A model of the relationship between psychological characteristics,mobile phone addiction and use of mobile phones by Taiwanese university female students

While many researches have analyzed the psychological antecedents of mobile phone addiction and mobile phone usage behavior, their relationship with psychological characteristics remains mixed. We investigated the relationship between psychological characteristics, mobile phone addiction and use of mobile phones for 269 Taiwanese female university students who were administered Rosenberg’s self-esteem scale, Lai’s personality inventory, and a mobile phone usage questionnaire and mobile phone addiction scale. The result showing that: (1) social extraversion and anxiety have positive effects on mobile phone addiction, and self-esteem has negative effects on mobile phone addiction. (2) Mobile phone addiction has a positive predictive effect on mobile phone usage behavior. The results of this study identify personal psychological characteristics of Taiwanese female university students which can significantly predict mobile phone addiction; female university students with mobile phone addiction will make more phone calls and send more text messages. These results are discussed and suggestions for future research for school and university students are provided.     

基于Smartphone的嵌入式应用程序开发初探

智能手机发展迅速，基于智能手机的应用程序开发也逐渐多起来，本文主要介绍Microsoft的Smartphone智能手机平台．以及基于此平台使用Visual Studio．NET进行应用程序的开发的方法。     

Ambient awareness: From random noise to digital closeness in online social networks

Ambient awareness refers to the awareness social media users develop of their online network in result of being constantly exposed to social information, such as microblogging updates. Although each individual bit of information can seem like random noise, their incessant reception can amass to a coherent representation of social others. Despite its growing popularity and important implications for social media research, ambient awareness on public social media has not been studied empirically. We provide evidence for the occurrence of ambient awareness and examine key questions related to its content and functions. A diverse sample of participants reported experiencing awareness, both as a general feeling towards their network as a whole, and as knowledge of individual members of the network, whom they had not met in real life. Our results indicate that ambient awareness can develop peripherally, from fragmented information and in the relative absence of extensive one-to-one communication. We report the effects of demographics, media use, and network variables and discuss the implications of ambient awareness for relational and informational processes online.     

The action of looking at a mobile phone display as nonverbal behavior/communication: A theoretical perspective

This study investigates the now-common action of looking at a mobile phone display, thereby offering insight into the present communication situation in an era in which the use of high-performance mobile phones has become ubiquitous. In this study, the action of looking at a mobile phone display is considered nonverbal behavior/communication. This study applies a basic, general model to elucidate the present situation of face-to-face communication in light of the increasing prevalence of social interaction via mobile phone use. The results derived from the model include mobile phone users’ increasing social power and an accumulation of potential discontent in relation to different interpretations. This study concludes that in an era of high-performance mobile phones, the social context in face-to-face communication can be influenced by the act of looking at a mobile phone display.     

A semi-supervised social relationships inferred model based on mobile phone data

Exploring the relationships of humans is an important study in the mobile communication network. But the relationship prediction accuracy is not good enough when the number of known relationship labels (e.g., “friend” and “colleague”) is small, especially when the number of different relation classes are imbalanced in the mobile communication network. To deal with issues, we present a semi-supervised social relationships inferred model. This model can infer the relationships based on a large amount of unlabeled data or a small amount of labeled data. The model is a co-training style semi-supervised model which is combined with the support vector machine and naive Bayes. The final relationship labels are decided by the two classifiers. The proposed model is evaluated by a real mobile communication network dataset and the experiment results show that the model is effective in relationship mining, especially when the relationship network is in a stable state.     

The effect of mediation on impression formation: a comparison of face-to-face and video-mediated conditions

It is suggested that communication mediated by video may have an important impact on the way in which individuals are perceived and this might be a result of an attenuation or distortion of visual signals. The current study aimed to test this further by employing a simple mind-reading task, which gave participants an opportunity to interact with one another. Participants completed the task in pairs either face-to-face or via video-mediated technologies. After completing the task, participants filled in a questionnaire which was designed to assess perceptions of how much they liked and how intelligent they believed their partner in the task to be. Results indicate that participants were regarded as significantly less likeable and intelligent in the video-mediated condition. This is probably a consequence of the attenuation of visual signals, in particular eye gaze, which has been shown to be important in impression formation. Findings from this study have practical implications for using this type of technology to assess performance, for example in interviews, especially if comparisons are made with face-to-face interviewees.     

Implications of smartphone user privacy leakage from the advertiser’s perspective

Many smartphone apps routinely gather various private user data and send them to advertisers. Despite recent study on protection mechanisms and analysis on apps’ behavior, the understanding of the consequences of such privacy losses remains limited. In this paper, we investigate how much an advertiser can infer about users’ social and community relationships. After one month’s user study involving about 190 most popular Android apps, we find that an advertiser can infer 90% of the social relationships. We further propose a privacy leakage inference framework and use real mobility traces and Foursquare data to quantify the consequences of privacy leakage. We find that achieving 90% inference accuracy of the social and community relationships requires merely 3 weeks’ user data. Finally, we present a real-time privacy leakage visualization tool that captures and displays the spatial–temporal characteristics of the leakages. The discoveries underscore the importance of early adoption of privacy protection mechanisms.     

Already up? using mobile phones to track & share sleep behavior

Users share a lot of personal information with friends, family members, and colleagues via social networks. Surprisingly, some users choose to share their sleeping patterns, perhaps both for awareness as well as a sense of connection to others. Indeed, sharing basic sleep data, whether a person has gone to bed or waking up, informs others about not just one's sleeping routines but also indicates physical state, and reflects a sense of wellness. We present Somnometer, a social alarm clock for mobile phones that helps users to capture and share their sleep patterns. While the sleep rating is obtained from explicit user input, the sleep duration is estimated based on monitoring a user's interactions with the app. Observing that many individuals currently utilize their mobile phone as an alarm clock revealed behavioral patterns that we were able to leverage when designing the app. We assess whether it is possible to reliably monitor one's sleep duration using such apps. We further investigate whether providing users with the ability to track their sleep behavior over a long time period can empower them to engage in healthier sleep habits. We hypothesize that sharing sleep information with social networks impacts awareness and connectedness among friends. The result from a controlled study reveals that it is feasible to monitor a user's sleep duration based just on her interactions with an alarm clock app on the mobile phone. The results from both an in-the-wild study and a controlled experiment suggest that providing a way for users to track their sleep behaviors increased user awareness of sleep patterns and induced healthier habits. However, we also found that, given the current broadcast nature of existing social networks, users were concerned with sharing their sleep patterns indiscriminately.     

Inferring social nature of conversations from words: Experiments on a corpus of everyday telephone conversations

Language is being increasingly harnessed to not only create natural human–machine interfaces but also to infer social behaviors and interactions. In the same vein, we investigate a novel spoken language task, of inferring social relationships in two-party conversations: whether the two parties are related as family, strangers or are involved in business transactions. For our study, we created a corpus of all incoming and outgoing calls from a few homes over the span of a year. On this unique naturalistic corpus of everyday telephone conversations, which is unlike Switchboard or any other public domain corpora, we demonstrate that standard natural language processing techniques can achieve accuracies of about 88%, 82%, 74% and 80% in differentiating business from personal calls, family from non-family calls, familiar from unfamiliar calls and family from other personal calls respectively. Through a series of experiments with our classifiers, we characterize the properties of telephone conversations and find: (a) that 30 words of openings (beginnings) are sufficient to predict business from personal calls, which could potentially be exploited in designing context sensitive interfaces in smart phones; (b) our corpus-based analysis does not support Schegloff and Sack's manual analysis of exemplars in which they conclude that pre-closings differ significantly between business and personal calls – closing fared no better than a random segment; and (c) the distribution of different types of calls are stable over durations as short as 1–2 months. In summary, our results show that social relationships can be inferred automatically in two-party conversations with sufficient accuracy to support practical applications.     

移动支付中公钥加密算法的研究与实现

移动支付在目前社会中应用越来越广泛,结合公钥加密算法,给出了手机号做移动支付的身份绑定介质的实例。     

Kei-Tying teens: Using mobile phone e-mail to bond, bridge, and break with social ties—a study of Japanese adolescents

This paper examines the extent to which Japanese adolescents use mobile phone e-mail to bond, bridge, and break with their social ties. Although existing literature shows that adolescents use mobile phone e-mail to bond with intimate strong ties, the fluid nature of social networks during adolescence suggests that mobile phone e-mail may also be used to bridge to new ties and to break with old ties. Drawing on a stratified random sample survey of 501 high school students living in Tokyo, we find that mobile phone e-mail is used both to bond and bridge, but not to break with ties. We also find that the intensity with which Japanese adolescents use mobile phone e-mail is more fundamentally a result of bridging than bonding. These findings apply both to typical users and heavy users.     

Mobile phones and driving: a review of contemporary research

This study reviews research on the effects of using a mobile phone when driving. First, it is should be pointed out that the availability of a mobile phone in a car is of great value, for example, in emergencies and accidents. However, the results from the research covered in this review show that using a mobile phone in a car while driving impairs driving performance significantly. To exemplify, a drivers attention to traffic and traffic information is impaired and the control of the car becomes less precise and smooth when talking over a phone. The conversation in itself impairs attention and manoeuvring performance as well as the motor activities needed for phoning. Based on the research available, the present review gives numerical estimates of the disturbing effects of different aspects of mobile phoning on driving performance. Contrary to what people assume, hand-held phones have not been shown to impair driving quality more than hands free phones. Instead, in contrast to public opinion, the content of a conversation is most important in determining the degree of distraction; complex conversations disturb driving much more than simple conversations. Analyses of accidents have shown that the impairment of driving while phoning leads to an increased risk of having an accident for both hand-held and hands free mobile telephones.