Article Per Year (5 Year)
p-Index From 2020 - 2025
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All Journal Language, Technology, and Social Media Blockchain, Artificial Intelligence, and Future Research
Chhibber, Sugandha
Unknown Affiliation
Humanities Computer Science & IT Education Languange, Linguistic, Communication & Media Social Sciences

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How Do Different Generations Communicate on Social Media? A Comparative Analysis of Language Styles, Emoji Usage, and Visual Elements Azad, Inamul; Chhibber, Sugandha; Tajhizi, Azra
Language, Technology, and Social Media Vol. 1 No. 2 (2023): December 2023 | Language, Technology, and Social Media
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/ltsm.v1i2.61

Abstract

This study aims to explore generational differences in language styles on social media, with a focus on levels of formality, emoji usage, and the integration of visual communication elements. A quantitative content analysis was conducted on a sample of 4,000 social media posts collected from Twitter, Facebook, and Instagram. The sample included posts from four generational cohorts: Baby Boomers, Generation X, Millennials, and Generation Z. Each post was analyzed for language structure, the frequency of emoji use, and the presence of visual elements such as memes. Statistical methods, including ANOVA, were employed to identify significant differences across generations. The analysis revealed that Baby Boomers prefer more formal language structures, reflecting their adherence to traditional communication norms. In contrast, Generation Z demonstrates a strong preference for informal language, frequent use of abbreviations, emojis, and memes, illustrating their adaptation to the fast-paced, visually-oriented nature of digital communication. The study concludes that these generational differences are shaped by both cultural background and technological exposure, leading to distinct communication patterns across age groups. This research contributes to the field of digital communication by providing empirical evidence on how generational cohorts interact differently on social media, offering valuable insights for marketers and digital strategists in tailoring their communication strategies.
Will Artificial Intelligence Reshape the Global Workforce by 2030? A Cross-Sectoral Analysis of Job Displacement and Transformation Chhibber, Sugandha; Rajkumar, S.R.; Dassanayake, Sandun
Blockchain, Artificial Intelligence, and Future Research Vol. 1 No. 1 (2025): May 2025
Publisher : WISE Pendidikan Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70211/bafr.v1i1.178

Abstract

The rapid advancement of artificial intelligence (AI) is transforming the global labor market, presenting both opportunities and challenges. This study investigates the extent of AI-driven job displacement and task transformation across industries, highlighting sector-specific vulnerabilities and workforce perceptions. Using secondary data from Statista’s global surveys (2022–2023), involving 22,816 employees, 1,684 business leaders, and 803 corporations, the study employs descriptive statistical analysis to identify patterns of job disruption and skill adaptation. The findings reveal that AI primarily reshapes job functions rather than eliminating entire occupations, with 57% of respondents reporting task augmentation and 36% expressing concern about job loss. Routine-based sectors, such as manufacturing and customer service, face higher displacement risks, while knowledge-based professions, including healthcare, education, and creative industries, experience AI as a complementary tool. Additionally, disparities in AI adoption are evident between large corporations and small-to-medium enterprises (SMEs), often due to resource limitations and varying digital readiness. The study concludes that successful AI integration hinges on proactive strategies, including continuous workforce reskilling, adaptive education systems, and ethical AI deployment. Policymakers, industry leaders, and educational institutions must collaborate to ensure an inclusive transition, prioritizing digital literacy and skills development. Future research should explore regional variations, firm-level case studies, and the long-term socio-economic impacts of AI adoption. Ultimately, this study underscores the importance of balancing technological advancement with workforce resilience to foster sustainable economic growth in an AI-driven era.
Co-Authors Azad, Inamul Dassanayake, Sandun Rajkumar, S.R. Tajhizi, Azra