcher investigated the use of metaphors and comparison during 

communication on SNSs. Metaphors deal with the meaning beyond the text 

(Herrmann, 2016). The findings revealed that 8,75% of Facebook, 3,75% of 

WhatsApp and 2,5% of Twitter users used metaphors and similes. Here all the 

texts were scrutinised for examples. 

This finding confirmed what was found in the textual, as few examples of 

metaphors and similes were found as proof of linguistic operation on an 

advanced an abstract level. This finding revealed that the most examples of 

metaphors and similes as figurative language. 

% Facebook % WhatsApp % Twitter

Metaphors and similes 8,75 3,75 2,5

0

5

10

Metaphors and similes



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Figure 14. The use of high and low register words in Social networking Services (SNSs) 

 

The researcher investigated the use of high register words on SNSs by 

students. Yule (2018) defines register as a conventional use of language linked 

with a specific context. Language linked with specific fields is called jargon e.g. 

wicket is used in cricket. Register refers to a variety of language preferred to 

create a formal or informal atmosphere (Baker, 2011). Baker (2011) identifies the 

parameters of register by referring to: 

• Field – Linguistic choices are influenced by whether the field involved is a 

formal setting requiring high register words or informal requiring lower 

register; 

• Tenor – This an abstract term referring to the interpersonal relationships 

will influence whether more formal language must be used. The level of 

formality is influenced by the age and even the ethnicity of speakers; 

• Mode – This term refers to the medium of transmission that will bear an 

influence on the level of formality. 

Crystal (2014) asserts that the novelty of Electronically Mediated 

Communication (EMC) offer new communicative opportunities; language is 

less complex (more informal with lower register and slang), contains spelling 

errors and social chitchat. The text is manipulated by the senders and semantic 

differences are observable when comparing traditional written and Internet 

texts. She also asserts that EMC is characterised by both formal and informal 

vocabulary all appearing on one page. This finding was confirmed by the data 

accumulated from the Facebook, WhatsApp and Twitter texts. 

High register words refer to more formal words and more elaborated 

language (Crystal, 2014). The results revealed that students used high register 

words on Facebook (5%), WhatsApp (3,75%) and the most on Twitter (16,25%). 

This finding is confirmed by Mafhouz (2018) who found that Twitter users tend 

to engage with higher register (more advanced and formal vocabulary). 

Participant 16 used e.g. the word blighted meaning spoiling in the negative 

sense. Twitter had the highest percentage of high register words. The examples 

of high register words mentioned in the metaphor below also revealed evidence 

of high register such as weaknesses (WhatsApp) and financially (Twitter). 

% Facebook % WhatsApp % Twitter

High register 5 3,75 16,25

0

5

10

15

20

High register



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99 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 

 

Furthermore, there was the word classism which occurred on Twitter used by 

participant 19. Twitter had more examples of high register words than the other 

platforms and it emerged that users tend to use more sophisticated language.  

 
Figure 15. The use of low register words in Social Network Services (SNSs) 

 

The researcher investigated the use of low register words in Social 

Networking Services (SNSs) as employed by students. In this instance he 

counted the words manually inside the texts. Low register words refer to 

informal and slang words such as taboo words e.g. ‘shit’ (Yule, 2018). Pedersen 

(2007) did a study on the use of slang in British English. It incorporates slang 

and colloquialisms. Slang is said to intrude Internet communication and also 

has an expiry date as it is followed by new examples after a period. Anderson 

and Trudgill (1990) maintain that slang is often identified as bad language and 

is chosen by people who assign a certain status to it. Slang is about coming up 

with new meanings and versions for words rather than inventing new words. 

The gap between males and females using slang is closing, since it was found 

that more females used slang especially those belonging to feminist movements. 

 

CONCLUSION 

This study has achieved its objectives of investigating discourse on social 

media by focusing on three specific platforms viz. Facebook, WhatsApp and 

Twitter. The discourse analysis yielded interesting and useful results that can 

guide Internet users on how to behave on Internet platforms and how to protect 

themselves. The new media need new training. Students and lecturers must be 

open to learn and embrace new technological developments. It emerged from 

the study that users of SNSs (the three studied) did not say much on the legal 

implication of using these networks. Legal steps against users can cause many 

challenges and must be an aspect that everyone must consistence.  

 

 

 

 

 

% Facebook % WhatsApp % Twitter

Low register 98,5 100 98,5

97

98

99

100

101

Low register



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