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.) 86 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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- A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 87 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 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. A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 89 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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.) 90 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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.) 91 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 92 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 93 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 94 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 95 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 96 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 97 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 98 ELTALL : English Language Teaching, Applied Linguistics and Literature, Vol. 5 No. 1 (2024) 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 A Discourse Analysis of Cyber Socialising Interactions in English Among Students (Tiyiselani Ndukwani, et al.) 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. 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