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Since the opening of China (aka, reform and opening-up), a great number of rural residents have migrated to large cities in the past 40 years. Such a one-way population inflow to urban areas introduces nontrivial social conflicts between urban natives and migrant workers. This study aims to investigate the most discussed topics about migrant workers on Sina Weibo along with the corresponding sentiment divergence.

An exploratory-descriptive-explanatory research methodology is employed. The study explores the main topics on migrant workers discussed in social media via manual annotation. Subsequently, guided LDA, a semi-supervised topic modeling approach, is applied to describe the overall topical landscape. Finally, the authors verify their theoretical predictions with respect to the sentiment divergence pattern for each topic, using regression analysis.

The study identifies three most discussed topics on migrant workers, namely wage default, employment support and urban/rural development. The regression analysis reveals different diffusion patterns contingent on the nature of each topic. In particular, this study finds a positive association between urban/rural development and the sentiment divergence, while wage default exhibits an opposite relationship with sentiment divergence.

The authors combine unique characteristics of social media with well-established theories of social identity and framing, which are applied more to off-line contexts, to study a unique phenomenon of migrant workers in China. From a practical perspective, the results provide implications for the governance of urbanization-related social conflicts.

The purpose of this research is to investigate the usage characteristics and the information propagation patterns of Chinese microblogs in different stages of an epidemic, given that the microblogging in China is different from other parts of the world. In addition, the authors aim to conceptualize the roles of different users and provide insights for using microblogging platforms to disseminate information in this context.

The authors conducted an analysis on Sina Weibo microblogs about the African Swine Fever epidemic from August to October 2018. The authors firstly applied a label propagation algorithm to classify users into government, media, verified users and nonverified users. The authors analyzed several user metrics, traced the information propagation patterns of their microblogs and calculated the average speed of information propagation using computational approaches.

The authors’ findings show that different types of users played different roles, such as supplying information, amplifying information, relaying information and engaging with other users. The microblogs posted by media dominated the propagation in most cases, but general users can propagate information faster. The direction of information propagation is one-way for the majority of microblogs, and few users repost earlier information. Additionally, microblogs attract more attention at the beginning and the middle phases of an epidemic. In the context of managing epidemics, the authors recommend governments and other verified users can work together to use microblogging platforms efficiently.

This research is one of the few studies to investigate information propagation patterns of different user categories on a Chinese microblogging platform during an epidemic. The authors’ work can be used by government agencies and public health authorities for disseminating information efficiently during epidemics or emergencies, especially in the early stages.

Social influence plays a crucial role in determining the size of information diffusion. Drawing on threshold models, we reformulate the nonlinear threshold hypothesis of social influence.

We test the threshold hypothesis of social influence with a large dataset of information diffusion on social media.

There exists a bell-shaped relationship between social influence and diffusion size. However, the large network threshold, limited diffusion depth and intense bursts become the bottlenecks that constrain the diffusion size.

The practice of viral marketing needs innovative strategies to increase information novelty and reduce the excessive network threshold.

In all, this research extends threshold models of social influence and underlines the nonlinear nature of social influence in information diffusion.

The purpose of this paper is to present an empirical assessment of the diffusion of advertising messages on microblogging sites. The diffusion properties of advertising messages are quantified based on the following three aspects: diffusion breadth, depth, and speed. Furthermore, this study examines the influence of message- and advertiser-level factors on the diffusion of advertising messages.

The study data comprises 20,000 advertising messages that are randomly drawn from a popular microblogging web site in China. Five message-level factors and four advertiser-level factors are constructed based on the information retrieved from the microblogging web site. Generalized linear modeling is adopted to examine the effects of such factors on the diffusion properties of advertising messages.

The positive driving forces underlying the diffusion of advertising messages on microblogging sites include message length, the advertisers’ in-degrees, and their reputation. The diffusion of advertising messages is hampered by typicality, affectivity, the completeness of the information of the advertising messages, and advertisers’ out-degrees.

To achieve optimal diffusion on microblogging sites, advertisers should select the appropriate time windows for releasing advertising messages. Moreover, advertisers should actively increase the number of fans, use less typical and less emotional words in advertising messages, and eliminate unnecessary URLs in such messages.

This study contributes to the diffusion theory by identifying the mixed effects of different information attributes on the diffusion of advertising messages on microblogging sites, and examining the roles of advertisers’ structural characteristics in the diffusion of advertising messages. Furthermore, the results illustrate how consumers cope with the advertisers’ sales presentations on microblogging sites.

This study aims to investigate the mechanism of the misinformation spread based on the elaboration likelihood model and the effects of four factors – emotion, topic, authority and richness – on the depth, breadth and structural virality of misinformation spread.

The authors collected 2,514 misinformation microblogs and 142,006 reposts from Weibo, used deep learning methods to identify the emotions and topics of misinformation and extracted the structural characteristics of the spreading network using the network analysis method.

Results show that misinformation has a smaller spread size and breadth than true news but has a similar spread depth and structural virality. The differential influence of emotions on the structural characteristics of misinformation propagation was found: sadness can promote the breadth of misinformation spread, anger can promote depth and disgust can promote depth and structural virality. In addition, the international topic, the number of followers, images and videos can significantly and positively influence the misinformation's spread size, depth, breadth and structural virality.

The influencing factors of the structural characteristics of misinformation propagation are clarified, which is helpful for the detection and management of misinformation.

The purpose of the paper is to deepen the understanding of supply chain performance objectives in the humanitarian context by striving to understand the underlying goals and conceptual variables behind the measurement of performance, such as efficiency.

The research is an in-depth case study with one humanitarian organization. The data are gathered with mixed methods over a two-year period. Interviews were conducted in August 2010 and April 2012, and a survey conducted in October 2012.

Misalignments are detected among different groups in humanitarian operations and between their goals and processes. These misalignments could possibly be corrected through long-term thinking in short-term operations by considering sustainability aspects throughout humanitarian assistance, for example. In addition, efficiency was a commonly identified objective in the case organization, although the definition varied widely and extended beyond the traditional definition of productivity to include planning, accountability and quality.

Better communication and definition of terms is necessary to align goals and the power hierarchy in humanitarian supply chains, where operations seem to be structured more according to donor requirements then beneficiary needs.

This is an in-depth case study, applying goal-setting theory to study supply chain performance. The study further responds to the public “aid efficiency” discussion by striving to recognize how efficiency is understood and how it can be measured in a humanitarian supply chain.

The purpose of this paper is to explore factors influencing social media usage effectiveness of publishing-related entities and discuss the differences between publishing-related individuals and organizations in their usage of social media and the differences between commercial organizations and public service organizations (such as libraries).

This paper studied 546 publishing-related entities’ accounts on the leading Chinese social media and built a theoretical model for the usage of social media by publishing-related entities. Furthermore, it examined the influencing factors from two aspects: power of influence of an entity (entity influence) and the relational interaction of a publishing-related entity with its audience (interactive relationship).

The study found that for publishing-related individual users of social media, entity influence has a greater positive effect on the effectiveness of social media usage than on the effect of interactive relationship. For publishing-related commercial organizations, the entity influence and interactive relationship have equal impacts on the effectiveness of social media usage. It is also found that interactive relationship has a stronger positive effect on the usage effectiveness of social media, especially for publishing-related public service organizations.

This research fills the gap in the research of comparative analysis in the understanding of social media usage by individuals and organizations related to publishing activities. Moreover, it has tried to propose a theoretical model that can help promote the effectiveness of social media usages by various publishing-related entities and their business strategies.

The rising threat of tropical cyclones in Zimbabwe is of great importance in establishing the general sources of humanitarian supply chain risks and assessing their negative impact on relief operations. There is a scarcity of studies that collate such evidence toward enhanced humanitarian supply chains in Southern Africa. With this in mind, this study explored scattered evidence on supply chain risks in the delivery of humanitarian aid to victims of Cyclone Idai in Zimbabwe.

This reflective study evaluates supply chain risks associated with Cyclone Idai humanitarian relief operations through qualitative in-depth interviews with relevant actors in the field. The data were triangulated with secondary information from associated publications, blogs and newspapers to reflect the truth about the phenomena under investigation.

The results show that Cyclone Idai disaster response operations were adversely affected by social, economic and political/governmental risk factors. In the same breath, poor or inadequate infrastructure and environmental factors were also contributing factors toward the futility of humanitarian relief operations.

This study is significant as it endeavors to contribute toward humanitarian supply chain management, specifically in assisting humanitarian organizations with suggested strategies that would work toward making humanitarian relief supply chains more resilient. However, more research needs to be done toward optimized implementation strategies for the suggested framework.

It is to the best knowledge of these researchers that this is a unique study carried out to examine humanitarian supply chain risk factors in Cyclone Idai relief operations in Zimbabwe.

This paper aims to understand the impact of the internet on different value activities in a physical goods (newspaper) supply chain.

Case studies were used to obtain rich data from three newspaper companies. The selected case study companies had experienced changes in their value chains as a result of the internet.

The internet has led to falling advertising revenues and dwindling circulations. The companies reacted to this by developing online news services, which do not have the distribution costs of a physical product, enable the customisation of editorial and advertising content, and facilitate the co‐creation of news content with consumers. Moving online has, however, not fully compensated for the losses in revenues. Readers were reluctant to pay for online content, the income from of the sale of web‐based advertising space was significantly lower than for the printed form, and journalists resisted co‐creation.

The small sample of cases limits the generalisability of the findings.

Regional newspapers face problems developing an effective online news service to enable them to remain relevant in the communities they serve. The findings suggest that, although newspapers have adopted multimedia, and now have some user generated content, there is a reluctance to consider greater usage of additional forms of news production and e‐tools.

This paper examines how digital media are displacing physical goods from a value chain. There is evidence that co‐creation, a variable so far neglected in the literature on internet supply chains, can have a critical impact on value adding/creation activities.

Online social networks are increasingly important venues for businesses to promote their products and image. However, information propagation in online social networks is significantly more complicated compared to traditional transmission media such as newspaper, radio, and television. In this chapter, we will discuss research on modeling and forecasting diffusion of virally marketed content in social networks. Important aspects include the content and its presentation, the network topology, and transmission dynamics. Theoretical models, algorithms, and case studies of viral marketing will be explored.