Search arXiv⌕ Search
Home/Archive/arXiv

arXiv · 2510.06788

Unpacking Discourses on Childbirth and Parenthood in Popular Social Media Platforms Across China, Japan, and South Korea

Zheng Wei·Yunqi Li·Yucheng He·Yuelu Li·Xian Xu·Huamin Qu·Pan Hui·Muzhi Zhou
View original source ↗Read source document ↗Export metadata ↓

Abstract

Social media use has been shown to be associated with low fertility desires. However, we know little about the discourses surrounding childbirth and parenthood that people consume online. We analyze 219,127 comments on 668 short videos related to reproduction and parenthood from Douyin and Tiktok in China, South Korea, and Japan, a region famous for its extremely low fertility level, to examine the topics and sentiment expressed online. BERTopic model is used to assist thematic analysis, and a large language model QWen is applied to label sentiment. We find that comments focus on childrearing costs in all countries, utility of children, particularly in Japan and South Korea, and individualism, primarily in China. Comments from Douyin exhibit the strongest anti-natalist sentiments, while the Japanese and Korean comments are more neutral. Short video characteristics, such as their stances or account type, significantly influence the responses, alongside regional socioeconomic indicators, including GDP, urbanization, and population sex ratio. This work provides one of the first comprehensive analyses of online discourses on family formation via popular algorithm-fed video sharing platforms in regions experiencing low fertility rates, making a valuable contribution to our understanding of the spread of family values online.

Explore related subjects

cs.SIcs.CY

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Zheng Wei, Yunqi Li, Yucheng He, Yuelu Li, Xian Xu, Huamin Qu, Pan Hui, Muzhi Zhou. 2025-10-08. Unpacking Discourses on Childbirth and Parenthood in Popular Social Media Platforms Across China, Japan, and South Korea. https://arxiv.org/abs/2510.06788

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

The Benefit of Collective Intelligence in Community-Based Content Moderation is Limited by Overt Political Signalling

Social media platforms face increasing scrutiny over the rapid spread of misinformation. In response, many have adopted community-based content moderation systems, including Community Notes (formerly Birdwatch) on X (formerly Twitter), Community Notes on Meta, and Footnotes on TikTok. However, research shows that the current design of these systems can allow political biases to influence both the development of notes and the rating processes, reducing their overall effectiveness. We hypothesise that enabling users to collaborate on writing notes, rather than relying solely on individually authored notes, can enhance the overall quality of their notes. To test this idea, we conducted an online experiment in which participants jointly authored notes on politically misleading posts. We find that collaboration improves the helpfulness of notes, although the average effect depends on the interactional context. In particular, the benefits of collaboration decline when participants are made aware of one another's political affiliations. We also find that politically diverse teams improve note quality when evaluating Republican posts, while team composition does not meaningfully affect note quality for Democrat posts. These findings underscore the complexity of community-based content moderation and highlight the importance of understanding group dynamics and political diversity when designing more effective moderation systems.

cs.SI↗
arXiv2026

The Same Ledger, Different Verdicts: How Measurement Specification Determines On-Chain Concentration

Whether a public blockchain is "decentralized" is routinely settled by citing a concentration statistic. On two ERC-20 ledgers, Chainlink (LINK) and Uniswap (UNI) over a 90-day window, we show that verdict depends on measurement specification rather than the ledger itself. Four discretionary choices (holder population, address type, temporal aggregation, and entity resolution) move the balance HHI for UNI from 109 to 2,336 (a factor of 21), with every specification defensible. Over the same range, the Gini coefficient moves by less than 0.003 and does not change under entity resolution, demonstrating that Gini and HHI answer different questions and cannot substitute for one another. We further document an implementation choice - summing versus overwriting repeated transfers - that discards roughly 85% of volume and overturns a finding on wealth and structural position. Substantively, both ledgers are extraordinarily unequal in ownership (balance Gini = 0.990 and 0.998) yet unconcentrated in routing (weekly flow HHI = 421 and 386), with the two dimensions close to statistically independent across addresses. A parameterized criterion for hidden brokers identifies 30 and 18 zero-balance intermediaries, 12 shared across ledgers; a matched control confirms that degree thresholding, rather than learned embeddings, drives the discovery. Finally, on the governance ledger, proposal-eligible addresses and routing intermediaries are almost disjoint, so routing contestability is held at the pleasure of a rule layer with a Nakamoto coefficient of two. We conclude that on-chain concentration should be reported as a specified range rather than a point estimate.

cs.SI↗
arXiv2026

Optimal and heuristic strategies for evaluating the influence of coordinated behavior in information cascades and retweet networks

Coordinated Inauthentic Behavior (CIB) has become a major concern in online social platforms, yet its actual impact on information diffusion remains poorly understood. Existing research has primarily focused on detecting coordinated activity, while comparatively little attention has been devoted to quantifying its influence once detected. In this work, we introduce two complementary frameworks for the post-hoc evaluation of coordinated accounts. First, we formulate the problem on information cascades as a constrained influence maximization problem over directed trees and develop a polynomial-time dynamic programming algorithm that computes the optimal placement of coordinated nodes, providing an upper bound on their achievable influence. Second, motivated by the limited availability of diffusion cascades in real-world platforms, we propose a network-based framework that estimates influence directly from retweet networks using the independent cascade model and compares the observed placement of coordinated accounts against established heuristic baselines. We evaluate both approaches on Twitter/X data from the 2019 UK General Election and on a collection of verified state-backed information operation campaigns spanning multiple countries. While coordinated accounts exhibit limited influence in the UK cascades, the network-based analysis reveals substantial differences across campaigns, with several operations achieving influence comparable to or exceeding that of structurally central seed sets. Finally, by reconstructing cascades from the retweet networks, we show that the two frameworks produce consistent results, suggesting that the observed effects reflect intrinsic structural properties of coordinated activity rather than artifacts of the underlying methodology.

cs.SI↗