Social influence aggregation on Weibo: psychological process expectations and meso-level cascade regimes in media psychology
- 1School of Arts, Northeastern University, Shenyang, China
Abstract
Background: Media Psychology investigates how media environments organize attention, judgment, and social influence. On Weibo, the repost is a publicly observable sharing act through which users may reduce uncertainty, follow social proof, and respond to intermediary visibility. A persistent research problem is that studies often move from laboratory exposures or message features to virality outcomes without specifying how micro forwarding decisions aggregate into distinct meso-level influence ecologies.
Objectives: This article analyzes Weibo repost cascades as observational records of social-influence aggregation and asks whether deep–narrow (DN) vs. shallow–broad (SB) topology regimes differ in structural indicators that map onto chain-relayed influence, local-reinforcement opportunity, and brokerage.
Methods: Using the public Key Propagation Graph Generator (KPG)/The Chinese University of Hong Kong (CUHK) Weibo propagation corpus (November 2019–March 2022; ≈4,174 source events), rooted trees were reconstructed from parent–child graph exports that also include term frequency–inverse document frequency (TF–IDF) feature vectors (text itself is unused here). Eligible cascades with 20–250 nodes (Neligible = 1, 013) were partitioned by k-means (k = 2; silhouette = 0.513) on standardized depth and relative breadth; before balanced sampling, the pools contained 399 deep–narrow (DN) and 614 SB events. Size-tertile stratified draws yielded 40 DN and 40 SB cascades (N = 80; 6,527 nodes; 6,447 edges). Analyses used Python 3.12 with networkx (graph metrics), scipy (Welch tests), pandas, and matplotlib. Confirmatory DN/SB contrasts used Welch t-tests with Holm–Bonferroni adjustment; average path length was also regressed on continuous depth and breadth by ordinary least-squares (OLS).
Results: Supporting confirmatory H1–H2, DN cascades showed longer average path lengths (Cohen's d = 2.71) and higher modularity (d = 2.95) than SB cascades. Density and clustering did not separate regimes after Holm adjustment. Exploratory role-proxy betweenness was descriptively elevated under DN for high-, medium-, and low-branching nodes; hop-layer branching persisted deeper under DN. These effect sizes quantify a regime-level separation of influence opportunity structures rather than merely restating depth.
Conclusion: Social influence on Weibo aggregates into at least two structurally distinct ecologies—chain-relayed reinforcement opportunity vs. hub-broadcast exposure. The study supplies meso indicators for Media Psychology; it does not measure individual affect, attitudes, or uncertainty reduction as intrapersonal processes, and observational associations should not be read as causal psychological mechanisms.
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BibTeX
@article{wang2026social,
title = {{Social influence aggregation on Weibo: psychological process expectations and meso-level cascade regimes in media psychology}},
author = {Lulu Wang},
journal = {Frontiers in Psychology},
year = {2026},
month = oct,
doi = {10.3389/fpsyg.2026.1953616},
url = {https://doi.org/10.3389/fpsyg.2026.1953616},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Social influence aggregation on Weibo: psychological process expectations and meso-level cascade regimes in media psychology
AU - Lulu Wang
PY - 2026
DA - 2026/10/21
JO - Frontiers in Psychology
DO - 10.3389/fpsyg.2026.1953616
UR - https://doi.org/10.3389/fpsyg.2026.1953616
AB - Background: Media Psychology investigates how media environments organize attention, judgment, and social influence. On Weibo, the repost is a publicly observable sharing act through which users may reduce uncertainty, follow social proof, and respond to intermediary visibility. A persistent research problem is that studies often move from laboratory exposures or message features to virality outcomes without specifying how micro forwarding decisions aggregate into distinct meso-level influence ecologies. Objectives: This article analyzes Weibo repost cascades as observational records of social-influence aggregation and asks whether deep–narrow (DN) vs. shallow–broad (SB) topology regimes differ in structural indicators that map onto chain-relayed influence, local-reinforcement opportunity, and brokerage. Methods: Using the public Key Propagation Graph Generator (KPG)/The Chinese University of Hong Kong (CUHK) Weibo propagation corpus (November 2019–March 2022; ≈4,174 source events), rooted trees were reconstructed from parent–child graph exports that also include term frequency–inverse document frequency (TF–IDF) feature vectors (text itself is unused here). Eligible cascades with 20–250 nodes (Neligible = 1, 013) were partitioned by k-means (k = 2; silhouette = 0.513) on standardized depth and relative breadth; before balanced sampling, the pools contained 399 deep–narrow (DN) and 614 SB events. Size-tertile stratified draws yielded 40 DN and 40 SB cascades (N = 80; 6,527 nodes; 6,447 edges). Analyses used Python 3.12 with networkx (graph metrics), scipy (Welch tests), pandas, and matplotlib. Confirmatory DN/SB contrasts used Welch t-tests with Holm–Bonferroni adjustment; average path length was also regressed on continuous depth and breadth by ordinary least-squares (OLS). Results: Supporting confirmatory H1–H2, DN cascades showed longer average path lengths (Cohen's d = 2.71) and higher modularity (d = 2.95) than SB cascades. Density and clustering did not separate regimes after Holm adjustment. Exploratory role-proxy betweenness was descriptively elevated under DN for high-, medium-, and low-branching nodes; hop-layer branching persisted deeper under DN. These effect sizes quantify a regime-level separation of influence opportunity structures rather than merely restating depth. Conclusion: Social influence on Weibo aggregates into at least two structurally distinct ecologies—chain-relayed reinforcement opportunity vs. hub-broadcast exposure. The study supplies meso indicators for Media Psychology; it does not measure individual affect, attitudes, or uncertainty reduction as intrapersonal processes, and observational associations should not be read as causal psychological mechanisms.
SN - 1664-1078
ER -