ReviewFrontiers in human neuroscience2025
Thirty years of public speaking anxiety research: topic modeling and semantic trend forecasting using LDA-Word2Vec integration.
Review in Frontiers in human neuroscience, 2025. 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
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Public speaking anxiety (PSA) is a widespread condition with profound psychological, educational, and occupational consequences. Despite increasing academic attention, few studies have systematically mapped the thematic development of PSA research or anticipated future directions. This study employs a semantically enriched framework integrating latent Dirichlet allocation (LDA) with Word2Vec to analyze 990 peer-reviewed journal articles (1995-2024) retrieved from the Web of Science Core Collection, spanning SSCI, SCI-Expanded, ESCI, and A&HCI indices. Nine major thematic clusters are identified, covering topics such as mental health distress, physiological reactivity, language apprehension, social phobia, and virtual reality interventions. Thematic evolution across four historical phases reveals growing conceptual convergence and an increasing focus on digital anxiety and assessment technologies. A Sankey diagram illustrates patterns of thematic continuity and transformation, highlighting both enduring topics and emerging lines of inquiry. To predict future research frontiers, two novelty indicators-Cluster Novelty and Topic Novelty-are introduced. Clusters focused on language learning (Topic 4), virtual therapy (Topic 6), and psychometric tools (Topic 8) emerge as the most temporally novel. This study provides a comprehensive, data-driven mapping of PSA research and offers methodological guidance for future interdisciplinary bibliometric analyses.
Indexed as
Identifiers
What OpenQuestion holds
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.