Fake news and COVID-19: modelling the predictors of fake news sharing among social media users

Fake news dissemination on COVID-19 has increased in recent months, and the factors that lead to the sharing of this misinformation is less well studied. Therefore, this paper describes the result of a Nigerian sample (n = 385) regarding the proliferation of fake news on COVID-19. The fake news phenomenon was studied using the Uses and Gratification framework, which was extended by an “altruism” motivation. The data were analysed with Partial Least Squares (PLS) to determine the effects of six variables on the outcome of fake news sharing. Our results showed that altruism was the most significant factor that predicted fake news sharing of COVID-19. We also found that social media users’ motivations for information sharing, socialisation, information seeking and pass time predicted the sharing of false information about COVID-19. In contrast, no significant association was found for entertainment motivation. We concluded with some theoretical and practical implications.     

The media use of American youngsters in the age of narcissism : Surviving in a 24/7 media shock and awe – distracted by everything

Digital life in the age of nonstop connection is not easy, especially not for the so-called Millennials, youngsters born after 1980. Research findings, such as the recently released comprehensive reports by the Kaiser Family Foundation and Pew Foundation, highlight that media are among the most powerful forces in young people’s lives today. Eight- to twenty-somethings in the US spend more than 50 h in front of a screen each week. That is more than a regular working week. The TV shows they watch, video games they play, songs they listen to, books they read, text messages they send and websites they visit are an enormous part of their lives, offering a constant stream of messages about families, peers, relationships, gender roles, sex, violence, food, values, clothes, and so on.     

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.     

Transferring human grasping synergies to a robot

In this paper, a system for transferring human grasping skills to a robot is presented. In order to reduce the dimensionality of the grasp postures, we extracted three synergies from data on human grasping experiments and trained a neural network with the features of the objects and the coefficients of the synergies. Then, the trained neural network was employed to control robot grasping via an individually optimized mapping between the human hand and the robot hand. As force control was unavailable on our robot hand, we designed a simple strategy for the robot to grasp and hold the objects by exploiting tactile feedback at the fingers. Experimental results demonstrated that the system can generalize the transferred skills to grasp new objects.     

Why do people purchase virtual goods? A uses and gratification (U&G) theory perspective

Few literature studies have investigated the relationships between different uses and gratifications (U&Gs) of mobile instant messaging (MIM) apps, continuation, and purchase intentions. To address this gap, the researchers aimed to examine the influence of the content, social, process, and technology U&Gs of MIM on continuation intentions toward MIMs, and purchase intentions toward virtual goods available on MIMs. A comprehensive research model was developed based on the U&G theory, which was tested using cross-sectional data from 309 Japanese MIM users. The study considered six different U&Gs of MIM as independent variables and purchase intentions towards stickers and continuation intentions towards MIM as dependent variables. The study results suggest that exposure U&G has a significant positive association with MIM sticker purchase intentions. The entertainment and affection U&G are positively associated with continuation intentions towards MIM use. The study contributes to the literature by investigating U&Gs that motivate MIM users to have both positive purchase intentions toward virtual goods, such as stickers, and continuation intentions toward MIMs. The study has significant theoretical and practical implications for both researchers and practitioners who are interested in virtual goods, the virtual economy, MIM apps, social media, new media, and the service economy.     

大学生科研创新实践项目的管理探索

近年来,大学生科研创新能力和实践动手能力的培养得到很大的重视,高校都在开展多种多样的大学生创新实践项目。本文从管理和辅导角度探讨如何更好地开展大学生科研与创新实践项目,内容包括创新项目选题,创新能力培养的基本原则,以及创新实践过程的心理辅导,最后介绍了我校在管理和辅导大学生科研创新实践项目过程中的一些心得与体会。     

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.     

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.