ArticlePloS one2026
Public sentiment and thematic evolution in the metaverse: A large-scale computational analysis of Twitter discourse.
Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
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Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
This study investigates public perception of the metaverse through a large-scale computational analysis of 52,874 English-language tweets. Leveraging sentiment analysis tools (VADER and RoBERTa) and unsupervised topic modeling (BERTopic), we categorize discourse into four thematic domains: general metaverse discussion, Meta's Horizon Worlds, metaverse-related cryptocurrency tokens, and virtual social events. Our findings reveal that 43.0% of tweets express positive sentiment, driven by enthusiasm for immersive innovation and digital transformation, while 23.6% convey skepticism, primarily concerning platform reliability, corporate dominance, and privacy. Sentiment surrounding Horizon Worlds reflects a paradox: underlying optimism is overshadowed by user frustration, with negative tweets generating disproportionately high engagement. Analysis of metaverse token discourse indicates robust investor interest, tempered by persistent concerns over market volatility and fraudulent schemes. Topic modeling further uncovers a notable narrative shift from speculative price-focused discussions toward utility-driven use cases. Virtual events (e.g., digital weddings, concerts) elicit the most positive sentiment (51.3%), with users frequently expressing emotional resonance and communal belonging, as visually reinforced by word cloud analysis. This research contributes to the literature on digital adoption and emerging technologies by mapping the evolving social discourse of the metaverse. It offers actionable insights for platform developers, investors, and educators seeking to align innovation with user expectations and provides a predictive lens for forecasting public readiness for the next generation of digital interaction.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.