Linking information and people in a social system for academic conferences

This paper investigates the feasibility of maintaining a social information system to support attendees at an academic conference. The main challenge of this work was to create an infrastructure where users’ social activities, such as bookmarking, tagging, and social linking could be used to enhance user navigation and maximize the users’ ability to locate two important types of information in conference settings: presentations to attend and attendees to meet. We developed Conference Navigator 3, a social conference support system that integrates a conference schedule planner with a social linking service. We examined its potential and functions in the context of a medium-scale academic conference. In this paper, we present the design of the system’s socially enabled features and report the results of a conference-based study. Our study demonstrates the feasibility of social information systems for supporting academic conferences. Despite the low number of potential users and the short timeframe in which conferences took place, the usage of the system was high enough to provide sufficient data for social mechanisms. The study shows that most critical social features were highly appreciated and used, and provides direction for further research.     

Social welfare maximization in participatory smartphone sensing

Participatory smartphone sensing has lately become more and more popular as a new paradigm for performing large-scale sensing, in which each smartphone contributes its sensed data for a collaborative sensing application. Most existing studies consider that smartphone users are strictly strategic and completely rational, which try to maximize their own payoffs. A number of incentive mechanisms are designed to encourage smartphone users to participate, which can achieve only suboptimal system performance. However, few existing studies can maximize a system-wide objective which takes both the platform and smartphone users into account. This paper focuses on the crucial problem of maximizing the system-wide performance or social welfare for a participatory smartphone sensing system. There are two great challenges. First, the social welfare maximization cannot be realized on the platform side because the cost of each user is private and unknown to the platform in reality. Second, the participatory sensing system is a large-scale real-time system due to the huge number of smartphone users who are geo-distributed in the whole world. A price-based decomposition framework is proposed in our previous work (Liu and Zhu, 2013), in which the platform provides a unit price for the sensing time spent by each user and the users return the sensing time via maximizing the monetary reward. This pricing framework is an effective incentive mechanism as users are motivated to participate for monetary rewards from the platform. In this paper, we propose two distributed solutions, which protect users’ privacy and achieve optimal social welfare. The first solution is designed based on the Lagrangian dual decomposition. A poplar iterative gradient algorithm is used to converge to the optimal value. Moreover, this distributed method is interpreted by our pricing framework. In the second solution, we first equivalently convert the original problem to an optimal pricing problem. Then, a distributed solution under the pricing framework via an efficient price-updating algorithm is proposed. Experimental results show that both two distributed solutions can achieve the maximum social welfare of a participatory smartphone system.     

The sociability score: App-based social profiling from a healthcare perspective

As the smartphone becomes an integral part of our lives, its value as a rich data source reaches an increasing potential. Several previous studies have used smartphone-derived data to discover relationships between user characteristics and different types of smartphone use. However, none tried to use smartphone data to capture an individual's social behavior into one profile, aimed at providing additional information for the diagnostic evaluation of social deficits. This study presents a novel way of combining different modalities of smartphone data for the creation of sociability profiles using a scoring mechanism that allows for easy addition and removal of data sources. Following installation of the smartphone application, data is being sampled in the background to allow for the assessment of spontaneous smartphone use. Sociability scores were based on the integration of social communication and social exploration scores derived from smartphone use and environmental data sampling (e.g., GPS and external Bluetooth signals). Finally, we have applied our Sociability model to create social profiles of ten test subjects as a baseline for future studies. This pilot study provided insight in the usability of the individual sociability scores for future smartphone application to provide longitudinal objective measures of normal and atypical human social behavioral profiles in their natural environment.     

Workshop Report: The Challenge of Complexity

The multiplicity of choices available to the designer in applying the technology peripheral devices to specific system products often constitutes a problem in itself. Thus, "The Challenge of Complexity" was selected by the Computer Elements Technical Committee as the theme of their recent Phoenix Workshop. Held at Carefree, Arizona, this past December 5-8, the meeting drew 55 attendees from 17 companies and four universities.     

Identifying and facilitating social interaction with a wearable wireless sensor network

We have designed a highly versatile badge system to facilitate a variety of interaction at large professional or social events and serve as a platform for conducting research into human dynamics. The badges are equipped with a large LED display, wireless infrared and radio frequency networking, and a host of sensors to collect data that we have used to develop features and algorithms aimed at classifying and predicting individual and group behavior. This paper overviews our badge system, describes the interactions and capabilities that it enabled for the wearers, and presents data collected over several large deployments. This data is analyzed to track and socially classify the attendees, predict their interest in other people and demonstration installations, profile the restlessness of a crowd in an auditorium, and otherwise track the evolution and dynamics of the events at which the badges were run.     

The dark side of smartphone usage: Psychological traits,compulsive behavior and technostress

Smartphones have become necessities in people’ lives. Along with its obvious benefits, however, the smartphone has other effects that are not all that glorious. This study investigates the dark side of the smartphone trend. We examine the link between psychological traits and the compulsive behaviors of smartphone users, and look further into the stress caused by those compulsive behaviors. We conducted an empirical study consisting of 325 participants and compared Structural Equation Modeling with competing models. The results suggest that compulsive usage of smartphone and technostress are positively related to psychological traits including locus of control, social interaction anxiety, materialism and the need for touch. Gender differences are also found in the aforementioned relationships. The results have practical implications to user-oriented smartphone design and operation companies as well as government agencies as they combat the social ills brought on by smartphones.     

Unusual business or business as usual: An investigation of meeting support requirements in multilateral diplomacy

The concept of supporting meetings at the same time and at the same place with computers raises the problem of how salient features of group behaviors are understood in meetings. In this paper we critically examine some aspects of meeting behaviors. We point out that the idea of small, cohesive business teams is not necessarily a valid starting point in thinking of all meeting support. In particular, beliefs that relate to user aspects, group features such as composition, structure and protocols, and task characteristics such as nature, importance, and goals in meetings may need deliberation in many group decision support systems (GDSS) interventions. To demonstrate the credibility of our analysis we investigate meeting behaviors typical in multilateral diplomacy and show that few, if any, of the widely held beliefs of meeting behaviors are valid in this context. Moreover, such behaviors are not uncommon or peculiar only to diplomatic arenas. Similar behaviors can be identified in any meeting environment where participants do not share the same social worlds, have conflicting values and interests, do not follow the same social habits and meeting protocols, act through a “representative” mandate, are changeable, and do not agree on issues at stake in the meeting process. Our analysis points out, however, that developing meeting support for such ‘fuzzy’ environments is not needless or unrealistic. The support functionality of a fuzzy GDSS must be simple and focus on central aspects of the meeting process (issues) which in our case revolves around text management and display. Moreover, sufficient attention must be paid to the physical meeting environment that must reflect the social structures and protocols.     

Practicing What We Preach: IEEE VR 2009 Virtual Program Committee Meeting

This article reports on the experience of conducting the program committee (PC) meeting for the IEEE VR 2009 conference in Second Life. More than 50 PC members from around the globe met virtually over a two-day period to decide which papers to accept for presentation at the conference. Survey responses from 42 of the PC members indicate generally positive feelings toward this meeting format, although several alterations will help improve interaction between attendees in future meetings.     

Smartphone habit and behavior in Brunei: Personalization,gender, and generation gap

A smartphone is a device which offers advanced technologies, functions similarly to a computer, supports multitasking and makes it easy to remain connected with others. The following survey design research examined the usage patterns of smartphone users across different demographics. The results of this study provide insights into the prevalence of respondents’ usage of smartphones and their habits and behavior related to smartphone use itself especially among the younger generation of social disorders such as nomophobia and phubbing. In addition to documenting the experience of smartphone users, the research also examines personality patterns related to smartphone usage, the trends of different age groups, and the effects of gender preferences.     

Smartphone addiction among university students in the light of some variables

We explored the frequency and indices of smartphone addiction in a group of King Saud University students and investigated whether there were differences in smartphone addiction based on gender, social status, educational level, monthly income and hours of daily use. We developed a questionnaire probing smartphone addiction consisting of five dimensions: 1) overuse of smartphone, 2) the psychological-social dimension, 3) the health dimension, 4) preoccupation with smartphones, and 5) the technological dimension. After being validated, the questionnaire was administered to 416 students, both male and female, at King Saud University. Results revealed that addiction percentage among participants was 48%. The order of smartphone addiction indices were as follows: overuse of smartphone, the technological dimension, the psychological-social dimension, preoccupation with smartphones, and the health dimension. Significant gender differences were found in the degree of addiction on the whole questionnaire and all of its dimensions with the exception of the technological dimension in favor of males. Significant differences by social status were found in favor of the unmarried. Bachelor degree students were found to have the highest degree of addiction. Significant differences by hours of daily use were also detected in favor of participants using the smartphone for more than 4 h a day. As to the monthly income dimension, significant differences were found on the health dimension in favor of participants with lower monthly income.     

MobiByte: An Application Development Model for Mobile Cloud Computing

Mobile cloud computing presents an effective solution to overcome smartphone constraints, such as limited computational power, storage, and energy. As the traditional mobile application development models do not support computation offloading, mobile cloud computing requires novel application development models that can facilitate the development of cloud enabled mobile applications. This paper presents a mobile cloud application development model, named MobiByte, to enhance mobile device applications’ performance, energy efficiency, and execution support. MobiByte is a context-aware application model that uses multiple data offloading techniques to support a wide range of applications. The proposed model is validated using prototype applications and detailed results are presented. Moreover, MobiByte is compared with the most recent application models with a conclusion that it outperforms the existing application models in many aspects like energy efficiency, performance, generality, context awareness, and privacy.     

Accurate smartphone indoor positioning using a WSN infrastructure and non-invasive audio for TDoA estimation

In this paper we propose a reliable acoustic indoor positioning system fully compatible with a conventional smartphone. The proposed system takes advantage of the smartphone audio I/O and its processing capabilities to perform acoustic ranging in the audio band using non-invasive audio signals and it has been developed having in mind applications that require high accuracy, such as augmented or virtual reality, gaming or audio guiding applications. The system works in a distributed operation mode, i.e. each smartphone is able to obtain its own position using only acoustic signals. In order to support the positioning system, a Wireless Sensor Network (WSN) of synchronized acoustic beacons is proposed. To keep the infrastructure in sync we developed an Automatic Time Synchronization and Syntonization (ATSS) protocol that ensures a sync offset error below 5 μs. Using an improved Time Difference of Arrival (TDoA) estimation approach (that takes advantage of the beacon signals’ periodicity) and by performing Non-Line-of-Sight (NLoS) mitigation, we were able to obtain very stable and accurate position estimates with an absolute error of less than 10 cm in 95% of the cases and a mean absolute standard deviation of 2.2 cm for a position refresh period of 350 ms.     

Understanding student simultaneous smartphone use in learning settings: A conceptual framework

Smartphone use in learning settings is a common behaviour amongst college students. Building on the theory of consumerism, self-efficacy and addictive behaviours, the current study developed a three-component conceptual framework to understand college students' smartphone use in organizational as well as self-directed learning settings. One thousand and thirty-three students in Shenzhen completed an online survey that measured their frequency of using smartphones in learning settings, motivation for using smartphones in learning settings, behavioural control self-efficacy, smartphone use time, problematic smartphone use, multitask habit and impulsiveness. Regression and configurational analytical approaches were used to examine linear and nonlinear relationships. Results support the use of the proposed framework to explain students' smartphone use behaviour in learning settings.     

Secure Encrypted Steganography Graphical Password scheme for Near Field Communication smartphone access control system

The revolutionary development of smartphone which offers compelling computing and storage capabilities has radically changed the digital lifestyles of users. The integration of Near Field Communication (NFC) into smartphone has further opened up opportunities for new applications and business models such as in industry for payment, electronic ticketing and access control systems. NFC and graphical password scheme are two imperative technologies that can be used to achieve secure and convenient access control system. One of the potential uses of such technologies is the integration of steganography graphical password scheme into NFC-enabled smartphone to transcend conventional digital key/tokens access control systems into a more secure and convenient environment. Smartphone users would have more freedom in customizing the security level and how they interact with the access control system. As such, this paper presents a secure two-factor authentication NFC smartphone access control system using digital key and the proposed Encrypted Steganography Graphical Password (ESGP). This paper also validates the user perception and behavioral intention to use NFC ESGP smartphone access control system through an experiment and user evaluation survey. Results indicated that users weigh security as a dominant attribute for their behavioral intention to use NFC ESGP smartphone access control system. Our findings offer a new insight for security scholars, mobile device service providers and expert systems to leverage on the two-factor authentication with the use of NFC-enabled smartphone.     

Cross-generational analysis of predictive factors of addictive behavior in smartphone usage

Smartphone addiction has been widely researched in recent years, and the effects of various demographic, personality-linked, psychological, and emotional variables, have been found. Our research goal was to examine this phenomenon from the cross-generational perspective and compare the factors that can predict smartphone addiction for different age groups. We conducted a study with 216 Israeli smartphone users, representing three generations of smartphone users: Generation X, Generation Y, and Generation Z, who filled in an 80-item questionnaire. The factors examined included the social environment pressure to use smartphone, emotional gain from smartphones, personality, daily usage time, various mobile apps and user needs. The main finding of the study is that a significantly higher level of addictive behavior was found for Generation Y compared to the other two generations. The strongest predictive factors in the computed hierarchical regression model for all three generations were social environment pressure and emotional gain. Interestingly, emotional gain from smartphone use, which reflects users' enjoyment and positive emotions along with relief of negative emotions and psychological states, was significantly higher for generation Z than for the older generations. In addition, neuroticism and the daily usage time appeared as predictive factors for the younger generations, and for Generation Z alone the WhatsApp app usage was found as a significant predictive factor as well. This study contributes to understanding the factors of smartphone addictive behavior for different generations, which might lead to more effective educational measures and explanatory campaigns on technology effects on psychological well-being.     

Fear of missing out,need for touch,anxiety and depression are related to problematic smartphone use

Problematic smartphone use is an important public health challenge and is linked with poor mental health outcomes. However, little is known about the mechanisms that maintain this behavior. We recruited a sample of 308 participants from Amazon’s Mechanical Turk labor market. Participants responded to standardized measures of problematic smartphone use, and frequency of smartphone use, depression and anxiety and possible mechanisms including behavioral activation, need for touch, fear of missing out (FoMO), and emotion regulation. Problematic smartphone use was most correlated with anxiety, need for touch and FoMO. The frequency of use was most correlated (inversely) with depression. In regression models, problematic smartphone use was associated with FoMO, depression (inversely), anxiety, and need for touch. Frequency of use was associated with need for touch, and (inversely) with depressive symptoms. Behavioral activation mediated associations between smartphone use (both problematic and usage frequency) and depression and anxiety symptoms. Emotional suppression also mediated the association between problematic smartphone use and anxiety. Results demonstrate the importance of social and tactile need fulfillment variables such as FoMO and need for touch as critical mechanisms that can explain problematic smartphone use and its association with depression and anxiety.     

The role of aesthetic,cultural, utilitarian and branding factors in young Chinese consumers' repurchase intention of smartphone brands

Despite the exponential growth of smartphone consumption, to date, very few studies have investigated the factors that influence consumers' repurchase intention of smartphone brands. China has become the world's largest consumer markets for smartphones, therefore understanding young Chinese consumers' repurchase intention in the smartphone market is of crucial importance to smartphone companies. A preliminary qualitative study based on 30 face-to-face interviews has led to the development of a new conceptual framework including aesthetic (design appeal), functional (perceived quality), brand value (brand popularity), social (subjective norm) and cultural influences (mianzi). The newly developed framework has been tested through partial least squares structural equation modeling with a sample of 321 young Chinese smartphone users. The results show that young Chinese customer's smartphone repurchase intention is mainly determined by mianzi, perceived quality, brand popularity, and design appeal. Furthermore, findings also highlight that subjective norm, perceived quality and design appeal affect Chinese people's mianzi.     

Smartphone addiction and its relationship with social anxiety and loneliness

Individuals with psychosocial problems such as social phobia or feelings of loneliness might be vulnerable to excessive use of cyber-technological devices, such as smartphones. We aimed to determine the relationship of smartphone addiction with social phobia and loneliness in a sample of university students in Istanbul, Turkey. Three hundred and sixty-seven students who owned smartphones were given the Smartphone Addiction Scale (SAS), UCLA Loneliness Scale (UCLA-LS), and Brief Social Phobia Scale (BSPS). A significant difference was found in the mean SAS scores (p?<?.001) between users who declared that their main purpose for smartphone use was to access social networking sites. The BSPS scores showed positive correlations with all six subscales and with the total SAS scores. The total UCLA-LS scores were positively correlated with daily life disturbance, positive anticipation, cyber-oriented relationship, and total scores on the SAS. In regression analyses, total BSPS scores were significant predictors for SAS total scores (β?=?0.313, t?=?5.992, p?<?.001). In addition, BSPS scores were significant predictors for all six SAS subscales, whereas UCLA-LS scores were significant predictors for only cyber-oriented relationship subscale scores on the SAS (β?=?0.130, t?=?2.416, p?<?.05). The results of this study indicate that social phobia was associated with the risk for smartphone addiction in young people. Younger individuals who primarily use their smartphones to access social networking sites also have an excessive pattern of smartphone use.     

Mining smartphone data for app usage prediction and recommendations: A survey

Smartphones nowadays have become indispensable personal gadgets to support our activities in almost every aspect of our lives. Thanks to the tremendous advancement of smartphone technologies, platforms, as well as the enthusiasm of individual developers, numerous mobile applications (apps) have been created to serve a wide range of usage purposes, making our daily life more convenient. While these apps are used, data logs are typically generated and ambience context is recorded forming a rich data source of the smartphone users’ behaviors. In this paper, we survey existing studies on mining smartphone data for uncovering app usage patterns leveraging such a data source. Our discussions of the studies are organized according to two main research streams, namely app usage prediction and app recommendations alongside a few other related studies. Finally, we also present several challenges and opportunities in the emerging area of mining smartphone usage patterns.