Information mining and similarity computation for semi- / un-structured sentences from the social data

In recent years, with the development of the social Internet of Things (IoT), all kinds of data accumulated on the network. These data, which contain a lot of social information and opinions. However, these data are rarely fully analyzed, which is a major obstacle to the intelligent development of the social IoT. In this paper, we propose a sentence similarity analysis model to analyze the similarity in people’s opinions on hot topics in social media and news pages. Most of these data are unstructured or semi-structured sentences, so the accuracy of sentence similarity analysis largely determines the model’s performance. For the purpose of improving accuracy, we propose a novel method of sentence similarity computation to extract the syntactic and semantic information of the semi-structured and unstructured sentences. We mainly consider the subjects, predicates and objects of sentence pairs and use Stanford Parser to classify the dependency relation triples to calculate the syntactic and semantic similarity between two sentences. Finally, we verify the performance of the model with the Microsoft Research Paraphrase Corpus (MRPC), which consists of 4076 pairs of training sentences and 1725 pairs of test sentences, and most of the data came from the news of social data. Extensive simulations demonstrate that our method outperforms other state-of-the-art methods regarding the correlation coefficient and the mean deviation.     

Prediction of risk factors of cyberbullying-related words in Korea: Application of data mining using social big data

The study examined a decision tree analysis using social big data to conduct the prediction model on types of risk factors related to cyberbullying in Korea. The study conducted an analysis of 103,212 buzzes that had noted causes of cyberbullying and data were collected from 227 online channels, such as news websites, blogs, online groups, social network services, and online bulletin boards. Using opinion-mining method and decision tree analysis, the types of cyberbullying were sorted using SPSS 25.0. The results indicated that the total rate of types of cyberbullying in Korea was 44%, which consisted of 32.3% victims, 6.4% perpetrators, and 5.3% bystanders. According to the results, the impulse factor was also the greatest influence on the prediction of the risk factors and the propensity for dominance factor was the second greatest factor predicting the types of risk factors. In particular, the impulse factor had the most significant effect on bystanders, and the propensity for dominance factor was also significant in influencing online perpetrators. It is necessary to develop a program to diminish the impulses that were initiated by bystanders as well as victims and perpetrators because many of those bystanders have tended to aggravate impulsive cyberbullying behaviors.     

How the intensity of the immersive experience impels the extent of Social Streaming App dependency? An empirical assessment with mediation and moderation effects

With the rapid growth and popularity of Social Streaming Apps (SSAs) worldwide, it is valuable for scholars to understand the links between immersive experience provided by SSA, users’ attitudes towards SSA, and the resultant SSA dependency. Although unexplored in the SSA context, previous research has indicated the significance of immersive experience and its influence on user’s specific behavior through user attitude. The present study employs Structural Equation Modelling, by using 459 samples from a survey, to explore how the intensity of immersive experience can influence the degree of user dependency on SSA. Results indicate that immersive experience is positively associated with users’ positive attitudes towards SSA, which would lead to SSA dependency. In addition, this study also found out that users’ favorable attitude partially mediates the relationship between immersive experience and solitary play dependency. Whereas, attitude fully mediated the relationship between five out of six dimensions of SSA dependency. Furthermore, to better comprehend the intervening relationships between immersive experiences, user attitude, SSA dependency, the study also conducted a moderation analysis taking frequency of use as a moderating variable. The results illustrate that a high frequency of use is a strong psychological indicator for SSA dependency. This supports the importance of considering actual behavior along with their psychological states when examining users’ immersive experience and their SSA dependency.     

An efficient hybrid protection scheme with shared/dedicated backup paths on elastic optical networks

Fast recovery and minimum utilization of resources are the two main criteria for determining the protection scheme quality. We address the problem of providing a hybrid protection approach on elastic optical networks under contiguity and continuity of available spectrum constraints. Two main hypotheses are used in this paper for backup paths computation. In the first case, it is assumed that backup paths resources are dedicated. In the second case, the assumption is that backup paths resources are available shared resources. The objective of the study is to minimize spectrum utilization to reduce blocking probability on a network. For this purpose, an efficient survivable Hybrid Protection Lightpath (HybPL) algorithm is proposed for providing shared or dedicated backup path protection based on the efficient energy calculation and resource availability. Traditional First-Fit and Best-Fit schemes are employed to search and assign the available spectrum resources. The simulation results show that HybPL presents better performance in terms of blocking probability, compared with the Minimum Resources Utilization Dedicated Protection (MRU-DP) algorithm which offers better performance than the Dedicated Protection (DP) algorithm.     

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.     

Comprehensive classification of collaboration approaches in E-learning

There are a number of approaches to learning such as traditional approaches (teacher-centered) and collaborative approaches (learner-centered). Nowadays, the concepts of collaboration and social interactions are the major trends in education. Therefore, many researchers embrace these concepts to offer the educational field enhanced learning environments which are supported by communication and collaboration techniques. The adaptation causes the existence of varied approaches which are addressing the collaborative learning techniques. As a result, there is a need for a mechanism to study those approaches and highlight their eminence. The aim of this paper is to give a comprehensive overview about the state-of-art in collaborative learning, especially by integrating social media tools. To do so, the study adopts a classification framework based on four different views (subject, purpose, method, and tool). The framework has been used to compare ten collaborative e-learning approaches. The finding indicates the potential of all approaches in developing an online learning environment for remote collaborative learning despite the lack of fulfilling all the requirements highlighted in the four views.     

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.     

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.     

传感器网络环境下人机协同系统研究

针对人与服务机器人协同远程健康监控系统,分析了系统总体结构设计、传感器网络、微型无线生物信号处理模块等关键设备的设计与实现等方面典型问题.实验室应用证明,所设计硬件、软件及算法的有效性.     

基于社会网络增量的动态社区组织探测

在现实世界中,社会网络结构并不是一成不变的,而是随着时间的推移不断变化,同样社区作为社会网络的一个本质特性也是如此。为了揭示真实的网络社区结构,该文提出一种基于属性加权网络的增量式动态社区发现算法,将网络的属性信息融合在拓扑图中,定义了节点与社区之间的拓扑势吸引,利用网络相对于前一时刻的改变量不断更新完善当前时刻社区结构。通过在真实网络数据上进行实验仿真,证明此算法能够更有效、更实时地发现有意义的社区结构,并具有较小的时间复杂性。