Interdisciplinary study on popularity prediction of social classified hot online events in China

We offer an interdisciplinary study of computer science and social science, analyzing behavior surrounding three types of online events: political events, social events, and non-public events. Based on the intrinsic characteristics of the three event types, this paper creates an effective method to predict such events. We continuously followed and recorded data every 10 min for 10 months from September 14, 2012 to July 11, 2013, and collected over 14 million “hot” posts from Sina Weibo, the largest microblogging provider in China. After removing spammers and noises, we developed a database of 4180 hot online events and 7,761,395 threads. We found that people’s online behavior regarding event types varies in terms of follow-up statistics and the predictability of events. The Chinese are, typically, quite concerned with social affairs that relate most closely to their personal interests and preferences. People tend to cluster around political events more often than social events and non-public events. This is demonstrated by an algorithm embedded with a clustering growth pattern of events, which predicts the popularity of online political events above others. The statistical findings are justified by Habermas’ public sphere theory and the theory of vertical/horizontal collectivism/individualism. This research provides an interesting piece of computational social science work to assist in the analysis of incentives concerning China’s collective events.     

Consumers’ acceptance of information and communications technology in tourism: A review

The impact of information and communications technology (ICT) in tourism (e-tourism) has altered the ways tourism services are accessed and consumed. Ubiquitous and highly innovative ICTs provide different channels for consumers to use tourism services; thus, studies on e-tourism are numerous and fragmented. Different factors account for how consumers embrace these channels. The purpose of this study is to review studies on consumers’ acceptance or adoption of e-tourism in order to group the studies, synthesize the theories, models and frameworks used and identify the antecedents influencing consumers’ e-tourism acceptance and usage. A total of 71 studies from 2005 to 2016 (inclusive) from both tourism-based and non-tourism-based journals were selected, synthesized, and included. Based on their contexts, similarity and relevance, the 71 studies were segregated into three distinct groups. This study found that research among the groups is uneven. Implications and research directions are suggested.     

Social media in marketing: A review and analysis of the existing literature

People worldwide are largely engaged and attached with the web 2.0 technology and Social media platforms. By the same token, businesses start looking at such technologies as effective mechanisms to interact more with their customers. Equally, the related issues of social media marketing have been also the focus of attention for academics and researchers to expand the current understanding about such phenomena over the marketing area. Accordingly, the main aim of this study is to systematically examine and review the current studies that have conducted over the related area of social media and marketing. By reviewing approximately 144 articles, the researchers were able to provide an overview of the main themes and trends covered by the relevant literature such as the role of social media on advertising, the electronic word of mouth, customers’ relationship management, and firms’ brands and performance. In this review, it has also studied the most common research approaches adopted to examine the related issues of social media marketing. Further discussion is also introduced followed by an explanation of the current review limitations and recommended directions to be examined by future studies.     

Digital advertising around paid spaces,E-advertising industry’s revenue engine: A review and research agenda

We develop and describe a framework for research in a particular segment of digital advertising. Internet Advertising Paid Slots and Spaces (IAPS) is a neologism and work almost like a stock exchange for buying and selling advertising in various formats on designated spaces around web and make a significant contribution to Internet advertising revenues. These paid spaces were found to encompass diverse areas of Internet advertising that include search engine marketing, social media advertising and display advertising. Given the complexity of the modern digital advertising eco system, this literature review seeks to provide clarity, up-to-date knowledge and ongoing insights into Internet advertising channels, for managers making investment decisions in this context.     

Pandemic simulation of antivirals + school closures: buying time until strain-specific vaccine is available

A strain-specific vaccine is unlikely to be available in the early phases of a potential H5N1 avian influenza pandemic. It could be months and at the current production rate may not provide timely protection to the population. Intervention strategies that control the spread of infection will be necessary in this situation, such as the use of the US stockpile of antiviral medication coupled with a 6-month school closure. The agent-based simulation model, EpiSimS, was used to assess the impact of this intervention strategy followed by three different vaccine approaches: (1) 2-dose, 80% effective, (2) 1-dose, 30% effective, and (3) 1 dose, 80% effective. Simulations show that the combination of antivirals, school closures, and a strain-specific vaccine can reduce morbidity and mortality while in effect. A significant second infection wave can occur with current vaccine technology once school closures are relaxed, though an ideal vaccine is able to contain it. In our simulations, worker absenteeism increases in all cases mostly attributed to household adults staying home with children due to the school closures.

Individual behavior and macro social properties. An agent-based model

The paper aims at presenting an agent-based modeling exercise to illustrate how small differences in the cognitive properties of agents can generate very different macro social properties. We argue that it is not necessary to assume highly complicated cognitive architectures to introduce cognitive properties that matter for computational social science purposes. Our model is based on different simulation settings characterized by a gradual sophistication of behavior of agents, from simple heuristics to macro-micro feedback and other second-order properties. Agents are localized in a spatial interaction context. They have an individual task but are influenced by a collective coordination problem. The simulation results show that agents can generate efficiency at a macro level particularly when socio-cognitive sophistication of their behavior increases.

A (computational) social science perspective on societal transitions

This paper aims to illustrate how social sciences, sociology in particular, have theorized on societal transitions. The first section introduces some preliminary definitions. The assumption is that a societal transition is more than a social, economic or technological change. It is a large-scale and long-term macro process through which a given social system radically changes its structural basis, in terms of new socio-technical practices, governance rules, social and economic institutions, cultural frames, and patterns of social life. The second section provides an excursus on social science accounts on transitions. In particular, the attention has been given to Norbert Elias’ famous study on the rise and fall of the court society in France, between 17th and 18th century and to Manuel Castells’ recent analysis of the emergence of the network society. The third section discusses problems and challenges of standard approaches and suggests some building blocks of societal transition models, taken from complexity and social simulation literature. The concluding section suggests some way-forward measures towards a computational social science approach to societal transitions.

I Saw You in the News: Mediated and Direct Intergroup Contact Improve Outgroup Attitudes

This study extends the boundary conditions of mediated contact theory by (a) differentiating between mediated contact quantity and quality, (b) examining whether mediated contact exerts effects above and beyond direct contact, and (c) offering causal and generalizable evidence on the effects of exposure to numerous individual outgroup members in news media. We match individual‐level data from a representative panel survey with data on the amount of coverage about members from two outgroups and with the results from validated sentiment analysis. Mediated contact, and especially its quantity, improved outgroup attitudes independently of direct contact. These findings emerged for both outgroups and across two outcome measures.     

Linking Network Structure to Support Messages: Effects of Brokerage and Closure on Received Social Support

Building on the network theory of brokerage and closure, this study takes a structural approach to examine network structure and its influence on reception of different types of social support. The study extracted ego networks of 227 active users from a large online health social network and tracked their received supportive comments on personal profiles for 3 months. A total of 3,270 comments were analyzed. The results showed that network brokerage (operationalized as effective size) predicted the amount of informational and network support, whereas network closure (operationalized as local clustering coefficient) predicted the amount of emotional and esteem support received on one's profile. Moreover, brokerage was found to predict received emotional support. Theoretical and practical implications were discussed.