Computer-mediated Communication Platforms Research Articles

Artificial intelligence and computer-mediated communication: the text analysis and undergrad’s class observation

The term “computer-mediated communication” (CMC) describes the transmission of messages and information using computer technology. With the extensive use of email, instant messaging, social media, and other digital platforms in Nepal in recent years, this style of communication has grown in popularity. The article examines how computer-mediated communication (CMC) and artificial intelligence (AI) have grown in significance in Nepal’s undergrad English education. This article allows students to collaborate on projects and tasks, which improves their learning experience, by examining the potential of AI and CMC. The facts of Nepal’s education have been examined using the four different basic literature reviews. Despite the need for further literature on artificial intelligence and computer-mediated communication in Nepal’s English classes for undergrads between 2018 and 2023, the studies reviewed shed light on the possibilities of technology and AI in language acquisition. Undergraduate class observation, self-administered text analysis, social information processing theory and experimental research, which involves adjusting variables to see how they affect learning results, were used to gather data. The study’s findings also demonstrate how using CMC platforms encourages students to practice their digital literacy. They gain knowledge on how to move through online spaces, efficiently communicate with a variety of digital tools, and assess the reliability of information sources. Students can communicate with their teachers outside of the classroom via video conferencing software and online discussion boards. This may result in more in-depth discussions and debates as well as greater student engagement.

Language portraits going digital and multimodal: deciphering the translanguaging space and linguistic repertoires among multilinguals

In recent years, language portraits (LPs) have emerged as a valuable tool for visually representing multilingual learners’ linguistic repertoires. However, previous studies have primarily relied on traditional methods of inviting participants to sketch their language portraits on paper using pens and crayons. In this paper, we propose the use of digital methods to collect and analyze data on language portraits to examine the translingual practices and negotiations of meaning among multilingual individuals. By utilizing Synchronic Computer-Mediated Communication platforms, participants can actively deploy and mobilize multi-linguistic and multi-semiotic resources in lived experiences, engaging in interactive translanguaging practices. In this particular case study, data were collected through a biographic survey and a sketch of the language portraits in digital form, which were then further supported by follow-up interviews. Four participants’ LPs and oral narratives during the interviews were then subjected to qualitative multimodal analysis and discourse analysis. The results revealed that these digital language portraits (DLPs) possess significant features such as digital affordance and multimodality. They tap into the translanguaging spaces that emerge from the creative and critical meaning-making process, enabling multilingual individuals to visualize their linguistic repertoires through digital visual strategies. Furthermore, it was discovered that DLPs can foster creative performance and discursive negotiations, thereby enhancing participants’ expressive abilities in developing their language perceptions.

Machine voice-over translation in social media: Perceived quality of translation of YouTube travel vlogs

One of the challenges of social media as a means of interaction is to ensure media accessibility, i. e. to provide users with a free and unhindered access to the content of computer-mediated communication platforms. In the context of global networking, linguistic constraints due to the use of a verbal code different from the language of the potential user while creating media content, are not the least of the obstacles to such access. Given the obvious dominance of English in the online space, this is mainly a matter of expanding the audience by engaging individuals whose source language proficiency is not sufficient for unimpeded use of social media, in particular for viewing, listening and understanding video content uploaded on video hosting sites and other digital platforms. Since user-generated video content is generally characterised by individual and independent production, free accessibility and target audiences sharing a common interest for a specific subject matter, regardless of their residence area and language affiliation, human audio-visual translation is not considerable in such circumstances. For this reason, as a way to overcome language barriers and ensure media accessibility, the most advanced Internet portals are beginning to implement Web-based online machine translation solutions, made possible by the development of linguistic digital technologies. The survey conducted as a part of this study has shed light on the users’ perception of machine voice-over translation of English-language travel vlogs into Russian, and formulated some hypotheses regarding the ways to further improve its quality. The empirical evidence for this study was obtained from a two-step survey involving users and experts (audiovisual translators) who assessed the quality of machine voice translation of English-language travel vlog into Russian. According to the results ontained machine translation seems to be conceptually acceptable as a means of enabling language media accessibility in social media.

Impoliteness Strategies Inflicted by Twitter Users: The Case of Interaction with Malaysian Royal Family

The language used in Computer-Mediated Communication (CMC) has been a debated issue for a long time. Ever since the normalisation of this method of communication, the interaction has been going on only between the common people, resulting in a more expressive and direct communication process. However, recently, the elites and royalties have also come into CMC platforms which causes confusion in the interaction between the common people and the royalties. Therefore, it leads to the clash between the common people and the royalties on social media. This study aims to analyse the impoliteness strategies used by Twitter users in expressing their resentment towards royalties by using the impoliteness theory introduced by Culpeper in 1996. 442 tweets that represent impoliteness has been gathered through purposive sampling method. Based on the analysis, the most popular strategy used by Twitter users is off-record (75), followed by sarcasm (55), Negative Impoliteness (41), Bald on record (39) and positive impoliteness (32). The findings show that although Twitter users are more expressive, they tend to resort to a more subtle approach to express their resentment towards the royalties.

Computer-mediated Diagnostic Assessment of Mixed-ability EFL Learners’ Performance on Tiered Tasks: Differentiating Mediation on Google Meet™

Grounded in Vygotsky’s sociocultural theory of mind and the learner-centered approach to second/foreign language acquisition (SLA), this study investigated the extent to which the embedded differentiated instructions and diagnostic assessment, being mediated on Google Meet™ computer-mediated communication platform, would impact the improvement of mixed-ability English-as-a-Foreign-Language (EFL) learners’ English words pronunciation and their degree of engagement in language learning. In a repeated-measures research design, an intact group of 66 EFL learners were partitioned into three tiers of higher, mid- and lower achievers to complete a virtual pretest of listening comprehension, followed by a series of parallel tiered performance tasks of English words pronunciation on a weekly basis. Their task outcomes were subsequently subjected to collective computer-mediated diagnostic assessment. After 10 sessions of intervention, the participants performed on an immediate virtual posttest of listening comprehension, and a post hoc interview. The results of mixed between-within subjects analysis of variance (ANOVA) indicated both the significant learning progress by the tiers, and the outperformance of the lower achievers on the tiered tasks. The statistical results of an analysis of covariance (ANCOVA) similarly reported significant improvement of the tiers’ performance on the pretest-posttest summative assessment in this study. The inductive content analysis of the participants’ responses to the structured interview elicited seven themes which were interpreted as the participants’ strong approval of the usefulness of differentiated instructions, effectiveness of diagnostic assessment, and successful appeal of Google Meet platform.

Computer-Mediated Communication in Adults With and Without Moderate-to-Severe Traumatic Brain Injury: Survey of Social Media Use.

BackgroundIndividuals with a history of traumatic brain injury (TBI) report fewer social contacts, less social participation, and more social isolation than noninjured peers. Cognitive-communication disabilities may prevent individuals with TBI from accessing the opportunities for social connection afforded by computer-mediated communication, as individuals with TBI report lower overall usage of social media than noninjured peers and substantial challenges with accessibility and usability. Although adaptations for individuals with motor and sensory impairments exist to support social media use, there have been no parallel advances to support individuals with cognitive disabilities, such as those exhibited by some people with TBI. In this study, we take a preliminary step in the development process by learning more about patterns of social media use in individuals with TBI as well as their input and priorities for developing social media adaptations.ObjectiveThis study aims to characterize how and why adults with TBI use social media and computer-mediated communication platforms, to evaluate changes in computer-mediated communication after brain injury, and to elicit suggestions from individuals with TBI to improve access to social media after injury.MethodsWe conducted a web-based survey of 53 individuals with a chronic history of moderate-to-severe TBI and a demographically matched group of 51 noninjured comparison peers.ResultsMore than 90% of participants in both groups had an account on at least one computer-mediated communication platform, with Facebook and Facebook Messenger being the most popular platforms in both groups. Participants with and without a history of TBI reported that they use Facebook more passively than actively and reported that they most frequently maintain web-based relationships with close friends and family members. However, participants with TBI reported less frequently than noninjured comparison participants that they use synchronous videoconferencing platforms, are connected with acquaintances on the web, or use social media as a gateway for offline social connection (eg, to find events). Of the participants with TBI, 23% (12/53) reported a change in their patterns of social media use caused by brain injury and listed concerns about accessibility, safety, and usability as major barriers.ConclusionsAlthough individuals with TBI maintain social media accounts to the same extent as healthy comparisons, some may not use them in a way that promotes social connection. Thus, it is important to design social media adaptations that address the needs and priorities of individuals with TBI, so they can also reap the benefits of social connectedness offered by these platforms. By considering computer-mediated communication as part of individuals’ broader social health, we may be able to increase web-based participation in a way that is meaningful, positive, and beneficial to broader social life.

A tale of two language ideologies: Discursive co‐construction of L2 learner identity in Japanese CMC interactions

AbstractThis study investigates the relationship between learner perception, ideology, discourse, and identity in computer‐mediated communication (CMC) interactions between an advanced L2 Japanese learner and native Japanese speakers. Study findings show that, despite an invested identity as a proficient user of Japanese, the learner struggled to enact this identity in the face of two divergent language ideologies: one that promoted Japanese native speaker discourse as the goal of L2 learning and use, and one that promoted a particular Western “foreigner” discourse for non‐native speakers of Japanese. Furthermore, a third discourse—that of the CMC platform—also affected her discursive practices, both in terms of interaction and performance of multiple identities. These results reveal the complex, sometimes problematic, nature of CMC for L2 learning and use, while offering a unique perspective into the issue of the native speaker standard in Second Language Acquisition (SLA), particularly as it pertains to advanced learners.

Challenges in Conducting Online Videoconferencing Qualitative Interviews with Adolescents on Sensitive Topics

In the wake of COVID-19, researchers are seeking innovative data-collection methods. Computer-mediated communication platforms have played a pivotal role among these pursuits. However, conducting online interviews present challenges to both researchers and participants. Online data-collection forces researchers to give up control over the study environment due to the varying location participants partake in interviews. Consequently, researchers can no longer fully guarantee the confidentiality and privacy of the researcher-participant conversations. Participants may face difficulties if being asked to disclose private information in the presence of family members. These challenges are heightened when conducting online interviews with adolescents on sensitive topics. Thus, attention to the rigour of qualitative research is a fundamental consideration given these limitations in technical and social conventions with the use of online data-collection methods. Despite the host of challenges, online interviewing creates valuable opportunities for researchers to rise to the challenge of social distancing in their data-collection efforts.

Understanding “Zoom fatigue”: Theorizing spatial dynamics as third skins in computer-mediated communication

“Zoom fatigue”—theorized here as part of a larger experience with computer-mediated communication (CMC) exhaustion—has emerged as a common negative experience through prolonged use of CMC platforms. Despite CMC exhaustion’s ubiquity, the relatively novel phenomenon has caused much speculation for its root causes with little information pinpointing why it occurs. Utilizing research, observations, and personal accounts, this article explores synchronous online consultations (SOCs) within writing centers as matching sites to ponder the basis for CMC exhaustion. In doing so, third skins are proposed to account for how nuanced differences in space between SOCs and face-to-face exchanges mean participants are not engaged as human actors but “flattened” into a totality of third skin comprising person, background, and technology. The resulting transformation and our bodies exerting substantial cognitive efforts to interact with this transformation are theorized to produce CMC exhaustion. The implications for this are twofold: 1) for readers interested in the underlying causes of CMC exhaustion, this work presents a framework to test the ideas proposed and develop mitigating strategies, and 2) for readers who study SOCs, third skins might explain previously observed limitations in the effectiveness of visuality in CMC.

Quantifying the Causal Effects of Conversational Tendencies

Understanding what leads to effective conversations can aid the design of better computer-mediated communication platforms. In particular, prior observational work has sought to identify behaviors of individuals that correlate to their conversational efficiency. However, translating such correlations to causal interpretations is a necessary step in using them in a prescriptive fashion to guide better designs and policies. In this work, we formally describe the problem of drawing causal links between conversational behaviors and outcomes. We focus on the task of determining a particular type of policy for a text-based crisis counseling platform: how best to allocate counselors based on their behavioral tendencies exhibited in their past conversations. We apply arguments derived from causal inference to underline key challenges that arise in conversational settings where randomized trials are hard to implement. Finally, we show how to circumvent these inference challenges in our particular domain, and illustrate the potential benefits of an allocation policy informed by the resulting prescriptive information.

KNOWLEDGE SHARING ON SOCIAL MEDIA: STATE OF THE ART IN 2018

In the past decade, the importance of social media has increased, especially in knowledge sharing practices. Current massive evolution of computer-mediated communication platforms influenced the ways of how knowledge is managed and shared by individuals. This literature review of published papers in the past decade explores the potential of using social media in knowledge sharing by individuals and, through the mapping of the existing studies, identifies research opportunities for future studies. Primary, tacit and explicit knowledge sharing have been investigated. The findings suggest that there are different ways in which knowledge is shared across social media, but the systematic approach and synthesis is challenging to define. Therefore, there are some open courses of future research that may form the basis for a theoretical framework. The results of the present literature review should increase methodological rigor, and provide the guidelines to academics by identifying research opportunities. They can also serve as a comprehensive collection of findings for knowledge management decision makers.

Smile Mimicry and Emotional Contagion in Audio-Visual Computer-Mediated Communication.

We investigate whether smile mimicry and emotional contagion are evident in non-text-based computer-mediated communication (CMC). Via an ostensibly real-time audio-visual CMC platform, participants interacted with a confederate who either smiled radiantly or displayed a neutral expression throughout the interaction. Automatic analyses of expressions displayed by participants indicated that smile mimicry was at play: A higher level of activation of the facial muscle that characterizes genuine smiles was observed among participants who interacted with the smiling confederate than among participants who interacted with the unexpressive confederate. However, there was no difference in the self-reported level of joviality between participants in the two conditions. Our findings demonstrate that people mimic smiles in audio-visual CMC, but that even though the diffusion of emotions has been documented in text-based CMC in previous studies, we find no convincing support for the phenomenon of emotional contagion in non-text-based CMC.

Your comments are important to me! The impacts of online customer reviews in shopping websites

The aim of this study is to examine the influence of Online Customer Reviews (OCRs) on consumers' purchase intentions, and to understand the role of attitude on information adoption within the computer-mediated communication platforms. For this purpose, a research model was developed based on the Information Adoption Model (IAM). The model was empirically tested and validated through Structural Equation Modelling (SEM). The data were collected from a sample of 384 university students. The results confirm that attitude plays an important role on information adoption; and the following are among the key factors which influence consumers' purchase intentions: eWOM quality, eWOM credibility, attitude towards eWOM, perceived eWOM usefulness, and eWOM adoption. Theoretical and practical implications are discussed as well as recommended for future studies.

Understanding the relationship between intensity and gratifications of Facebook use among adolescents and young adults

Facebook is a well-known computer-mediated communication platform considered popular among adolescents and young adults. New media scholars have coined the term “intensity of Facebook use” (IFU) for the concept that measures the emotional and affective attitude towards Facebook use among young people. IFU is an important service use concept that has been positively linked with the different psychosocial outcomes of student well-being. However, only a limited amount of the prior literature has investigated the relationship between IFU and different Facebook uses and gratifications (U&G). The existing literature suggests inconsistent findings with a sole emphasis on young adults. To address these gaps, the present study has investigated the differential role of different Facebook U&G among adolescents and young adults in predicting IFU. A total of three cross-sectional data sets (N=373, 107, 105) represented adolescents and university-attending young-adult Facebook users. The study results suggest that process U&G do and content U&G do not play any significant role in predicting IFU. Adolescents and young adults differ in their sought Facebook U&G. In addition to this, cultural differences were observed in the sought Facebook U&G and their differential role in predicting IFU.

Supporting the development of synchronous text-based computer-mediated communication with an intelligent diagnosis tool

To date, a look at the scientific literature on the construction and use of synchronous computer-mediated communication (CMC) support environments reveals that most researchers have focused either on exchanging information or on constructing and presenting posts. In this work, an intelligent collaborative synchronous CMC platform that detects whether the learners address the expected discussion issues is proposed. The concept maps related to the learning topics are first outlined by the instructor. After each learner issues a post on the synchronous CMC platform, a feature selection approach is adopted to derive the input parameters of a one-class Support Vector Machines (SVMs) classifier. The classifier then determines if the learners’ posts are related to the concept maps previously outlined by the instructor. Meanwhile, learner peers from the same group are asked to provide comments on the synchronous CMCs, and a group grading module is established in this work to evaluate the quality of the synchronous CMCs. If the evaluation results from the classifier and the group grading module are inconsistent, the instructor or the teaching assistant is consulted to verify the evaluation results. Notably, a feedback rule construction mechanism is used to issue feedback messages to learners in cases where the synchronous CMC support system detects that the learners have strayed astray from the expected learning topics in their posts. The classification rates for the one-class SVM classifier can reach up to 97.06%, and the average pre-test and post-test grades were 51.94 and 66.77, respectively, which revealed that the junior high school students participating in synchronous CMC activities related to natural science were benefited by the proposed intelligent synchronous CMC platform.

Toward Cyber-Enhanced Working Dogs for Search and Rescue

The authors introduce the fundamental building blocks for a cyber-enabled, computer-mediated communication platform to connect human and canine intelligence to achieve a new generation of Cyber-Enhanced Working Dog (CEWD). The use of monitoring technologies provides handlers with real-time information about the behavior and emotional state of their CEWDs and the environments they're working in for a more intelligent canine-human collaboration. From handler to dog, haptic feedback and auditory cues are integrated to provide remote command and feedback delivery. From dog to handler, multiple inertial measurement units strategically located on a harness are used to accurately detect posture and behavior, and concurrent noninvasive photoplethysmogram and electrocardiogram for physiological monitoring. The authors also discuss how CEWDs would be incorporated with a variety of other robotic and autonomous technologies to create next-generation intelligent emergency response systems. Using cyber-physical systems to supplement and augment the two-way information exchange between human handlers and dogs would amplify the remarkable sensory capacities of search and rescue dogs and help them save more lives.