Aug 2026· Emerging Media· Vol 4, pp. 457 - 485· 1 citation· 104 references
TL;DR
This research examined how public communication about emerging technologies is shaped through platform-specific multimodal conventions and engagement dynamics on TikTok to provide insights for stakeholders who seek to promote responsible AI communication on video-sharing platforms where algorithms shape which content is prioritized.
Abstract
Generative artificial intelligence (AI) tools such as ChatGPT are increasingly integrated into many realms of society and everyday life, generating both promise and concern. This underscores the need to examine how they are represented on social media, where their meanings, uses, and implications are publicly negotiated. Drawing on a snapshot of top results returned by TikTok's algorithmic ranking system, we examined 4458 TikTok videos with English-language descriptions related to ChatGPT, combining topic modeling with interpretive multimodal content analysis. We identified six overarching themes ranging from informational content, including tutorials and sociotechnological discussions, to entertainment-oriented content such as playful interactions with AI and memes. Multimodal analysis showed that creators blend visual, aural, and textual resources in distinct ways to construct meanings and assessments across themes. Engagement analyses revealed that entertainment-oriented content attracted higher interaction than informational content, although informational content was more prevalent. With a focus on TikTok, this research illustrates how public communication about emerging technologies is shaped through platform-specific multimodal conventions and engagement dynamics. The findings provide insights for stakeholders who seek to promote responsible AI communication on video-sharing platforms where algorithms shape which content is prioritized.
This study explores LLM-generated documents, their social impacts and biases, and their outcomes in research. Language, as a deeply intricate and nuanced system, continues to challenge our efforts in both understanding and generation. Language modeling has progressed from foundational statistical techniques to the sophistication of Large Language Models (LLMs) powered by deep learning. Trained on vast quantities of data, self-generated content, and self- and semi supervised learning, demonstrate remarkable capabilities for producing contextually relevant, human-like text and executing a broad spectrum of language tasks. Despite their promise, these systems are not without limitations, particularly concerning embedded biases stemming from training data and model architecture. Emerging scholarship delves into their symbolic reasoning, potential, and interdisciplinary applications, though many avenues remain insufficiently explored. As examples of generative artificial intelligence, ChatGPT increasingly contributes to education by fostering accessible learning, facilitating domain-specific assessments, and nurturing creativity and critical thinking among learners. It attempts to understand the LLM model by unraveling the facts in day-to-day practices. This article applies the qualitative methods used in comparing two AI-generated recommendation letters, indicating male and female (Ajit/ Ajita). Textual review as a major tool and technique of knowing LLMs and their biases, significance, social impacts, and the ways of interpreting biases with outcomes. It is based on sociotechnical system theory and algorism bias theory. This article claims that LLMs are the latest AI-generated product utilized in academic discourses, enriching the capacity of the user. The biases could be minimized by careful attention, capacity, tactful utilization, and knowledge of the user.
A. Sharma· Multi-Disciplinary Explorati...· 0 citations
The rapid popularization of Artificial Intelligence (AI) has extended beyond academic and industrial spaces into everyday social media discourse, with TikTok emerging as one of the most active arenas for AI-related public conversation. Although prior research has extensively examined TikTok’s algorithmic affordances and AI-related content circulation, limited attention has been given to the communicative roles of digital actors who actively shape public discourse on AI within TikTok’s participatory environment. This study examines how digital communication actors contribute to the formation, circulation, and reinforcement of AI discourse on TikTok through a qualitative netnographic approach. Data were collected from 45 publicly accessible TikTok videos published between May 2024 and June 2026, through non-participant observation using purposive quota sampling based on seven AI-related hashtags: #ArtificialIntelligence, #AI, #ChatGPT, #AITools, #AIIndonesia, #TeknologiAI, and #MachineLearning. Engagement metrics including likes, comment counts, and save counts were documented for each video. The analysis identifies five dominant communicative roles performed by digital actors: educators, opinion leaders, popularizers, critics, and amplifiers. Each role contributes distinct narrative framings of AI as a productivity tool, an economic opportunity, a threat to employment, an ethical concern, or a popular cultural trend. TikTok is positioned as an algorithmic digital public sphere where technological discourse is shaped through content formats, hashtag structures, visible engagement dynamics, and platform visibility mechanisms rather than unilaterally transmitted
Unknown authors· International Journal Of Hum...· 0 citations
This study analyzes how a government-operated chatbot shapes citizen interactions and public value through emotional, thematic and behavioral dynamics and demonstrates how chatbot-mediated processes influence citizen experience in digital government.
Tehila Tigist Neguse, H. Gabay, Iris Reychav et al.· Transforming Government: Peo...· 0 citations
An exploratory account of how AI use is embedded within broader emotional and relational dynamics, pointing to the need to consider AI engagement within the contexts in which social interaction is managed.
Nurashikin Salim, Ayşe Şafak, Merve Güçlü Aydoğan· Current Psychology· 0 citations
AI chatbots may support confidence by allowing users to ask questions, explore ideas, and express emotions without the same pressure they may feel in face-to-face situations, as the use of AI chatbots also creates concerns about reduced human interaction.
K. Khairuddin, Nur Shazana binti Abdul Rani, Siti Nur Izyandiyana binti Ab Hadi et al.· International journal of res...· 0 citations
Experimental comparisons with GPT-4o vanilla across three roles, evaluated through an ablation study and a multi-evaluator panel combining LLM-based and human judges, consistently rank XBot as the best performing system, demonstrating superior empathy, role stability and conversational depth, while GPT-4o vanilla exhibits pervasive persona drift across all experimental scenarios.
Luciano Caroprese, Ester Zumpano, M. Aracne et al.· Discover Artificial Intellig...· 0 citations
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