Feedback between node and network dynamics can produce real-world network properties

Real-world networks are characterized by common features, including among others a scale-free degree distribution, a high clustering coefficient and a short typical distance between nodes. These properties are usually explained by the dynamics of edge and node addition and deletion.     

Order preservation in a generalized version of Krause’s opinion dynamics model

Krause’s model of opinion dynamics has recently been the subject of several studies, partly because it is one of the simplest multi-agent systems involving position-dependent changing topologies. In this model, agents have an opinion represented by a real number and they update it by averaging those agent opinions distant from their opinion by less than a certain interaction radius. Some results obtained on this model rely on the fact that the opinion orders remain unchanged under iteration, a property that is consistent with the intuition in models with simultaneous updating on a fully connected communication topology.Several variations of this model have been proposed. We show that some natural variations are not order preserving and therefore cause potential problems with the theoretical analysis and the consistence with the intuition. We consider a generic version of Krause’s model parameterized by an “influence function” that encapsulates most of the variations proposed in the literature. We then derive a necessary and sufficient condition on this function for the opinion order to be preserved.     

SPETA: Social pervasive e-Tourism advisor

Tourism is one of the major sources of income for many countries. Therefore, providing efficient, real-time service for tourists is a crucial competitive asset which needs to be enhanced using major technological advances. The current research has the objective of integrating technological innovation into an information system, in order to build a better user experience for the tourist. The principal strength of the approach is the fusion of context-aware pervasive systems, GIS systems, social networks and semantics. This paper presents the SPETA system, which uses knowledge of the user’s current location, preferences, as well as a history of past locations, in order to provide the type of recommender services that tourists expect from a real tour guide.     

The effects of network neutrality on the diffusion of new Internet application services

The debate over network neutrality started with the appearance of new Internet application services that are latency sensitive and the use of broad bandwidth. These services are still diffusing, and more applications that use broader bandwidth with greater latency sensitivity are expected to be developed. To estimate precisely the effect of network neutrality regulation, it is necessary to forecast the number of end-users that will adopt application services. However, previous studies are limited in that they assume that the potential market and the final number of adopters are constant at the current market penetration level. By computational experiments, this research estimates the effect of network neutrality regulation considering the diffusion process of application services such as IPTV and VoIP. Additionally, it deduces the relation between the effect of network neutrality regulation and the level of diffusion of new Internet application services.     

大数据时代的社交网络分析

概述了大数据时代社交网络的技术背景、网络拓扑结构和MapReduce。阐述了一种新的社交网络的用户聚类分析方法,即如何利用已知的用户,简要推算出好友共同关注和共同粉丝的可能性,以及用户好友群内的连通分支情况。通过一系列的聚类步骤,一种好友共享粉丝/关注的可能性被进一步表征出来,并简要讨论了其应用。     

In search of computer-aided social support in non-communicable diseases care

Non-communicable diseases burden is well-known and care for these diseases goes beyond patients’ engagement, extending to their family, friends, and acquaintances. The ability of social relations in alleviating the harmful effects of health risks is known as social support. Computing can be used to promote social support to enhance the care of non-communicable diseases. However, it is unclear how computing obtains such enhancement. This paper presents a systematic review, in the form of a mapping study, aiming to answer how computing enhances non-communicable diseases care by using social data and by promoting social support. It also looks for available computing models focused on social support promotion in non-communicable diseases care. The study was guided by a two-phase process review, resulting in 38 reviewed papers from journals, conferences, and chapters in the period from 2010 to 2016. In general, the reviewed papers focus on controlled trials, frameworks and systems, knowledge discovery, simulation models or social media usage analysis. Knowledge discovery was the predominant subject, followed by social media usage analysis, and frameworks and systems.     

Microblogging,friendship maintenance,and life satisfaction among university students: The mediatory role of online self-disclosure

Despite a substantial literature suggests that computer-mediated communication impact individuals’ various psychosocial factors, relatively few studies have elucidated the underlying mechanism behind these associations. Building upon self-disclosure theory and previous studies, the principal purpose of this present research is to systematically explore the relationships among microblog utilization, online self-disclosure, friendship maintenance, and perceived life satisfaction. A web-based survey was implemented using a total of 426 university students in Northwestern China. Structural equation modeling reveals that intensity of microblog use is positively associated with these students’ friendship maintenance and life satisfaction. Additionally, online self-disclosure plays the crucial mediatory role in the relationships between microblog use, quality of relationships, and gratification with life. The results imply that as microbloggers disclosure their inner thoughts or emotional states with other users online, they could foster their friendship maintenance and obtain greater life satisfaction. However, contrary to the expectation, students’ friendship maintenance is not discovered to be a significant predictor of the sense of life satisfaction in the online environment. Overall, these obtained outcomes of the empirical work could offer new insights into the deep comprehending of the social psychological process of microblogging among younger generation in the new media context.     

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.     

Increasing inequalities in what we do online: A longitudinal cross sectional analysis of Internet activities among the Dutch population (2010 to 2013) over gender,age, education,and income

We investigate types of Internet activities among a representative sample of the Dutch population from 2010 to 2013. We examined usage patterns of seven types of Internet activities (i.e., information, news, personal development, commercial transaction, social interaction, leisure, and gaming) and related these patterns with gender, age, education, and income. Activities related to news, personal development, commercial transaction, and social interaction increased in popularity. For most capital enhancing activities, men, younger people, higher educated people, and people with higher than average incomes were prominent. These observations, however, are subject to change. The Internet seems to provide increasingly more capital-enhancing opportunities for those with higher education and income, which would accordingly reinforce their already strong positions in society.     

异质社交网络中多通道特征融合的好友推荐模型

合理有效的好友推荐算法对于社交网络的发展和扩张有重大的意义。然而随着社交网络的复杂化和异质化,传统推荐系统中协同过滤推荐方法不能满足需求。针对异质社交网络中存在着大量的内容相关信息这一特点,根据好友推荐的需求,提出了多通道特征融合的好友推荐模型。该模型对用户相关的多维特征进行挖掘与利用,包括显性特征(如用户profile,用户tag,社交关系等)和隐性特征(如用户重要度,挖掘用户标注发现其领域兴趣等),并进一步将这些内容相关的多特征融合到协同排序算法中进行学习训练。实验结果表明,随着多个内容特征的逐步融合,算法的MAP值稳步提高,最终相对未融合的协同排序方法提高了12%,并在一定程度上的解决了冷启动问题,提高了好友推荐的多样性。