User requirements of social media for the elderly: a case study in Taiwan

Numerous researchers have proposed website design norms that are suitable for the elderly. However, in the design of community platforms, elderly users were not considered in social media usage. Young and middle-aged people are the main targets in several social media platforms. To co-ordinate the digital lives of elderly users, the emphasis in this study was to determine the problems and to search for solutions. The real requirements and proper solutions for the elderly were integrated by analysing possible factors. This study is an anthropological user centred approach, to explore the verbal behaviour of senior citizens while they accessed Facebook. Facebook, which is a social media platform with a multilingual language interface, is currently used worldwide and served the purpose of an experimental base for this research. By determining the user environments that are suitable for the elderly, including web page accessibility, interface design and real social life transformation, this article proposes the factors for a social media website, the factors for the elderly to use social media platforms, a social media platform design that can be easily used by the elderly and design factors suitable for the elderly.     

Play in the smart city context: exploring interactional,bodily, social and spatial aspects of situated media interfaces

ABSTRACT

Urban media interfaces can assume many forms, offering rich possibilities for interactions and social encounters. We focus on a particular type of urban interfaces, namely urban media installations, which are situated, fixed (i.e. non-mobile) and outdoor interactive interfaces enhanced by digital technologies. Drawing on research on play in the context of the smart city, we aim to clarify how the digital and the physical worlds of urban media installations can coalesce into enjoyable and socially thriving playscapes. Two case studies of urban media installations are presented: the Appearing Rooms, a seasonal art installation in London, and the Mirror Pool, a permanent, large-scale urban installation in Bradford, UK. Each of these interfaces incorporates a design paradigm that differs from the other in terms of context, duration of implementation, and scale. Following a longitudinal approach based on non-participant observations and time-lapse photography, we analyse emergent interactions and focus in particular on playful encounters at different levels and scales: from the micro scale of the bodily engagement to the macro scale of the spatial and social configurations. Our case studies highlight that the urban spatial layout is a key element in defining the emerging interactions and encounters around the urban situated interfaces.     

Retracted: A study of a B2C supporting interface design system for the elderly

People are now living longer because of advances in medical science, resulting in the percentage of the elderly in the population increasing year by year. These older individuals cannot move about like youngsters do. Internet shopping could become one of the most important shopping channels for them. According to related domestic and foreign survey results, this is confirmed by the increased percentage of elderly Internet shoppers. A lot of consumers, however, are still not satisfied with their Internet shopping experiences. Many have had the experience of giving up before completing the purchasing procedure. The key factors included in such procedures are rather complex, and user interfaces are not necessarily well‐designed. Nowadays, most websites are still designed for the convenience of the seller instead of the consumers. Often consumers find that their interfaces are complex and hard to use and that they require a high mental workload. Based on the behavioral model of older Internet consumers and difficulties they have encountered, and after exploring the information provided by shopping websites and evaluating the status of their current interface design, this study proposes an example of a supporting interface design system (SIDS) for the elderly. The effects of the SIDS are verified experimentally. A total of 12 subjects participated in the experiment. The results showed that the SIDS could successfully reduce the time spent by the elderly subjects on inputting data during the shopping process and the number of repetitions and the time spent on searching for, examining, and comparing products. Furthermore, it was also helpful to reduce the mental workload caused by Internet shopping. © 2012 Wiley Periodicals, Inc.     

Web-based knowledge exchange through social links in the workplace

Knowledge exchange between employees is an essential feature of recent commercial organisations on the competitive market. Based on the data gathered by various information technology (IT) systems, social links can be extracted and exploited in knowledge exchange systems of a new kind. Users of such a system ask their queries and the system recommends known and unknown experts selected out of user's friends. The friends either provide the solution or forward the query to their friends. By means of the established social paths to experts, the system facilitates informal learning and exchange of latent knowledge between organisation members in their workplace. The overall concept, limitations and detailed features of this novel knowledge exchange system are discussed in the article.     

A correlative denoising autoencoder to model social influence for top-N recommender system

In recent years,there are numerous works been proposed to leverage the techniques of deep learning to improve social-aware recommendation performance.In most cases,it requires a larger number of data to train a robust deep learning model,which contains a lot of parameters to fit training data.However,both data of user ratings and social networks are facing critical sparse problem,which makes it not easy to train a robust deep neural network model.Towards this problem,we propose a novel correlative denoising autoencoder(CoDAE)method by taking correlations between users with multiple roles into account to learn robust representations from sparse inputs of ratings and social networks for recommendation.We develop the CoDAE model by utilizing three separated autoencoders to learn user features with roles of rater,truster and trustee,respectively.Especially,on account of that each input unit of user vectors with roles of truster and trustee is corresponding to a particular user,we propose to utilize shared parameters to learn common information of the units that corresponding to same users.Moreover,we propose a related regularization term to learn correlations between user features that learnt by the three subnetworks of CoDAE model.We further conduct a series of experiments to evaluate the proposed method on two public datasets for Top-N recommendation task.The experimental results demonstrate that the proposed model outperforms state-of-the-art algorithms on rank-sensitive metrics of MAP and NDCG.     

基于降噪自编码器的社会化推荐算法

现有的社会化推荐算法未考虑信任用户对目标用户深层的偏好影响。针对这一问题,提出了一种基于深度学习的混合推荐算法,利用降噪自编码器学习用户及其信任用户的评分偏好,使用加权隐藏层来平衡这些表示的重要性,有效建模用户间的潜在偏好交互。在此基础上,通过用户聚类和个性化权重区分不同类的用户受其信任用户的影响程度。在开放数据集上的实验结果表明,该算法优于现有的社会化推荐算法,与主要的推荐算法SoRec、RSTE、SocialMF、TrustMF相比,其平均绝对误差(MAE)和均方根误差(RMSE)显著降低,获得了较好的推荐效果。     

A user-centric smart product-service system development approach: A case study on medication management for the elderly

With the advancement in Internet implementations, computational intelligence and network technologies, smart product-service system (SPSS) has become an important research area. A lot of research effort has been devoted to construct the conceptual framework, identify the important elements and evaluate the effectiveness of SPSS. However, there is still no SPSS development approach from user-centric perspective. Therefore, this article aims to provide a novel understanding of user-centric SPSS (UC-SPSS), outline the conceptual framework of UC-SPSS and contribute a UC-SPSS development approach. Specifically, a multimodal user analysis module with S-E-T (society-economy-technology) analysis, user behavioral analysis and user segmentation is deployed. According to the user needs identified, a provider identification and integration network is established in the dimensions of material, data and value flows. Jointly considering the user needs and provider capability, the BCE (benefit-cost-expectation) model and Product Function Architecture are applied to assist in the realization of the smart, connected service. To illustrate, a UC-SPSS on medication management for the elderly was developed, and it has been evaluated from user experience and sustainable value aspects. The results showed that the developed medication service is interesting and helpful for the elderly to take their medication. However, the service is not simple enough, especially in data visualization. In terms of sustainable value, the developed service can achieve better performance in economic, material and energy costs, and can support the further regulation of medical industry. Based on the case illustration, the proposed approach appears effective to help with SPSS development.     

Adoption of travel information in user-generated content on social media: the moderating effect of social presence

Travel patterns have gradually changed from group travel to individual travel. An increasing number of people acquire travel information through various types of media. One of the alternative information sources is social media, which enables users to exchange information among members. However, one of the characteristics of social media is information sharing, not information search, which involves both giving (i.e. posting) and taking (i.e. selective reading, forwarding, replying, linking, and liking) information. Compared to the ‘giving’ side of information-sharing research, less effort has been spent on the ‘taking’ side of information research. Therefore, we investigate travel information adoption in social media as well as how individuals communicate with each other. We use the elaboration likelihood model, which measures the impact of central (e.g. argument quality) and peripheral (e.g. credibility) cues on traveller information-sharing behaviour corresponding with social presence on social media. The results of an empirical analysis of 527 respondents, who were experienced in travel information adoption via social media, were examined. Our findings revealed that argument quality had a positive effect on perceived usefulness and source credibility positively affected perceived usefulness and social relationships. Perceived usefulness had a significant positive effect on social relationships. Both perceived usefulness and social relationships affected travel information adoption. Lastly, the levels of argument quality and source credibility perceived by social media members were found to differ according to the level of social presence.     

Feature selection for event discovery in social media: A comparative study

Microblog as one kind of typical social media has many research implications in social event discovery and social-media-based e-learning and collaborative learning. At present, researchers usually employ feature-based classification approaches to detect social events in microblogs. However, it is very common to get different results when different features are used in event discovery. Therefore, it has been a critical issue how to select appropriate features for event discovery in microblogs. In this paper, we analyze five different feature selection methods and present an improved method for selecting features for microblog-based event discovery. We compare all the methods on a real microblog dataset in terms of various metrics including precision, recall, and F-measure. And finally we discuss the best feature selection method for the event discovery in microblogs. To the best of our knowledge, there are no such comparative studies on feature selection for event discovery in social media, and this paper is expected to offer some useful references for the future research and applications on the event discovery in microblogs.     

Incorporating metapath interaction on heterogeneous information network for social recommendation

Heterogeneous information network (HIN) has recently been widely adopted to describe complex graph structure in recommendation systems, proving its effectiveness in modeling complex graph data. Although existing HIN-based recommendation studies have achieved great success by performing message propagation between connected nodes on the defined metapaths, they have the following major limitations. Existing works mainly convert heterogeneous graphs into homogeneous graphs via defining metapaths, which are not expressive enough to capture more complicated dependency relationships involved on the metapath. Besides, the heterogeneous information is more likely to be provided by item attributes while social relations between users are not adequately considered. To tackle these limitations, we propose a novel social recommendation model MPISR, which models MetaPath Interaction for Social Recommendation on heterogeneous information network. Specifically, our model first learns the initial node representation through a pretraining module, and then identifies potential social friends and item relations based on their similarity to construct a unified HIN. We then develop the two-way encoder module with similarity encoder and instance encoder to capture the similarity collaborative signals and relational dependency on different metapaths. Extensive experiments on five real datasets demonstrate the effectiveness of our method.     

An e-health platform for the elderly population: The butler system

The Butler system is an e-health platform designed to improve the elderly population’s quality of life. The Butler system has three applications diagnostic, therapeutic and playful. The objective of this work is to present the influence of the use of the platform on elderly users’ mood states and the degree of acceptance. These measures were assessed through visual analogical scales before and after the platform use, with the outcome measures MANOVAS analyses were performed. Seventeen users (from 58 to 79 years old) completed four sessions with the system; they could choose which technological resources they used in each session. The results showed that after using the system, the participants’ insensitive emotions increased and their negative ones decreased. In addition, they obtained high levels of satisfaction, low levels of subjective difficulty and would recommend Butler to other users. Therefore, the results indicate that Butler might be an effective system for improving emotional states in elderly population.     

DeepMUI: A novel method to identify malicious users on online social network platforms

The use of online social network (OSN) platforms has become an essential component of contemporary society, facilitating global connectivity, and information sharing among individuals. The proliferation of malicious users has emerged as a noteworthy obstacle, exerting a detrimental effect on the authenticity of the data disseminated through these channels. A malicious profile is created with the intention of disseminating false information, manipulating perspectives, and executing harmful actions, including phishing schemes, identity theft, and the propagation of malware. Consequently, the identification of malicious users has emerged as an essential undertaking for both OSN platforms and researchers. The objective of this study is to investigate the issue of identifying malicious users on OSN platforms. The DeepMUI model has been introduced as a new approach to identifying malicious users on OSN platforms, utilizing user profile metadata-derived characteristics. The DeepMUI architecture is composed of long short-term memory and convolutional neural network models. Additionally, it integrates alterations to the pooling layer to improve its overall efficacy. The experiments have demonstrated that DeepMUI exhibits promising results in the task of identifying malicious users, with greater accuracy and minimal loss compared to existing methods.     

GeoSRS: A hybrid social recommender system for geolocated data

We present GeoSRS, a hybrid recommender system for a popular location-based social network (LBSN), in which users are able to write short reviews on the places of interest they visit. Using state-of-the-art text mining techniques, our system recommends locations to users using as source the whole set of text reviews in addition to their geographical location. To evaluate our system, we have collected our own data sets by crawling the social network Foursquare. To do this efficiently, we propose the use of a parallel version of the Quadtree technique, which may be applicable to crawling/exploring other spatially distributed sources. Finally, we study the performance of GeoSRS on our collected data set and conclude that by combining sentiment analysis and text modeling, GeoSRS generates more accurate recommendations. The performance of the system improves as more reviews are available, which further motivates the use of large-scale crawling techniques such as the Quadtree.     

The effects of helping,self-expression,and enjoyment on social capital in social media: the moderating effect of avoidance attachment in the tourism context

ABSTRACT

A majority of senior Internet users maintains persistent social connections with others through social media (SM), such as Facebook and Twitter. This research explores the impacts of helping, self-expression, and enjoyment on bonding social capital and bridging social capital which in turn influence SM involvement; it also explores the moderating effect of avoidance attachment among senior SM users. The results show that helping, self-expression, and enjoyment have significant impacts on bonding social capital and bridging social capital. Also, bonding social capital and bridging social capital have significant effects on SM involvement. Furthermore, relationships between helping and bonding social capital, between self-expression and bonding social capital, and between self-expression and bridging social capital are stronger for seniors with high avoidance attachment. Conversely, the relationships between enjoyment and bonding social capital as well as between enjoyment and bridging social capital are stronger for seniors with low avoidance attachment. Accordingly, the results of this study provide theoretical contributions to the literature of behaviour and information technology. In addition, some implications of the research and various strategies for practitioners and marketers that can be used to better increase users’ involvement in SM for tourism-related activities are discussed.     

Affordances of social media in collective action: the case of Free Lunch for Children in China

This paper studies the socialised affordances of social media in the processes of collective action, exploring the role of technology in the under‐researched area of civil society. We examine the case of Free Lunch for Children (FL4C), a charitable programme in China based on the microblogging platform, Weibo. Adopting the perspective of affordances‐for‐practice, we draw upon the collective action model to better understand the sociomaterial practices and social processes involving social media, and seek to address the ‘when’ and ‘how’ questions of affordances. The study generates theoretical and practical implications for understanding the role of social media in social transformation.     

基于Hadoop社交网络分析平台的设计与实现

随着社交网络的快速发展,海量社交网络的数据挖掘成为一个重要课题;针对海量数据的社交网络分析方法进行研究,以Hadoop的分布式文件系统和Map/Reduce并行方法设计基于Hadoop的分布式数据挖掘框架,在此基础上,通过Map/Reduce的并行方法,将传统数据挖掘算法并行化,以谱聚类的并行为例,阐述转化的过程并对在大数据条件下所面临的内存不足的问题给出相应的算法优化;最后对3个不同量级的数据集进行实验,验证基于Hadoop的社交网络分析平台的框架的合理性和算法并行化的有效性。     

A study of detecting and combating cybersickness with fuzzy control for the elderly within 3D virtual stores

Elderly individuals can access online 3D virtual stores from their homes to make purchases. However, most virtual environments (VEs) often elicit physical responses to certain types of movements in the VEs. Some users exhibit symptoms that parallel those of classical motion sickness, called cybersickness, both during and after the VE experience. This study investigated the factors that contribute to cybersickness among the elderly when immersed in a 3D virtual store. The results of the first experiment show that the simulator sickness questionnaire (SSQ) scores increased significantly by the reasons of navigational rotating speed and duration of exposure. Based on these results, a warning system with fuzzy control for combating cybersickness was developed. The results of the second and third experiments show that the proposed system can efficiently determine the level of cybersickness based on the fuzzy sets analysis of operating signals from scene rotating speed and exposure duration, and subsequently combat cybersickness.     

Effects of bath chairs on the behavior,muscle workload,and experience in independent bathing of the elderly: A Chinese case study

It is important to use a bath chair for reducing the injury risk in elderly independent bathing and for improving the elderly bathing experience. This study aimed to investigate the elderly independent bathing process and the effect of bath chairs on the elderly. We investigated the bath scenarios of elderly Chinese people through a questionnaire and behavior observation. Then, based on the survey results, we designed an experiment to evaluate the muscle workload and subjective experience in twelve bathing tasks. Twelve elderly participants were recruited to complete the bathing task in two scenarios: with a chair and without a chair. We found Showering was the dominant bathing style for elderly Chinese people. The rectus-femoris and the lumbar-erector workload change differed significantly between the two scenarios when cleaning the lower body, and the subjective experience with a chair was significantly better than that without a chair. The amplitude of the basic motions of the static-work joints significantly affects the workload of corresponding muscles and the bathing experience. The bath chair effectively reduced the workload of the rectus femoris and the lumbar-erector, reducing the risk of falls and improving the subjective experience of the elderly when cleaning the lower body. However, the bath chair had limited improvement in the workload of the rectus femoris and the lumbar-erector during some bathing tasks, which was the main direction of the bath-chair optimization. This study helps to evaluate the elderly bathing experience, and optimizes bath-chair design.     

The reciprocal effects of social network site use and the disposition for self-disclosure: A longitudinal study

Since the advent of social network sites (SNSs), scholars have critically discussed the psychological and societal implication of online self-disclosure. Does Facebook change our willingness to disclose personal information? The present study proposes that the use of SNSs and the psychological disposition for self-disclosure interact reciprocally: Individuals with a stronger disposition show a higher tendency to use SNSs (selection effect). At the same time, frequent SNS use increases the wish to self-disclose online, because self-disclosing behaviors are reinforced through social capital within the SNS environment (socialization effect). In a longitudinal panel study, 488 users of SNSs were surveyed twice in a 6 months interval. Data were analyzed using structure equation modeling. The proposed reciprocal effects of SNS activities and self-disclosure were supported by the data: The disposition for online self-disclosure had a positive longitudinal effect on SNS use which in turn positively influenced the disposition for online self-disclosure. Both effects were moderated by the amount of social capital users received as a consequence of their SNS use.     

A neuro-fuzzy warning system for combating cybersickness in the elderly caused by the virtual environment on a TFT-LCD

Only a few studies in the literature have focused on the effects of age on virtual environment (VE) sickness susceptibility and even less research was carried out focusing on the elderly. In general, the elderly usually browse VEs on a thin film transistor liquid crystal display (TFT-LCD) at home or somewhere, not a head-mounted display (HMD). While the TFT-LCD is used to present VEs, this set-up does not physically enclose the user. Therefore, this study investigated the factors that contribute to cybersickness among the elderly when immersed into a VE on TFT-LCD, including exposure durations, navigation rotating speeds and angle of inclination. Participants were elderly, with an average age of 69.5 years. The results of the first experiment showed that the rate of simulator sickness questionnaire (SSQ) scores increases significantly with navigational rotating speed and duration of exposure. However, the experimental data also showed that the rate of SSQ scores does not increase with the increase in angle of inclination. In applying these findings, the neuro-fuzzy technology was used to develop a neuro-fuzzy cybersickness-warning system integrating fuzzy logic reasoning and neural network learning. The contributing factors were navigational rotating speed and duration of exposure. The results of the second experiment showed that the proposed system can efficiently determine the level of cybersickness based on the associated subjective sickness estimates and combat cybersickness due to long exposure to a VE.