https:doi.org/10.25312/j.9777
Prisca Boniphace Makulilo https://orcid.org/0009-0008-7812-6320 College of Business Education
e-mail: prismakulilo78@gmail.com
Wpływ korekty na przejrzystość przekazu w akademickiej komunikacji WhatsApp: studium przypadku College of Business Education w Tanzanii
Abstract
This study examines how proofreading behaviours affect clarity in communicating and interpreting messages in higher learning WhatsApp groups, focusing on the CBE-ALL-STAFF group at the Dar es Salaam campus. Using a qualitative case study with 60 academic and non-academic staff of diverse ages, professions, and digital skills, data were gathered through interviews, focus group discussions, and analysis of 100 authentic WhatsApp messages. NVivo 12 coding revealed five themes: professional image, misinterpretation, context- dependent conduct, emotional effects, and time inefficiencies. Findings show strict proofreading in formal contexts, especially among academics, while informal settings allow more flexibility. Omissions often led to confusion, reputational harm, and redundant follow-ups. The study highlights proofreading as vital for clarity and professionalism in academic digital communication and suggests that institutions enhance norms through literacy programs and context-sensitive training.
Keywords: proofreading, mobile messaging, WhatsApp groups, digital communication
Streszczenie
Badanie analizuje wpływ zachowań związanych z korektą tekstu na jasność komunikacji i interpretacji wiadomości w grupach WhatsApp w szkolnictwie wyższym, ze szczególnym uwzględnieniem grupy CBE-ALL-STAFF na kampusie w Dar es Salaam. W ramach jakościowego studium przypadku przebadano 60 pracowników akademickich i nieakademickich w różnym wieku, zróżnicowanych zawodowo i pod względem kompetencji cyfrowych. Dane zebrano poprzez wywiady, dyskusje fokusowe oraz analizę 100 autentycznych wiadomości z WhatsAppa. Analiza w NVivo 12 ujawniła pięć głównych tematów: wizerunek zawodowy, błędne interpretacje, zachowania zależne od kontekstu, efekty emocjonalne oraz nieefektywność czasową. Wyniki pokazują, że rygorystyczna korekta dotyczy głównie komunikacji formalnej, zwłaszcza wśród pracowników akademickich, podczas gdy w sytuacjach nieformalnych występuje większa swoboda. Zaniedbania w korekcie prowadziły do nieporozumień, szkód wizerunkowych oraz zbędnych działań następczych. Badanie podkreśla kluczową rolę korekty w zapewnianiu jasności i profesjonalizmu w akademickiej komunikacji cyfrowej oraz sugeruje wprowadzenie programów podnoszenia kompetencji językowych i szkoleń dostosowanych do kontekstu.
Słowa kluczowe: korekta, wiadomości mobilne, grupy WhatsApp, komunikacja cyfrowa
The advent of mobile messaging has revolutionized communication in personal, academic, and professional realms (Verheijen, 2013). Messaging apps like WhatsApp, Telegram, Facebook Messenger, and SMS have emerged as universal tools of daily interaction through their immediacy, convenience, and usability (Moses, 2014; García-Peñalvo, Conde, 2015). These apps facilitate fast exchange of messages over long distances, transforming how people socialize in formal and informal contexts (Williams, Brown, 2021). The convenience and speed of mobile messaging are, however, often at the cost of linguistic accuracy (Marin, 2022). Various studies highlight how users tend to neglect writing rules like grammar, punctuation, and sentence structure, potentially breaking down communication in formal and professional contexts (Nobles, Paganucci, 2015; Sibarani, Marbun, Hartati, 2024).
In view of the pervasiveness of mobile messaging in institutions of higher learning, little is known about how proofreading habits or their absence influence the accuracy, clarity, and meaning of academic or professional group community messaging (Turner, 2011; Mlundi, 2024). This is especially critical in virtual academic communities like in- stitutional WhatsApp groups where formal and informal messaging occur simultaneously with a potential for misinterpretation and reputational risks.
Previous studies to date have concerned themself mostly with mobile messaging techno- logical affordances and digital literacy and informal communication (Tagg, 2015; Ling, 2016). Thurlow and Brown (2003) and Darics (2013) show how mobile messaging has evolved an informal register in terms of abbreviations, emojis, acronyms, and non-standard terminology. These studies recognize how such aspects support efficiency and spontaneity but also boost the chance of misinterpretation when reviewed or edited before transmis- sion of a message. While informal registers were studied by Tagg (2015), studies on how
formality in a message is sustained through proofreading institutional WhatsApp groups, in particular in environments where formality, clarity, and professional image are major concerns (Schnurr, 2024; Sibarani, Marbun, Hartati, 2024), are rare.
In workplace and academic scenarios, the impact of miscommunication is even more substantial, and it can affect credibility, personal relationships, and outcome of opera- tions (Rosmi, Syamsir, 2021; Sujinpram, Wannaruk, 2024). Correctly, Drouin and Davis (2009) pointed out the social and cognitive implications of typos and grammatical errors on message perception but failed to discuss how users proactively proofread to minimize these implications. Geisler (2004) and Darics (2013), likewise, point to the significance of editing in written communication especially in the face of non-verbal information deprivation but concentrate mostly on email and long-form writing instead of short and fast-paced messages like one find on platforms such as WhatsApp.
In the African context and particularly within universities, mobile communication studies have predominantly revolved around access, digital divides, and social connectiv- ity (Mtega, Malekani, 2016; Kim, 2018). Despite this, few studies are found addressing systematically how message quality particularly proofreading impacts organizational and academic digital platforms’ accuracy in information delivery, clarity of information, and meaning interpretation (Williams, Brown, 2021). Since there is increasing use of WhatsApp in institutions of higher learning to disseminate announcements, plan meetings, and transmit deadlines, a lack of decently proofread clear messages can lead to confusion, wasting time, and a tarnished professional image (Junco, Cotten, 2011; Miyake, 2020).
In view of the increasing application of WhatsApp in institutions of higher learning, there is a scarcity of empirical studies examining how proofreading habits impact message meaning and clarity in organizational group messaging. More importantly, little is known about how proofreading habits differ in terms of message type (official vs. informal), user type (academic vs. non-academic), and digital competency. This study bridges this gap by examining WhatsApp use in the CBE-ALL-STAFF group at the Dar es Salaam campus a site where academic and non-academic workers often communicate. Employing a qual- itative case study design and NVivo 12 for coding analysis, this study aims to: Investigate to what extent proofreading is used in organizational WhatsApp messaging, explore how proofreading habits impact message meaning and clarity, uncover communicative effects of unproofread messages, and show how digital professional communication in institu- tions of higher learning can be enhanced. By so doing, this study contributes to digital communication literature and offers actionable suggestions to improve message quality and professionalism in institutions of learning.
Symbolic interactionism (Herbert, 1969)
Symbolic Interactionism concerns with how people construct meaning in social interaction through symbols such as language, gestures, and written text. For the purposes of this
study mobile messaging, in this case on WhatsApp, is a symbol of communication. Any grammatical structure, punctuation mark, emoji, even message layout carries meaning, easily distorted in case proofreading is omitted. Symbolic Interactionism is appropriate in this study since it explains how proofreading has an effect on mutual meaning between the recipient and the sender. Without proofreading, these symbols are misused or inter- preted wrongly, leading to misunderstanding, confusion, and emotional misinterpretation. Therefore, this theory explains the importance of proofreading in ensuring the written symbol conveys meaning in digital academic exchange.
Media richness theory (Daft, Lengel, 1986)
Media Richness Theory states that different channels of information transmission differ in their capacity to transmit information. Richer channels such as face-to-face interac- tion facilitate more instant feedback, several cues (tone of voice, face expressions), and personalized language, whereas lean channels such as text messaging have none of these characteristics and depend on written clarity. WhatsApp is a lean medium with fewer cues to facilitate meaning-making, thus increasing the impact of careless proofreading. The theory is important to this study because it highlights why minor mistakes in digital communications (misspellings, omissions of punctuation, etc.) have a severe impact on message reception and meaning. The theory thus validates the necessity of proofreading to counter the inadequacy of lean channels of information such as WhatsApp.
Communication accommodation theory (Giles, Ogay, 2007)
Theory of Communication Accommodation (CAT) describes how people adapt their communication behaviour to fit social context, audience, or purpose. CAT in this study assists in examining how respondents adapt proofreading behaviour based on a perception of formality of WhatsApp chat whether academic, professional, or informal. The re- spondents might have stricter proofreading strategies when chatting with their lecturers or supervisors or even group work contexts and be less stringent when communicating with fellow classmates. This theory reinforces a finding in this study that proofreading is a technically achieved behaviour and also a socially motivated activity with respect to context, social interaction, and digital literacy. Thus, CAT contributes to an under- standing of variability in situations and social motivation concerning users’ proofreading behaviour in institutional WhatsApp chats.
Theoretical framework integration
These three theories collectively present a detailed, multi-faceted grounding for this study. Symbolic Interactionism describes how written symbols language and punctuation con- struct meaning and how such symbol errors may cause a breakdown in meaning. Media Richness Theory highlights communicational constraints of mobile messaging platforms such as WhatsApp and reinforces the significance of proofreading in guaranteeing cla- rity in a situation where non-verbal cues are limited. The social accommodative nature of proofreading conduct is studied through Communication Accommodation Theory, addressing why people vary their linguistic exactitude in relation to audience and setting. The combination of these three theories ensures a multi-faceted and comprehensive analy-
sis of how proofreading conduct affects clarity, professionalism, and efficiency in digital communication in university WhatsApp groups.
This research utilized a qualitative research method assisted by Computer-Assisted Qual- itative Data Analysis Software (CAQDAS), in this case NVivo 12, to investigate how proofreading practice contributes to message clarity, accuracy, and meaning in the CBE- ALL-STAFF - Dar es Salaam Campus WhatsApp group. The qualitative methodology was selected because it enables in-depth investigation into respondents’ actual experience, behaviours, and attitudes towards communicating in virtual platforms (Creswell, Poth, 2018). NVivo 12 was utilized throughout the research process from data management to coding and theme development to improve transparency, rigor, and analytical depth of this study.
In this investigation, an exploratory case study design was used. This is suitable for analy- sing contemporary phenomena in their real-world context (Yin, 2014). Here, the What- sApp messaging setting was researched in a natural environment where proofreading is exhibited in daily communication. The case study facilitated the selection of a particular digital messaging group run from a university while analysing how proofreading affects effective communication in both academic, professional, and interpersonal scenarios.
The data collection used purposive sampling to recruit members of the CBE-ALL-STAFF WhatsApp group who were active and have experience of mobile messaging in different contexts (professional, academic, and personal). The data was collected from 60 people (of different ages and genders and having different roles in communications). The parti- cipants were selected so they would have experience in WhatsApp group use for a period of a minimum of six months to have adequate exposure to its interaction dynamics. This sampling design recommended by Patton (2015) provided cases to meet information requirements of the study.
The data were gathered in October to December of 2023 using three qualitative methods: – Semi-structured interviews (n = 30): These were crafted to investigate individual proofreading habits, attitudes towards message accuracy, and perceived effects of proof- reading. The flexibility of interviews meant that in-depth responses were facilitated by
an interview protocol.
Focus group discussions (12 groups of 5 people): These were carried out to obtain communal opinions, shared norms, and conflicts about proofreading habits. The duration of each was between 60 and 90 minutes and was audio-recorded (Barbour, 2018).
Content analysis of 100 anonymized WhatsApp messages: Real messages were drawn (with permission) from the group and examined for typographical, grammatical, and punctuation errors and how they influenced clarity and meaning. The sampling of 100 messages was driven by theoretical saturation, in that no new themes or insights were forthcoming following review of around 80 of them. The last 100 messages provided a tractable yet information-dense dataset to facilitate thematic analysis. Audio data were transcribed verbatim and brought into NVivo 12 to be systematically examined.
Thematic analysis, following Braun and Clarke’s (2006) six-step model, was used to in- terpret the qualitative data. NVivo 12 supported a transparent and structured analytical process. The steps included:
Data familiarization: Transcripts and messages were read multiple times, with initial notes recorded.
Generating initial codes: NVivo’s coding function was used to apply both inductive and deductive codes based on theoretical constructs (e.g., accuracy, misinterpretation, context sensitivity).
Searching for themes: Coded data were grouped into broader nodes representing emerging themes such as Message Clarity, Proofreading Habits, Communication Break- down, and Contextual Variations.
Reviewing themes: NVivo’s query tools (matrix coding, word frequency, and co-oc- currence models) helped validate theme coherence and interrelationships.
Defining and naming themes: Themes were refined, defined, and supported with direct quotes.
Producing the report: The final themes were aligned with the theoretical framework and research questions.
NVivo’s advanced tools such as word frequency clouds, cluster analysis, and matrix queries allowed the researcher to explore patterns across demographics and contexts (e.g., comparing proofreading behaviours across formal vs. informal messages or among different age groups).
Informed written permission was obtained for all participants, and ethical standards of Cohen, Manion and Morrison (2011) were adhered to. The anonymity, confidentiality, and voluntary nature were assured to all participants. Participant-identifying information in WhatsApp messages was excluded, and only anonymized text was subjected to analysis. The data were kept safe and participants were entitled to withdraw at any time
NVivo 12 was used to code qualitative data gathered through interviews, FGDs, and message content into major thematic nodes. The features in this software such as Word
Frequency Query, Matrix Coding, and Thematic Node Tree facilitated visualization and comparison of academic and non-academic staff patterns. Some of the important findings in data are provided below:
Key finding: Academic staff associate proofreading with professional credibility, while non-academic staff emphasize its role in ensuring task clarity and precision.
WhatsApp message examples
– Academic staff message (with error):
Pls submit your research final paper tommorow latest 11pm.
(Unproofread message led to confusion over whether the deadline was tomorrow or another date.)
Corrected message:
Please submit your final research paper by 11:00 PM tomorrow (Thursday, 28th Sep- tember).
– Non-academic staff message (with error):
HR will conduct trainng for new recruts at confernce room Mini Hall tommorow.
(Spelling errors led to multiple clarification requests.)
Corrected version:
HR will conduct training for new recruits in Conference Room Mini Hall tomorrow at 10:00 AM.
The Node Tree picked out keywords such as professional, errors, image, clarity, and mistakes to emphasize how proofreading is beneficial to both personal credibility and institutional reputation. The academic staff considered it as part of intellectual presentation and non-academic staff associated it with operational accuracy.
WhatsApp message examples
Submit the assignment from Human Resources Office latest Tuesday (Lecturers assumed it meant the upcoming Tuesday and submitted early.) Corrected version:
Please submit the assignment from Human Resources Office by Tuesday, 26th Septem- ber 2023 at 10:00 PM.
Friday meeting confirmed
(Lack of a date led to assumptions; the meeting was actually the following week.)
Corrected version:
Friday, 6th October 2023 – Budget Review Meeting confirmed at 3 PM at Mini Hall.
We will not present tomorow’s class
(Interpreted as class cancellation, while the intention was no student presentations.)
Clarified version:
Note: Students will not present during tomorrow’s classes. The lectures will continue as usual.
NVivo insight
Text Search Query results indicated regular references to confuse, incorrect, meaning, and clarify, demonstrating misinterpretation was a result of both structural mistakes and a shortage of context. Matrix Coding found instructional consequences affected academic employees, while non-academic employees were affected by workflow interruptions.
Key finding: Participants adjusted their proofreading habits depending on the message’s formality, audience, and urgency.
WhatsApp message examples
Formal message (academic – proofread):
Dear lecturers, please remember that students’ research proposals are due this Friday, 5:00 PM…
Informal message (academic – unproofread):
cnt make it today sorry
Formal message (non-academic – proofread):
Please ensure all payment vouchers for July are submitted by Wednesday, 10 AM…
Informal message (non-academic – not proofread):
seen tht, il do it tomoro
NVivo insight
Matrix Coding Query reflected explicit differences in tone based on audience. Academic employees were more consistent in their use of formal tone, particularly when communi- cating with students. NVivo’s Diagram of Comparison of Codes indicated that insensitivity to context was associated with heightened potential for miscommunication and perceived lack of professionalism.
Key finding: Errors in sensitive or hierarchical messages caused embarrassment, frustra- tion, and strained relationships.
WhatsApp message examples
Please don’t repeat that again.
(Interpreted as a reprimand, though the sender intended to ask for repetition.)
You should mind you’re tone in meetings.
(Typo “you’re” instead of “your” led to perceived sarcasm and conflict.)
NVivo insight
Word Tree Query for I felt brought forth intense emotional reactions like embarrassed, mi- sunderstood, ashamed, and disrespected. Emotional impact was intensified in hierarchical scenarios (staff-to-supervisor), depicting how small mistakes can bring about large-scale interpersonal discomfort.
Key finding: Poor proofreading led to repeated follow-ups and clarification efforts, redu- cing communication efficiency and productivity.
WhatsApp message examples
Submit final presentation before next Wednesday
(Lecturers requested clarification: “Do you mean this coming Wednesday or the next one?”)
Clarification sent: Wednesday, 17th
Bring the payment voucher to Mr. Said off by 3:00
(Ambiguity led to confusion did “off by 3:00” mean “before” or “he leaves at” 3:00?)
NVivo insight
Cluster Analysis indicated this theme to be overlapping with Message Misinterpretation and Proofreading Habits, thereby supporting that minor errors were always initiating long chains of clarifications. Frequent NVivo keywords were clarify, resend, time-wasting, and confused implying resultant delays due to unnecessary errors.
Tab. 1. Theme frequency comparison summary
Theme | Academic Staff | Non-Academic Staff | Total |
Proofreading and Professional Image | 62 | 41 | 103 |
Message Misinterpretation | 58 | 67 | 125 |
Context-Sensitive Proofreading | 45 | 51 | 96 |
Emotional and Social Consequences | 39 | 42 | 81 |
Communication Efficiency and Time Waste | 40 | 49 | 89 |
Source: Author’s data collection
Fig. 1. Thematic Frequency of NVivo 12-Coded Data by Staff Type
Source: Data coded from NVivo 12.
The NVivo 12 analysis brings to surface how proofreading in mobile messaging is a com- plex social activity rather than a purely mechanical process. It affects how messages are written, read, and understood in professional and informal situations. The academic and non-academic employees all appreciate its significance most when errors cause misunderstandings, damage to reputation, or operational inefficiency. Such analysis is more detailed than summary charts and identifies deeper layers of interpretation of how language, context, and perception intermingle in digital university arenas.
This part deals with the results of the NVivo 12-based analysis and how proofreading behaviour affects communication clarity, effectiveness, and meaning in WhatsApp group messaging among academic and non-academic employees in CBE-ALL-STAFF – Dar es Salaam campus. The discussion is rooted in Symbolic Interactionism, Communication Accommodation Theory, and Media Richness Theory and relates observed phenomena to mainstream theoretical contributions.
The research shows academic staff pay closer attention to proofreading messages so as to uphold a professional image, particularly in contexts where formality and clarity are necessary (i.e., announcements and assignment reminders). This supports Symbolic Interactionism (Blumer, 1969), which argues people exchange and decode meaning through symbols – in this instance, well-proofread text conveys competence, credibility and professionalism. Non-academic staff also valued accuracy but were more concerned with getting a task done with clarity in instruction rather than managing impressions. This difference in focus implies occupational role has a strong effect on linguistic behaviour in virtual contexts. These findings are consistent with Geisler (2004) and Drouin and Davis (2009), who noted accuracy in writing affects the credibility of the author.
Both academic and non-academic employees suffered repeated misinterpretation of mes- sages due to basic proofing mistakes. This exemplifies a major shortcoming of lean channels like WhatsApp, which lack redundancy cues such as facial expressions and tone (Xenakis et al., 2022). As Media Richness Theory suggests, written messaging is most susceptible to ambiguity when linguistic accuracy is poor. The findings confirm prior research (Schnurr, 2024; Sibarani, Marbun, Hartati, 2024) emphasizing the significant impact of minor language mistakes especially in formal or task-related communication. Additionally, the emotional labour involved in resolving misunderstandings through clar- ification, re-explanation, or mitigation proves to be a hidden cost of poor proofreading in organizational contexts.
An important insight is that proofreading is situation-dependent, with stricter adherence in formal or high-stakes situations (e.g., communication with supervisors or issuing deadlines) and relaxed norms in casual peer discussions. This aligns with Communication Accommodation Theory (Giles, Ogay, 2007), which suggests people adjust their communi- cation based on audience, context, and expectations. This adaptive behaviour mirrors what Merriam and Tisdell (2016) noted that digital communication is shaped by context cues. In this study, participants showed more linguistic care in formal or hierarchical settings.
Notably, their proofreading habits were not only strategic but emotionally motivated – past experiences of embarrassment, shame, or confusion prompted greater vigilance. Emotional effects (Theme 4) reinforced context-sensitive proofreading (Theme 3). Those who faced reputational harm or tension from earlier mistakes reported increased caution in group interactions. Here, emotion served as a regulatory force for behaviour.
consistent with Goffman’s (1959) notion of “face work,” where individuals manage their
social image in interactions. In text-based digital communication, where words substitute for tone and body language, proofreading becomes essential in preserving a positive image. Academic staff, in particular, were more sensitive to how mistakes might be perceived as unprofessional or incompetent. These insights echo Drouin and Davis (2009), who found that grammatical errors not only obscure meaning but also damage perceptions of the sender’s intelligence or seriousness.
A highly pragmatic outcome of poor proofreading was wasted time through clarifica- tion, repeated instructions, and interruptions in workflow. This confirms Krippendorff’s (2018) point that clarity in communication minimizes transactional friction and enhances efficiency. Participants reported that unclear messages often led to redundant back-and- forth, delays in decision-making, and inefficiencies – particularly in administrative or student-facing tasks. These problems often fed into emotional frustration for the sender, who had to repeatedly explain or correct miscommunications.
Interestingly, younger participants especially those in academic roles showed greater proofreading awareness in formal digital settings. This highlights generational differences in digital etiquette, shaped by familiarity with evolving tech norms and formal commu- nication expectations. This aligns with Patton (2015), who noted younger professionals tend to adapt more easily to digital tools and their conventions. However, the study also reveals a broader gap in digital etiquette based on age, training, and role underscoring the need for institution-wide initiatives on digital communication literacy.
The effects of proofreading on accuracy, clarity, and meaning of mobile messages in the CBE-ALL-STAFF – Dar es Salaam campus WhatsApp group were examined in this study through a qualitative data analysis conducted with NVivo 12. By surveying data gathered through interviews, focus group discussions, and message content analysis, it was determined that proofreading is much more than a matter of grammar formalities it is a communicative activity whose impact strongly dictates how mobile messages are received, interpreted, and reacted to in institutional digital spaces.
The major findings were that academic and non-academic respondents viewed proof- reading to be useful in formal or high-stakes writing. Proofreading was associated with good professional image, reduced possibilities of misinterpretation, and greater credibility. Unproofread text resulted in confusion, emotional discomfiture, loss of reputation, and inefficiency in information flow. It was also discovered that proofreading is a highly con- text-dependent process determined by formality of message, digital literacy, professional level, and generation norms.
NVivo 12 software was used to apply a layered thematic analysis to uncover deep insights into how academic faculty negotiate communicative digital norms. The results are important contributions to existing literature about mobile messaging, workplace communications, and literacy in an academic setting. With today’s increasingly digital academic landscape, proofreading is more than a linguistic process but a demonstration of professionalism and intentionality in everyday institutional communications. Therefore, it should be embraced as a crucial competency in generating successful, respectful, and effective digital discourse.
Grounded on the findings in this study, various actionable recommendations are presented to advance professionalism and quality in mobile phone messaging, in particular in orga- nizational WhatsApp groups.
To begin with, digital communications training has to be promoted. Institutions such as CBE should conduct regular workshops or short courses to train employees in devel- oping skills in digital communications. Proofreading skills, audience sensitivity, and tone in professional messaging need to be taught in such training. Including digital etiquette in employee development initiatives will make employees more sensitive to how minor errors influence message perception and professional reputation.
Secondly, internal messaging guidelines must be established for consistency and clarity. CBE and institutions like it must establish formal WhatsApp protocol guidelines – especially for academic and administrative groups. These must indicate clearly what is expected in terms of tone, punctuation, grammar, and proofreading in formal announce- ments, assignment of work, and time-sensitive messaging.
Thirdly, context-dependent proofreading needs to be fostered. Casual discussions among team members may not be necessary to be edited much, but members must know that different contexts carry different requirements. Proofreading should be in line with how important a message is. Deadline reminders, reports, or assessments are examples of communications to be rigorously proofread. The flexible methodology lessens the pos- sibility of mistake while professionalism will be sustained where it is most important.
Further investigation also needs to look at how predictive features autocorrect, speech to text, and predictive typing impact proofreading behaviours. Though designed to improve efficiency, these functions introduce errors unintentionally. Investigating their impact across ages and situations can uncover new problems and possibilities in digital messaging. Lastly, the scope of the study should be extended beyond WhatsApp. While WhatsApp has a large user base, there might be habits and expectations in other platforms such as email, Microsoft Teams, or even in Telegram based on interface design, formality, and audience norms. Comparative studies across these platforms would provide wider insights
into digital tools influencing proofreading and professionalism in communication.
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