Awareness Systems Markopoulos, Panos; Mackay, Wendy; Ruyter, Boris De
2009, 2009-07-15
eBook
People go about their daily tasks with an in-built awareness of their social and physical environments. This awareness helps them to work cooperatively in groups, coordinate actions, and to maintain ...and enhance social communication with others. Networked technology has extended the reach of people's awareness to remote and distributed groups and provided access to a much larger social network than was previously feasible. Awareness systems that are designed to support people to build up, maintain and make use of these extended networks are attracting the interest of industry, and include buddy lists in instant messaging, sustained audio-video links, active contact lists on mobile phones and so forth. This book contains contributions from leading researchers in the field and looks at the design of awareness systems from theoretical foundations through to empirical studies and design concepts and will be of interest to practitioners and researchers in the field of HCI.
The past nine months witnessed COVID-19's fast-spreading at the global level. Limited by medical resources shortage and uneven facilities distribution, online help-seeking becomes an essential ...approach to cope with public health emergencies for many ordinaries. This study explores the driving forces behind the retransmission of online help-seeking posts. We built an analytical framework that emphasized content characteristics, including information completeness, proximity, support seeking type, disease severity, and emotion of help-seeking messages. A quantitative content analysis was conducted with a probability sample consisting of 727 posts. The results illustrate the importance of individual information completeness, high proximity, instrumental support seeking. This study also demonstrates slight inconformity with the severity principle but stresses the power of anger in help-seeking messages dissemination. As one of the first online help-seeking diffusion analyses in the COVID-19 period, our research provides a reference for constructing compelling and effective help-seeking posts during a particular period. It also reveals further possibilities for harnessing social media's power to promote reciprocal and cooperative actions as a response to this deepening global concern.
WeChat is one of the most popular social media mobile apps in China and has become an important means of online communication among Chinese both in China and abroad. Despite much research about ...WeChat's uses and applications, few studies have examined the role of WeChat in international exchanges. This paper explores the functions of WeChat in Chinese exchange programs at a Midwestern state university in the United States. This project is a case study of one faculty member's efforts to recruit international students and contribute to campus diversity with the support of her institution. Employing rhetorical autoethnography, the paper analyzes the author's own communication experience with Chinese exchange students in 2016-2019 before the COVID-19 pandemic. Such communication initially took place completely online via WeChat and was later supplemented with face-to-face interaction after the students' arrival in the United States. WeChat enabled the author to establish ethos, build identification, present multiple identities, develop rapport, and provide support. WeChat's overlapping informative, persuasive, and supportive functions contributed to international recruitment and students' cultural adaptation abroad. Mei Zhang. Using WeChat to Communicate with Chinese Exchange Students. China Media Research 18(1): 84-1005 Keywords: WeChat, social media, mobile communication, Chinese students, Chinese exchanges
•In the academic context, focused on the peer seeking behavior in pages, movements and pathways from experimental situation.•Three types for pathways are identified by cluster analysis, combined with ...questionnaires and interviews.•The search intensions have an impact on the different pathways.•Implications for the interface design of ASNS are proposed based on the characteristics of searching process.
The advent of academic social networking sites (ASNS) has provided a more convenient way for users to seek out experts. This paper uses ResearchGate to explore the features of pathways through four different tasks, combined with questionnaires and interviews. These tasks are aimed at identifying the right experts with relevant expertise or experience for a given topic. We propose a pathway-based approach that takes into consideration both pages and navigations. The pathways show the whole process of how users find experts on ASNS for a variety of reasons. A user visiting ASNS will generate different types of pages, and navigation represents the act of moving from one page to another. A series of navigations between pages that can be linked together chronologically make up the pathways. A total of 94 valid pathways were used for the cluster analysis. The results show that the pages most frequently accessed by users are profile pages, search pages, and publication pages. A comparison of these three types found that the overall utilization of publication pages is low. Users pay more attention to research results pages within profile pages, and continuously adjust the queries on demand. Single seeking pathways, triangular seeking pathways and multiple seeking pathways are identified to understand the process of users’ expert finding. Finally, this paper proposes implications for the interface design of ASNS: improve search pages, focus on users' personalized needs, and apply relational networks in the seeking process. Furthermore, the findings have a positive impact on encouraging interaction, collaboration and innovation in the research environment.
Recent research on the addictive potential of modern technologies such as the internet, smartphones, or social networking sites (SNSs) has suggested that emotional and motivational changes associated ...with the sudden discontinuation of engagement with the technology mirror the aversive consequences seen when drug use is ceased abruptly. This has been observed even in moderate users and interpreted as a manifestation of withdrawal, an important marker of physical dependence in substance use disorders. On the other hand, a growing literature emphasises the positive effects of "digital detox" on mental health and well-being. Using a battery of affective and motivational measures, both explicit and implicit, the present study tracked the effects of a week of significantly reduced SNS use in moderate to heavy SNS users (N = 51). Our pre-registered analyses showed that the intervention elicited affective changes neither consistent with a general withdrawal syndrome (i.e., increased negative affect and cravings) nor with a general beneficial effect on well-being: While our data indicated some abstinence-related decreases of negative affect and boredom, they also showed a reduction of positive affect. These changes occurred regardless of problematic/addictive use behaviours. Importantly, restricting SNS use for one week had no effect on implicit measures of SNS use motivation (i.e., approach biases, time distortion and effort expenditure for SNS access) nor did it influence explicit cravings and SNS cue-reactivity. Together our findings suggest that restricting SNS use has nuanced and potentially offsetting effects on well-being. These could arise because use reduction may concurrently remove experiences that trigger negative emotions (e.g., upward social comparisons or Fear of Missing Out) but also those that elicit positive emotions (e.g., social approval). The hypothesised lack of a net effect on well-being would be consistent with our finding that voluntary reduction of SNS use does not mitigate or exacerbate SNS-related urges.
In contemporary society, many people move away from their personal networks for extended periods to reach professional and/or educational goals. This separation can often lead to feelings of ...loneliness, which can be stressful and sometimes debilitating for the individual. We seek to understand how a person's use of online social networks (OSNs)-technology-enabled tools that assist users with creating and maintaining their relationships-might affect their perceptions of loneliness. Prior research has offered mixed results about how OSNs affect loneliness-reporting both positive and negative effects. We argue in this study that a clearer perspective can be gained by taking a closer look at how individuals approach their relationship management in OSNs. Building on theoretical works on loneliness, we develop a model to explain the effects of relationship characteristics (i.e., relationship orientation, self-disclosure, and networking ability) and OSN features (i.e., active or passive) on perceived loneliness. Our findings show that OSN can be linked to both more and less perceived loneliness, that is, individuals' relationship orientation significantly affects their feelings of loneliness, which are further moderated by their degree of self-disclosure within the OSN. Furthermore, how users engage in the OSN (either actively or passively) influences their perceptions of loneliness. Practical implications regarding perceived loneliness include recommendations for firms to encourage mobile workers to utilize OSNs when separated from others, for education providers to connect with their new students before they arrive, and for users to utilize OSNs as a social bridge to others they feel close with.
Personality is an important psychological construct accounting for individual differences in people. Computational personality recognition from online social networks is gaining increased research ...attention in recent years. However, the majority of existing methodologies mainly focused on human-designed shallow statistical features and didn’t make full use of the rich semantic information in user-generated texts, while those texts are exactly the most direct way for people to translate their internal thoughts and emotions into a form that others can understand. This paper proposes a deep learning-based approach for personality recognition from text posts of online social network users. We first utilize a hierarchical deep neural network composed of our newly designed AttRCNN structure and a variant of the Inception structure to learn the deep semantic features of each user’s text posts. Then we concatenate the deep semantic features with the statistical linguistic features obtained directly from the text posts, and feed them into traditional regression algorithms to predict the real-valued Big Five personality scores. Experimental results show that the deep semantic feature vectors learned from our proposed neural network are more effective than the other four kinds of non-trivial baseline features; the approach that utilizes the concatenation of our deep semantic features and the statistical linguistic features as the input of the gradient boosting regression algorithm achieves the lowest average prediction error among all the approaches tested by us.
Currently, we are surrounded by all sorts of smart devices. Nevertheless, surprisingly, apart from e-health systems, few applications consider humans as active system players, as most ...applications/systems have the sole objective of providing some service to humans without considering their intents, actions, emotions, or social context. In this respect, they can be looked at as open loop, rather than integrating humans in a feedback loop, with potential to react to and change the environment. Systems that do consider human feedback are called Human-in-the-Loop Cyber-Physical-Systems (HiTLCPS), and these are now looked at as essential components of intelligent advisor systems (AS), i.e., systems that can take decisions and provide advice based the user environment and mood. In this paper, we present a HITLCPS AS system that combines online social networks (OSN) data with a variety of other data, such as environmental data and personal mobile devices data, in order to provide user advice. The paper details the system architecture, presents a data analysis from the collected dataset, provides results for some of the built models, and discusses future research directions.
PDF
