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The purpose of this paper is to use Weibo as a window to examine the Chinese netizens’ online attitudes and responses to two sets of population policy: the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy. The population policy change from the rigid One-Child Policy to the Selective Two-Child Policy then to the Universal Two-Child Policy aroused great attention of the Chinese people.

This research uses the crawler technique to extract data on the Sina Weibo platform. Through opinion mining of Weibo posts on two sets of population policy, the Weibo users’ online opinions on the Two-Child Policy are analyzed from two perspectives: their attention intensity and sentiment tendency. The research also use the State Bureau of Statistics of China’s national population data between 2011 and 2016 to examine the Chinese people’s actual birth behaviors after implementing the two different sets of the Two-Child Policy.

The research findings indicate that the Selective Two-Child Policy (Phase 2) and the Universal Two-Child Policy are good examples of thematic public sphere of Weibo. Weibo posts on the two sets of the Two-Child Policy have undergone different opinion cycles. People from economically developed regions and populous regions have paid more attention to both sets of Two-Child Policy than their counterparts in the less developed and less populated regions. Men pay more attention to the Two-Child Policy than women do. Despite people’s huge attention to the new population policy, the population growth after the policy is not sustainable.

The new population policy alone is difficult to boost China’s population within a short period of time. The Chinese Government must provide its people with enough incentives and supporting welfare to make the population growth happen.

These findings have important implications for understanding the dynamics of online opinion formation and changing population policy in China.

Sina Weibo and Twitter are the top microblogging platforms with billions of users. Accordingly, these two platforms could be used to understand the public mood. In this paper, the authors want to discuss how to generate and compare the public mood on Sina Weibo and Twitter. The predictive power of the public mood toward commodity markets is discussed, and the authors want to solve the problem that how to choose between Sina Weibo and Twitter when predicting crude oil prices.

An enhanced latent Dirichlet allocation model considering term weights is implemented to generate topics from Sina Weibo and Twitter. Granger causality test and a long short-term memory neural network model are used to demonstrate that the public mood on Sina Weibo and Twitter is correlated with commodity contracts.

By comparing the topics and the public mood on Sina Weibo and Twitter, the authors find significant differences in user behavior on these two websites. Besides, the authors demonstrate that public mood on Sina Weibo and Twitter is correlated with crude oil contract prices in Shanghai International Energy Exchange and New York Mercantile Exchange, respectively.

Two sentiment analysis methods for Chinese (Sina Weibo) and English (Twitter) posts are introduced, which can be reused for other semantic analysis tasks. Besides, the authors present a prediction model for the practical participants in the commodity markets and introduce a method to choose between Sina Weibo and Twitter for certain prediction tasks.

With the rapid development of social media in the past few years, some dark aspects of usage have appeared, e.g., Weibo addiction. Therefore, the purpose of this paper is to address the question of how Weibo keeps users hooked.

The study utilizes the netnography method to explore the symptoms of Weibo addiction and how it is formed.

First, some Weibo users have typical symptoms of addictive behavior, such as withdrawal, loss of control and general living problems; second, narcissism plays an important role in the process of Weibo addiction and has a stronger effect on content generation than content consumption; third, some users use Weibo as a means to alleviate anxiety, but they can then become more anxious owing to addiction; and fourth, the effect of comments has two sides – on the one hand, comments are one kind of feedback to posts, satisfying posters’ social needs, while on the other hand, a storytelling system consists of one post and its comments, upon which some Weibo users become more dependent.

This research is only a preliminary, exploratory study. Therefore, care should be taken when interpreting these findings.

This study should help social media service providers and users to pay attention to the risk of social media addiction. Social media service providers should take social responsibility, design more user-oriented guidelines for marketing ethics and launch more responsible marketing activities. Users should enhance self-control and better balance social media use and offline real life.

Netnography has not been widely used as an addictive behavior research technique. This study is further bolstered because it has also noticed the difference of addiction mechanisms between addictive micro-bloggers and their followers.

The purpose of this paper is to investigate how, in China, postings on social media site Weibo reflect as well as accelerate the reshaping of traditional values. As Chinese social media extend their reach outside China, the displays of visible desire, hedonism and materialism could influence global consumption ethos.

Using interpretive content analysis, over 250 Weibo postings of 8 selected Weibo users, from the network of one of the authors, were identified, coded and interpreted. The users were selected based on their frequency, variety and expressiveness of postings.

Weibo is playing a critical role in transforming Chinese consumer values. Via Weibo, personal consumption experiences are available for public gaze. Consequently, desire for powerfully signified objects and experiences is more visible; “enjoy now” is turning out to be an appreciated life attitude, and materialism and hedonism are growing irresistibly. As a result, the traditional Chinese consumer values – suppressing desire, delaying gratification and thriftiness – are losing ground in Chinese society. Also, as Weibo makes the influence of the elite as well as electronic word-of-mouth very powerful, the values of the elite and grassroots groups are actually converging instead of being separated by substantial chasms that have existed historically.

Sina Weibo had a US initial public offering (IPO) of its stock in April, 2014, and many other China-based Internet firms were getting set for US IPOs. This paper provides unique insights for Chinese social media companies’ potential global impact. Future social media contexts would be shaped by collision as well as convergence of Asia-centric and USA-centric platforms. This paper lays the groundwork for studying such interactions.

In-depth interpretations of Weibo postings contribute to our understanding of how social media impact Chinese society now and would potentially affect global societies later. This is a pioneering study on the massive influences of social media on the macro-level consumer behavior.

The purpose of this paper is to explore the Chinese microblog users’ psychological motivations and the association between users’ motivations and their offline civic and political engagement. Specifically, this study examines what the psychological impetuses of Weibo use are and how they promote the young citizens’ civic and political involvement.

The data were collected through the web-based survey with a total sample of 426 people. Principal components factor analysis, correlation analysis, and hierarchical multiple regressions were sequentially carried out to address the research questions.

The findings reveal that there are four major motives for using Weibo: information, socializing, recognition seeking and entertainment. Interestingly, seeking social needs is positively and significantly related to increasing young people’s civic participation, but not political participation.

Theoretically, the research demonstrates that the uses and gratifications is a suitable approach for analysis of psychological antecedents of Weibo use and subsequent outcomes. Practically, it will help understand the dynamics of how the new media technology may engender democratic development and change.

Although the growing significance of social media has drawn considerable attention, little research has been conducted to assess the political consequences of Weibo. The current study fills the void by investigating whether Weibo functions as an effective tool to facilitate democratic engagement in contemporary China. The obtained results may provide insight into the relationship between the gratification structures and engagement in other social settings.

With the development and application of mobile internet access, social media represented by Weibo, WeChat, etc. has become the main channel for information release and sharing. High-impact users in social networks are key factors stimulating the large-scale propagation of information within social networks. User influence is usually related to the user’s attention rate, activity level, and message content. The paper aims to discuss these issues.

In this paper, the authors focused on Sina Weibo users, centered on users’ behavior and interactive information, and formulated a weighted interactive information network model, then present a novel computational model for Weibo user influence, which combined multiple indexes such as the user’s attention rate, activity level, and message content influence, etc., the model incorporated the time dimension, through the calculation of users’ attribute influence and interactive influence, to comprehensively measure the user influence of Sina Weibo users.

Compared with other models, the model reflected the dynamics and timeliness of the user influence in a more accurate way. Extensive experiments are conducted on the real-world data set, and the results validate the performance of the approach, and demonstrate the effectiveness of the dynamics and timeliness. Due to the similarity in platform architecture and user behavior between Sina Weibo and Twitter, the calculation model is also applicable to Twitter.

This paper presents a novel computational model for Weibo user influence, which combined multiple indexes such as the user’s attention rate, activity level, and message content influence, etc.

This study argues that online user comments on social media platforms provide feedback and evaluation functions. These functions can provide services for the relevant departments of organizations or institutions to formulate corresponding public opinion response strategies.

This study considers Chinese universities’ public opinion events on the Weibo platform as the research object. It collects online comments on Chinese universities’ network public opinion governance strategy texts on Weibo, constructs the sentiment index based on sentiment analysis and evaluates the effectiveness of the network public opinion governance strategy adopted by university officials.

This study found the following: First, a complete information release process can effectively improve the effect of public opinion governance strategies. Second, the effect of network public opinion governance strategies was significantly influenced by the type of public opinion event. Finally, the effect of public opinion governance strategies is closely related to the severity of punishment for the subjects involved.

The theoretical contribution of this study lies in the application of image repair theory and strategies in the field of network public opinion governance, which further broadens the scope of the application of image repair theory and strategies.

This study expands online user comment research to network public opinion governance and provides a quantitative method for evaluating the effect of governance strategies.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-05-2022-0269

The purposes of this paper are to (1) explore how personality traits pertaining to the dominance influence steadiness compliance model manifest themselves in terms of user interaction behavior on social media and (2) examine whether social interaction data on social media platforms can predict user personality.

Social interaction data was collected from 198 users of Sina Weibo, a popular social media platform in China. Their personality traits were also measured via questionnaire. Machine learning techniques were applied to predict the personality traits based on the social interaction data.

The results demonstrated that the proposed classifiers had high prediction accuracy, indicating that our approach is reliable and can be used with social interaction data on social media platforms to predict user personality. “Reposting,” “being reposted,” “commenting” and “being commented on” were found to be the key interaction features that reflected Weibo users' personalities, whereas “liking” was not found to be a key feature.

The findings of this study are expected to enrich personality prediction research based on social media data and to provide insights into the potential of employing social media data for the purpose of personality prediction in the context of the Weibo social media platform in China.