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The purpose of this paper is to identify the key determinants of the information value of enterprises’ micro-blogs, drawing on the consumer’s perspective. This paper examines the effects of such information value on consumers’ purchase intention through the building of online brand equity. The paper also investigates how perceived usefulness intervenes in the relationship between micro-blog information value and consumer purchase intention.

The proposed research model is examined empirically using a survey of 315 users of the Sina micro-blog. The statistical analysis applies a method based on variance using partial least squares.

The results show that online retailers’ micro-blog posts, which are characterized by informativeness and persuasiveness as perceived by customers, positively impact online retailers’ brand equity, which in turn influences consumer purchase intention. In addition, perceived information usefulness is found to be an important contextual factor that moderates the relationship between perceived persuasiveness and online retailer brand equity.

This work adds significance to the literature by extending the research on micro-blog marketing and also provides practical recommendations for online retailers on the operation of micro-blogs.

The purpose of this paper is to investigate how government affairs micro-blog (also referred to as GAM) are applied to the disclosure of government emergency information in China, to identify its existing problems and to provide solutions.

In this paper, online research, case analysis and other methods were used to analyze the application status of China’s Government micro-blog in emergency information disclosure in recent years. Based on the relevant data and cases, a systematic theoretical research is conducted according to the established research framework.

There are some problems in the application of GAM to crisis management, such as insufficient information dissemination, incomplete information disclosure, fragmentation of information and lack of dynamic updating and communication. So, it is necessary to strengthen the organization and management of GAM, establish a perfect emergency management mechanism of GAM, increase the positive influence of GAM on public opinions and establish an evaluation accountability system of administrative micro-blog management.

The analysis of the application of GAM to the disclosure of government emergency information and the proposed strategies for improving its performance are all original, and they are both meaningful to more effective usage of GAM and facilitation of government emergency information disclosure.

The purpose of this paper is to present a new human dynamics model to explain the process of verified users' (VUs) posting on Sina micro-blog.

A common human dynamics research method with three steps is applied. Firstly, a large-scale behavioral dataset is collected involving 495 VUs and five topics on Sina micro-blog. Second, five important indicators that reveal the characteristics of posting behavior are analyzed. Then, a quantitative model is constructed to describe the process of posting behavior, and its validity is verified by simulations.

Three important characteristics of VUs' micro-blog posting behavior are observed: fat-tailed distribution, fluctuation and periodicity. These characteristics do not fit the assumption of interest-driven models proposed by previous literature. An optimized task-driven model is introduced to describe this complex phenomenon mathematically. The model is verified on empirical data, confirming that task-driven models can be optimized to explore information behavior on social media.

Being different from previous studies that mainly describe common users' posting behavior on social media by applying interest-driven models, this paper customizes an optimized task-driven model for VUs, who mainly treat social media as a platform for work and play a crucial role in information creation on social media.

This chapter offers reflections on the successes and failures of integrating the micro-blogging platform Twitter into a first-year university class. Twitter, intended as a way to answer the question “What are you doing?” is now used in originally unexpected ways. Broadly speaking, Twitter's popularity can be traced to three factors: conversation between users; a decentralized ecosystem of third-party applications; and as a result, the distributed nature of the users. Adopted by educators in higher education, Twitter has been used as: an object for study, a tool to communicating classroom announcements, as a way to enable student to reflect on their learning, a chance to get instant feedback from students, and as the specific tool used to facilitate in-class conversations. The ongoing use of micro-blogging also appears to have an ability to change the social dynamics of a classroom, expanding the social of the classroom beyond the physical. While identifying Twitter's limitations, the chapter outlines the most significant outcome from the author's integration of Twitter: an evolution of blended learning, proposed as a plesiochronous learning model, where learning occurs outside the classroom, with learner and instructor in different places but occurring at (virtually) the same time.

Delivering messages and information to potentially interested users is one of the distinguishing applications of online enterprise social network (ESN). The purpose of this paper is to provide insights to better understand the repost preferences of users and provide personalized information service in enterprise social media marketing.

It is accomplished by constructing a target audience identification framework. Repost preference latent Dirichlet allocation (RPLDA) topic model topic model is proposed to understand the mass user online repost preferences toward different contents. A topic-oriented preference metric is proposed to measure the preference degree of individual users. And the function of reposting forecasting is formulated to identify target audience.

The empirical research shows the following: a total of 20 percent of the repost users in ESN represent the key active users who are particularly interested in the latent topic of messages in ESN and fits Pareto distribution; and the target audience identification framework can successfully identify different target key users for messages with different latent topics.

The findings should motivate marketing managers to improve enterprise brand by identifying key target audience in ESN and marketing in a way that truthfully reflects personalized preferences.

This study runs counter to most current business practices, which tend to use simple popularity to seek important users. Adaptively and dynamically identifying target audience appears to have considerable potential, especially in the rapidly growing area of enterprise social media information service.

By drawing on the research paradigm of collective action that occurs in physical space, the present study aims to explore the antecedent predictors of network social mobilization – feeling of injustice – and discuss the emotional mechanism of this prediction: mediating effect of anger and resentment.

Micro-blog postings about network social mobilization were collected to develop the dictionary of codes of fairness, anger and resentment. Then, according to the dictionary, postings on Sina Weibo were coded and analyzed.

The feeling of injustice predicted network social mobilization directly. The predictive value was 27% and 33%, respectively during two analyses. The feeling of injustice also predicted social mobilization indirectly via anger and resentment. In other words, anger and resentment account for the active mechanism in which the feeling of injustice predicts network social mobilization. Mediating effect value was 29.63% and 33.33% respectively.

This study is our first exploration to use python language to collect data from human natural language pointing on micro-blog, a large number of comments of netizen about certain topic were crawled, but a small portion of the comments could be coded into analyzable data, which results in a doubt of the reliability of the study. Therefore, we should put the established model under further testing.

In the cyberspace, this study confirms the mechanism of network social mobilization, expands and enriches the research on social mobilization and deepens the understanding of social mobilization.

This study provides an empirical evidence to understand the network social mobilization, and it gives us the clue to control the process of network social mobilization.

This study uses the Python language to write Web crawlers to obtain microblog data and analyze the microblog content for word segmentation and matching thesaurus. It has certain innovation.

Plato and contemporary thinkers including American philosopher Martha Nussbaum have emphasized the need for political consciousness among the youth. Cultivating Humanity: A Classical Defence of Reform in Liberal Education by Nussbaum expressed that

It would be catastrophic to become a nation of technically competent people who have lost the ability to think critically, to examine themselves, and to respect the humanity and diversity of others.

It would be catastrophic to become a nation of technically competent people who have lost the ability to think critically, to examine themselves, and to respect the humanity and diversity of others.

Ideologically, it has been proven that advancement in technology can shift social ethos if we use it intelligently and then technology can lead to activism.

Digital activism can be defined as the use of electronic communication devices, for example, social media, Twitter, Facebook, YouTube, e-mail, e-blogging, micro-blogging and podcast for different forms of activism. It enables citizens to express ideology and spread information to a large audience regarding human rights. In this context, researchers have explored the level of digital activism among pupil teachers and found very little awareness regarding the same. Findings also reveal that the level of digital activism does not have any significant effect on attitude toward human rights and peace. Although findings reveal that attitude toward peace and human rights is positively correlated with each other. Therefore, on the basis of the findings, an intervention program for digital activism has been suggested at the end of this chapter that can foster digital activism among them.

Followee recommendation is a problem rapidly gaining importance in Twitter as well as in other micro-blogging communities. To find interesting users to follow, most recommendation systems leverage different factors such as graph topology or user-generated content, among others. Those systems mostly disregard, however, the effect of psychological characteristics, such as personality, over the followee selection process. As personality is considered one of the primary factors that influence human behaviour, the purpose of this paper is to shed some light on the impact of personality traits on followee selection.

The authors performed a data analysis comparing the similarity among Twitter users and their followees regarding personality traits. The authors analysed three different similarity measures. First, the authors computed an overall similarity considering the five personality traits or dimensions of the Five-Factor model as a whole. Second, the authors computed the dimension-to-dimension similarity considering each individual personality trait independently of each other. Third, the authors computed a cross-dimension similarity considering each personality dimension in relation to the others.

This study showed that personality should be considered as a distinctive factor in the process of followee selection. However, personality dimensions should not be analysed as a whole as the overall personality similarity might not accurately assess the actual matching between individuals. Instead, the performed data analysis showed the existence of relations among the individual dimensions. Thus, the importance of considering each personality trait with respect to others is stated.

This study is among the firsts to study the impact of personality, one of the primary factors that influence human behaviour and social relationships, in the selection of followees in micro-blogging communities.

This paper aims to research as to how Twitter is influential as an electronic word-of-mouth (e-WOM) communication tool and thereby affecting movie market. In present days, social media is playing an important role in connecting people around the globe. The technology has provided a platform in the social media space for people to share their experiences through text, photos and videos. Twitter is one such online social networking media that enables its users to send and read text-based messages of up to 140 characters, known as “tweets”. Twitter has nearly 200 million users and billions of such tweets are generated by users every other day. Social media micro-blogging broadcasting networks such as Twitter are transforming the way e-WOM is disseminated and consumed in the digital world. Twitter social behaviour for the Hollywood movies has been assessed across seven countries to validate the two basic blocks of the honeycomb model – sharing and conversation. Twitter behaviour was studied for 27 movies in 22 different cities of seven countries and for six genres with a total tweets of 9.28 million. The difference of Twitter social media behaviour was compared across countries, and “sharing” and “conversation” as two building blocks of the honeycomb model were studied. t-Test results revealed that the behaviour is different across countries and across genres.

The objective of the paper is to analyse Twitter messages on an entertainment product (movies) across different regions of the world. Hollywood movies are released across different parts of the world, and Twitter users are also in different parts of the world. The objective is to hence validate “conversation” and “sharing” building blocks of the honeycomb model. The research is confined to analysing Twitter data related to a few Hollywood movies. The tweets were collected across nine different cities spanning four different countries where English language is prominent. To understand the Twitter social media behaviour, a crawler application using Python and Java was developed to collect tweets of Hollywood movies from the Twitter database. The application has incorporated Twitter application programming interfaces (APIs) to access the Twitter database to extract tweets according to movies search queries across different parts of the world. The searching, collecting and analysing of the tweets is a rather challenging task because of various reasons. The tweets are stored in a Twitter corpus and can be accessed by the public using APIs. To understand whether tweets vary from one country to another, the analysis of variance test was conducted. To assess whether Twitter behaviour is different, and to compare the behaviour across countries, t-tests were conducted taking two countries at a time. The comparisons were made across all the six genres. In this way, an attempt was made to obtain a microscopic view of the Twitter behaviour for each of the seven countries and the six genres.

The findings show that the people use social media across the world. Nearly 9.28 million tweets were from seven countries, namely, USA, UK, Canada, South Africa, Australia, India and New Zealand for 27 Hollywood movies. This is indicative of the fact that today, people are exchanging information across different countries, that people are conversing about a product on social media and people are sharing information about a product on social media and, thus, proving the hypothesis. Further, the results indicate that the users in USA, Canada and UK, tweet more than the other countries, USA and UK being the highest in tweets followed by the Canada. On the other hand, the number of tweets in Australia, India and South Africa are low with New Zealand being the lowest of all the countries. This indicates that different countries’ users have different social media behaviour. Some countries use social media to communicate about their experience more than in some other country. However, consumers from all over the world are using Twitter to express their views openly and freely.

This research is useful to scholars and enterprises to understand opinions on Twitter social media and predict their impact. The study can be extended to any products which can lead to better customer relationship management. Companies can use the Internet and social media to promote and get feedback on their products and services across different parts of the world. Governments can inform the public about their new policies, benefits of governmental programmes to people and ways to improve the Internet reach to more people and also for creating awareness about health, hygiene, natural calamities and safety.

The purpose of this paper is to explore how to use social media in e-government to strengthen interactivity between government and the general public.

Categorizing the determinants to interactivity covering depth and breadth into two aspects that are the structural features and the content features, this study employs general linear model and ANOVA method to analyse 14,910 posts belonged to the top list of the 96 most popular government accounts of Sina, one of the largest social media platforms in China.

The main findings of the research are that both variables of the ratio of multimedia elements, and the ratio of external links have positive effects on the breadth of interactivity, while the ratio of multimedia features, and the ratio of originality have significant effects on the depth of interactivity.

The contributions are as follows. First, the authors analyse the properties and the topics of government posts to draw a rich picture of how local governments use the micro-blog as a communications channel to interact with the public. Second, the authors conceptualize the government online interactivity in terms of the breadth and depth. Third, the authors identify factors that will enhance the interactivity from two aspects: structural features and content features. Lastly, the authors offer suggestions to local governments on how to strengthen the e-government interactivity in social media.