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The correct organization of transfers in the public transport system allows to reduce the congestion of the route network while maintaining a sufficient level of service quality for users of transport services. When modelling the probability of transfer, it is advisable to separate the probability of a public transport user choosing a trip with a transfer and the probability of making a transfer at a certain stop of the public transport system. The first probability largely depends on the socio-economic characteristics of the passenger and the time parameters of the trip. The probability of transfer at a certain stop is affected by the information provision of the stop and the number of routes. The general configuration of the route network determines the "basic need for a transfer in the network" - the ratio of the number of pairs of transport zones between which there is no direct public transport route to the total number of pairs of transport zones. The simulation carried out in the PTV Visum software environment for Lviv city made it possible to assess the impact of the tariff system on the change in the number of transfers and to determine critical stops and routes of the network. The inclusion of data on the structure of the city's population in the model makes it possible to use mathematical functions of the probability of transfer on the socio-economic characteristics of the passenger (age, gender, income level) when calculating the forecast number of transfers on the network. [ABSTRACT FROM AUTHOR]

Chatbots possess great potential benefits, yet concerns persist regarding users adopting inappropriate, offensive language. This research delved into the influence of user characteristics on verbally aggressive behaviours towards social chatbots. Employing a mixed-method study, we examined individual characteristics such as personal dispositions, offensive language patterns, academic majors, and prior experiences with conversational agents. Findings from a ten-day field experiment involving 33 participants using a real-world Telegram-based chatbot app unveiled that users' anthropomorphism, computer-related major, and gender significantly impact their moral emotions and evaluations of the chatbot's capabilities. Moreover, employing offensive language towards the chatbot detrimentally impacted users' perceptions of its abilities, helpfulness, and likability. The research findings advocate for ongoing monitoring and effective resolution of users' behaviours regarding the use of offensive language in their interactions with a chatbot. Additionally, the results underscore the importance of incorporating diverse perspectives into chatbot design to address biases and offensive utterances. [ABSTRACT FROM AUTHOR]

While AI technology is becoming increasingly prevalent in our daily lives, the comprehension of machine learning (ML) among non-experts remains limited. Interactive machine learning (IML) has the potential to serve as a tool for end users, but many existing IML systems are designed for users with a certain level of expertise. Consequently, it remains unclear whether IML experiences can enhance the comprehension of ordinary users. In this study, we conducted a public event using an IML system to assess whether participants could gain technical comprehension through hands-on IML experiences. We implemented an interactive sound classification system featuring visualization of internal feature representation and invited visitors at a science museum to freely interact with it. By analyzing user behavior and questionnaire responses, we discuss the potential and limitations of IML systems as a tool for promoting technical comprehension among non-experts. [ABSTRACT FROM AUTHOR]

Background: Digital mental health interventions (DMHIs) may reduce treatment access issues for those experiencing depressive and/or anxiety symptoms. DMHIs that incorporate relational agents may offer unique ways to engage and respond to users and to potentially help reduce provider burden. This study tested Woebot for Mood & Anxiety (W-MA-02), a DMHI that employs Woebot, a relational agent that incorporates elements of several evidence-based psychotherapies, among those with baseline clinical levels of depressive or anxiety symptoms. Changes in self-reported depressive and anxiety symptoms over 8 weeks were measured, along with the association between each of these outcomes and demographic and clinical characteristics. Methods: This exploratory, single-arm, 8-week study of 256 adults yielded non-mutually exclusive subsamples with either clinical levels of depressive or anxiety symptoms at baseline. Week 8 Patient Health Questionnaire-8 (PHQ-8) changes were measured in the depressive subsample (PHQ-8 ≥ 10). Week 8 Generalized Anxiety Disorder-7 (GAD-7) changes were measured in the anxiety subsample (GAD-7 ≥ 10). Demographic and clinical characteristics were examined in association with symptom changes via bivariate and multiple regression models adjusted for W-MA-02 utilization. Characteristics included age, sex at birth, race/ethnicity, marital status, education, sexual orientation, employment status, health insurance, baseline levels of depressive and anxiety symptoms, and concurrent psychotherapeutic or psychotropic medication treatments during the study. Results: Both the depressive and anxiety subsamples were predominantly female, educated, non-Hispanic white, and averaged 38 and 37 years of age, respectively. The depressive subsample had significant reductions in depressive symptoms at Week 8 (mean change =—7.28, SD = 5.91, Cohen's d = -1.23, p < 0.01); the anxiety subsample had significant reductions in anxiety symptoms at Week 8 (mean change = -7.45, SD = 5.99, Cohen's d = -1.24, p < 0.01). No significant associations were found between sex at birth, age, employment status, educational background and Week 8 symptom changes. Significant associations between depressive and anxiety symptom outcomes and sexual orientation, marital status, concurrent mental health treatment, and baseline symptom severity were found. Conclusions: The present study suggests early promise for W-MA-02 as an intervention for depression and/or anxiety symptoms. Although exploratory in nature, this study revealed potential user characteristics associated with outcomes that can be investigated in future studies. Trial Registration: This study was retrospectively registered on ClinicalTrials.gov (#NCT05672745) on January 5th, 2023. [ABSTRACT FROM AUTHOR]

Short-form videos are popular worldwide as a thriving form of entertainment. Its fragmentation pattern, which presents users with intensive and engaging information, might lead to addiction and adverse effects. This study aims to investigate the effect of addiction to short-form videos on users' attention, including attention while watching videos and the ability of attentional concentration after watching time. Users addicted or non-addicted to short-form videos were screened to participate in a short-form video watching task and a Stroop task based on eye-tracking technology. The results showed that addicted users reported less interest, centration, and more distractions and exhibited more fixation counts and shorter average fixation duration during watching short-form videos than non-addicted users. In the Stroop task, addicted users achieved longer response time and less accuracy and showed longer average fixation duration, more fixation counts, and saccades between the targets and the distractors than non-addicted users. The results suggest that addicted users might suffer more difficulties maintaining attention, have more attention deficits while watching short-form videos, and have impaired attentional concentration for processing interference. The findings contribute to understanding the effect of addiction to short-form videos and provide helpful insight into using it healthily and preventing addiction. [ABSTRACT FROM AUTHOR]

[Purpose/Significance] With the popularity and development of social media, Weibo has become an important information transmission platform. Understanding the law of emergency information transmission based on the characteristics of Weibo users is of great significance for grasping the development trend of events, evaluating the influence of information, and formulating effective response strategies. [Methods/Process] Selecting typical cases of four types of emergencies (natural disasters, accidents, public health events, and social security events) as the research objects, this paper crawled the user data of the information transmission on the Weibo platform and analyzed the distributions of user gender, user geographical distribution, user attention and fan number and user type of the information transmission for these events, in order to reveal the differences and similarities of the user characteristics and transmission laws for the four types of emergencies. [Results/Conclusions] As for the similarities of the user characteristics and transmission laws, first, the audiences of the four types of emergencies have obvious regional characteristics, and the users in economically developed provinces generally have a higher attention rate. Second, the transmission users of all types of emergencies are generally concentrated on active users and grassroot users with strong and weak propagation power respectively, accompanied by a small number of authoritative users with strong influence. However, there are differences in the broadness and gender distribution of the audiences for different types of emergencies. First, natural disasters have a wider spread of the audiences and relatively higher attentiveness; accidents and public health events tend to be local events with relatively low attentiveness, whose audiences may be more concentrated in and around the affected areas; the audience spread of social security events is scattered depending on the nature of the event, the scope of influence as well as the communication channels. Second, female users pay more attention to natural disasters, public health events and social security events, while male users pay more attention to accidents, which can be attributed to the different emotional orientations and psychological characteristics associated with users of different genders. These results provide insights for the formulation of targeted guidance strategies for information dissemination. In future studies, we will collect data on other social media platforms, obtain more information on user characteristics through different channels, and introduce more in-depth analysis methods and indicators to comprehensively reveal the dynamic mechanisms of emergency information dissemination, thus improving the accuracy and effectiveness of the research. [ABSTRACT FROM AUTHOR]

Conversational AI, like Amazon's Alexa, are often marketed as tools assisting owners, but humans anthropomorphize computers, suggesting that they bond with their devices beyond an owner-tool relationship. Little empirical research has studied human-AI relationships besides relational proxies such as trust. We explored the relationships people form with conversational AI based on the Relational Models Theory (RMT, Fiske, 1992). Results of the factor analyses among frequent users (Ntotal = 729) suggest that they perceive the relationship more as a master-assistant relationship (i.e., authority ranking) and an exchange relationship (i.e., market pricing) than as a companion-like relationship (i.e., peer bonding). The correlational analysis showed that authority ranking barely correlates with system perception or user characteristics, whereas market pricing and peer bonding do. The relationship perception proved to be independent of demographic factors and label of the digital device. Our research enriches the traditional dichotomous approach. The extent to which users see their conversational AI as exchange partners or peer-like has a stronger predictive value regarding human-like system perception of conversational AI than the perception of it as servants. [ABSTRACT FROM AUTHOR]

Understanding users' individual differences may provide clues to help identify computer users who are prone to act insecurely. We examine factors that impact home users' reported computer security behaviour. We conducted two online surveys with a total of 650 participants to investigate the relationship between self-reported security behaviour and users' knowledge, motivation, confidence, risk propensity and sex-typed characteristics. We found that all of these factors impacted security behaviour, with knowledge as the most important predictor. We further show that a user's affinity to feminine or masculine characteristics is a better determinant of security behaviour than using binary male/female descriptors. Our study enabled us to confirm earlier results in the literature in a non-organisational setting, and to extend the literature by studying additional factors and by comparing the relative importance of each factor as a predictor of security behaviour. [ABSTRACT FROM AUTHOR]

Objective/Significance: To measure the international communication capacity of China’s English academic journal papers based on social media platforms.Method/Process: Social network analysis, content analysis and emotion analysis were used to describe the diffusion structure of China’s English academic journal papers on Twitter from the aspects of network structure and identify important node users, explore the identity characteristics and emotion characteristics of users as well as diffusion capability of journals of different disciplines.Conclusion/Discovery: Journal articles in the fields of natural sciences and engineering as well as humanities and social sciences exhibit a strong positive correlation between their diffusion structure and network size. Networks with a mixed diffusion structure typically have larger network sizes. The users occupying key positions in the diffusion network typically have profile information that is academically relevant. The retweets and comments are mainly statements without emotional inclination, and the comments are mainly summary descriptions of the papers. The distribution of diffusion width, diffusion strength and diffusion speed of each discipline is significantly different. There is a significant positive correlation between the diffusion structure of papers and their diffusion capabilities.Innovation/Value: To reveal the diffusion structure and characteristics of China’s English academic journal papers on social media platforms, so as to provide reference for expanding the visibility of China’s English academic journals and improving the international dissemination capacity of China’s English journals. [ABSTRACT FROM AUTHOR]

The paradigm of developing mobile apps has shifted from native apps that store data on mobile devices to mobile cloud computing (MCC) apps that send data to the cloud. Transferring users' data to the cloud provides several benefits, such as larger storage capacity and simultaneous access by multiple devices and users. However, storing data in the cloud also raises privacy concerns as users do not have direct control over their data. This study reports a privacy cost–benefit analysis including the moderating effects of dispositional traits (i.e. two personality meta-traits: stability and plasticity) and the behaviour-based trait (i.e. use experience) to understand information disclosure behaviour. The empirical study is based on a scenario-based survey (n = 807) from a diverse sample of MCC apps users. The results support the moderating effects of personality meta-traits; stability and plasticity differentially moderate the effects of perceived privacy risk and perceived value of data transfer to the cloud on information disclosure behaviour. Contradictory to prior research, prior use experience does not moderate the effects of the cost–benefit perceptions. The implications of research and practice are discussed. [ABSTRACT FROM AUTHOR]

The fundamental function of a natural gas pipeline network is to transport enough natural gas to users. Therefore, user characteristics should be considered in the formulation of the flow allocation plan of the pipeline network under accident conditions. However, user characteristics have usually not been considered in previous flow allocation models. In this study, a mixed integer linear programming model is developed to determine the optimal flow allocation plan of a large-scale and complex natural gas pipeline network under accident conditions, and the user characteristics are considered as well. The optimization objective is to maximize the weighted sum of the amount of natural gas transported to the consumers under accident conditions, and the weights of the natural gas users are obtained by user characteristics analysis. The model constraints include flow constraints, gas source supply capacity constraints, user demand constraints, pipeline transmission capacity constraints, pressure constraints, and pipeline hydraulic constraint. For the sake of model simplification, the hydraulic constraints are treated piecewise linearly. Furthermore, the model is set into a real-world situation, which is the natural gas pipeline network located in China, and the user characteristics are considered in the optimal flow allocation plan under accident condition. The impact of user characteristics is further investigated by calculating and comparing the flow allocation plan when considering and ignoring user characteristics. The study indicates that when user characteristics are considered, the natural gas pipeline network will tend to give higher priority to those crucial users. [ABSTRACT FROM AUTHOR]

Social media has become one of the most powerful and ubiquitous means by which individuals curate and share their life stories with the world at large. Not surprisingly then, researchers have started to examine the reasons why individuals post personal memories on social media and said individuals' characteristics. Across two studies, we extended this line of research by further testing the Purposes of Online Memory Sharing Scale (POMSS) and its subscales: self, social, therapeutic and directive. Additionally, we examined which of these motives led college students (Study 1) and adults of a community sample (Study 2) to post personal memories on social media and whether said motives were associated with the individuals' psychological characteristics. Overall, the results revealed that emerging adults and older adults posted personal experiences on social media primarily for social reasons. We also found that extraversion, disclosure and social media usage predicted each of the motives for posting personal experiences on social media. In addition, individuals who were more lonely and who had lower self-esteem were more likely to post personal experiences on social media for therapeutic reasons. We discuss these results in terms of their implications towards understanding the mnemonic consequences associated with social media use. [ABSTRACT FROM AUTHOR]

This study explored care recipients’ characteristics in relation to Taiwan’s “Professional Services and Home-Based Reablement Under Long-Term Care 2.0” plan. Methods: Data were extracted from the care management information database of the long-term care system in Taiwan, and secondary data analysis was performed. Descriptive statistics and multiple logistic regression were used to analyze the factors affecting outcomes. Results: The study revealed the following two main results: (1) Factors significantly influencing care recipients’ approval of the relevant professional services were residential area, type of A care management unit, a younger age, a higher level of education, a lower level of caregiver burden, having a foreign care worker, and a higher dependency level. (2) The characteristics of care recipients who were likely to discontinue their participation in home-based reablement plans were age, living with family caregivers, not having a foreign live-in caregiver, having mild to moderate disabilities (long-term care CMS level), and greater long-term care resource availability. Conclusions: Policy makers can use the care recipient characteristics identified in this study as a reference for developing an effective intervention model for the long-term care of care recipient groups in the community to meet the needs of both care recipients and their caregivers. [ABSTRACT FROM AUTHOR]

International students are a sizeable user group of academic libraries. However, their everyday life information seeking (ELIS) behavior is seldom studied. This hinders the planning of information services and information literacy training. In light of this gap, this study surveyed 112 international students in a U.S. public university on: (1) how frequently respondents used 11 information sources; (2) how difficult it was to find information in various domains; and (3) how much their ELIS was affected by various information seeking problems. Differences between gender-study level categories and problem solving styles were tested using ANOVAs. The study found that Web search engines, social networking sites, new friends, printed resources, and traditional mass media were the top sources for ELIS. Six everyday information domains (e.g., legal, financial, and personal development information) ranked more difficult to find than academic information. Non-credible, irrelevant, and outdated information were found to be the top problems. There were more statistically significant problem solving style differences (especially on the Problem Solving Confidence subscale) than gender-study level differences. Notable gender-study level differences were still found. Male undergraduate students, for example, were more affected by their reluctance to ask personal questions. Lastly, the implications to information literacy education were discussed. [ABSTRACT FROM AUTHOR]

This study investigated which social media platforms are used as information sources, and for what purposes. It also examined how user characteristics are related to the use of different platforms. A Web-based survey was used to collect data from undergraduate students. Responses from more than 800 students showed that most of the social media platforms are used as information sources, where wikis, user reviews, and media-sharing sites emerged as the top platforms. The purpose of use varied across platforms. T-test and ANOVA results also revealed individual differences. Significant differences in gender, class level, academic discipline, and Big Five personality traits were found in the frequency of information seeking using different platforms and also in the purpose of use. Study findings have implications for information literacy (IL) education and information services. Because many students are actively using social media platforms for a variety of information-seeking purposes, it is suggested that IL programs embrace social media as potential information sources and offer effective strategies for using and evaluating these increasingly popular social media sources. [Copyright &y& Elsevier]

Background: Smartphone apps are increasingly used for health-related behaviour change and people discover apps through different sources. However, it is unclear whether users differ by mode of app discovery. Drink Less is an alcohol reduction app that received national media coverage in the UK caused by celebrity influence (a male TV and radio national broadcaster, aged 51). Our aim was to compare users who discovered the app before and after this coverage.Methods: A natural experiment assessing the impact of media coverage of Drink Less on users' socio-demographic and drinking characteristics, app engagement levels, and extent of alcohol reduction. The study period was from 17th May 2017 to 23rd January 2019, with media coverage starting on 21st August 2018. Users were 18 years or over, based in the UK and interested in drinking less. Interrupted time series analyses using Generalised Additive Mixed Models were conducted for each outcome variable aggregated at the weekly level.Results: In 66 weeks prior to the media coverage, 8617 users downloaded the app and 18,959 in 23 weeks afterwards. There was a significant step-level increase in users' mean age (B = 8.17, p < .001) and a decrease in the percentage of female users (B = -27.71, p < .001), though these effects dissipated non-linearly over time. No effect of media coverage was detected on employment type or on the percentage of at-risk drinkers, though the mean Alcohol Use Disorders Identification Test score was lower after the media coverage (B = -1.43, p = .031). There was a step-level increase in app engagement - number of sessions (B = 3.45, p = .038) and number of days used (B = 2.30, p = .005) - which continued to increase over time following quadratic trends.Conclusions: Celebrity influence leading to national media coverage in the UK of the Drink Less app was associated with more people downloading the app who were male, older and engaged with the app; and did not appear to impact employment inequality. [ABSTRACT FROM AUTHOR]

It is of great theoretical significance and practical value to analyze the characteristics of users and behaviors in social networks, to study the personalized recommendation algorithms of users, to explore the inherent laws of event development, and to predict the movement of information or opinions. This paper analyzes the Weibo behavior through machine learning and cloud computing technology. Moreover, this paper studies and analyzes traditional network algorithms, and proposes a microblog recommendation algorithm based on statistical features. At the same time, the research content of this paper focuses on microblog contents, user characteristics, user preferences, and influence levels. The algorithm has simple structure and strong computing performance and performs feature data mining through cloud computing big data method, which is suitable for online mining microblog behavior. In addition, the performance of the algorithm was analyzed by design comparison experiments. The research indicates that the research algorithm proposed in this paper has certain advantages, which can be applied to network behavior analysis mining, and can provide theoretical reference for subsequent related research. [ABSTRACT FROM AUTHOR]

Background: There is a paucity of research on the population characteristics of mail-order pharmacy users. Objective: This study utilized a nationally representative sample to examine the characteristics of mail-order pharmacy users. Methods: This study used data from the 2012 Medical Expenditure Panel Survey (MEPS). The outcome variable was defined as whether the participant had used a mail-order pharmacy during the study year. Logistic regression was conducted to determine the factors which influence mail-order pharmacy use. All analyses incorporated MEPS sampling weights to adjust for the complex survey design. Results: Among the 14,106 adults included, approximately 18% of them had used a mail-order pharmacy at least once to fill their prescription in 2012. Compared to community pharmacy users, mail-order pharmacy users were more likely to be white, older, married, have a higher family income, a higher educational level, have health insurance, and have a prescription with at least a 30-day supply. There is no difference in gender or urban/rural disparity. In addition, mail-order pharmacy users had a lower percentage of out-of-pocket costs. Conclusion: Mail-order pharmacy use was significantly associated with certain patient characteristics. Policymakers should consider these characteristics when promoting mail-order pharmacy use. [ABSTRACT FROM AUTHOR]

In recent years, with the development of social media platforms, more and more people express their emotions online through short messages. It is quite valuable to detect emotions and relevant topics from such data. However, the feature sparsity of short texts brings challenges to joint topic-emotion models. In many cases, it is necessary to know not only what people think of specific topics, but also which individuals have similar feedback, and what characteristics of these users have. In this paper, we propose a user group based topic-emotion model named UGTE for emotions detection and topic discovery, which can alleviate the above feature sparsity problem of short texts. Specifically, the characteristics of each user are used to discover groups of individuals who share similar emotions, and UGTE aggregates short texts within a group into long pseudo-documents effectively. Experiments conducted on a real-world short text dataset validate the effectiveness of our proposed model. [ABSTRACT FROM AUTHOR]

• Understand young people's ridesplitting behavior characteristics and behavioral impacts. • Reveal evidence of ridesplitting user characteristics and its interaction with traditional modals. • Explore who use ridesplitting services and how they behave. • Find out the impacts of ridesplitting on modal shift and car ownership. • College survey data from the on-demand ride service platform of DiDi in Hangzhou, China. To better understand the young people's ridesplitting behavior characteristics and behavioral impacts on the emerging ride-sourcing platform, we present a survey-based comparison of DiDi Hitch and DiDi Express Pool that provide ridesplitting services in Hangzhou, China. Hitch is a social carpooling platform that helps commuters share rides. Express Pool is a mobility network providing pooled rides as the ridesplitting option of Express. In this paper, we explore why ridesplitting is popular, which mode is the primary, and how ridesplitting affects young people's travel behavior. A total of 607 investigated responses were collected via the DiDi ride-sourcing platform. Based on the survey data, a variety of behavioral aspects were analyzed, including the trip purpose, temporal and spatial characteristics of trips, travel time/cost variation, and modal shift frequency. Behavioral impacts on modal shift were further analyzed in a binary logit framework. The findings show that Hitch and Express Pool have both similarities and differences. Hitch is intended for long trips, while Express Pool is mainly intended for short trips as a supplement of multimodal mobility. It also provides evidence for ridesplitting user identification and the market share loss of bus and taxi. Some suggestions are raised for discussions in future research. [ABSTRACT FROM AUTHOR]

User characteristics should be considered when designing features for e-health or m-health applications, as the developed solution should aim to support this specific target group. This study explores the effect of user characteristics (personality, health state, stress/recovery state, leadership behavior) on the interest and likelihood of using an app for health promotion activities at the workplace. Leaders are a key factor for the success of workplace health promotion; therefore, the target group of this study are leaders. The data of 412 leaders were collected in an online study. Hierarchical multiple linear regression analyses were conducted for four outcome criteria ("personal health," "contacting," "leadership feedback" and "corporate key figures"). The findings showed that neuroticism, physical health and health-promoting leadership were important predictors for using an app for monitoring personal health and getting in social contact about health issues. The stress/recovery state was significantly related to the feature of getting in social contact. [ABSTRACT FROM AUTHOR]

Searching for information on the web is regarded as a complex problem-solving activity involving a range of cognitive and affective processes. Anxiety is a key affective factor. In this article, we describe the construction and initial validation stages of the Information Retrieval on the Web Anxiety Rate (IROWAR) scale. The final structure of this inventory was validated with a sample of 183 English-speaking Internet users. Reliability analyses indicated that the factors were internally consistent (Cronbach's alpha: 0.92). When we checked divergent validity, we found negative correlations with both self-efficacy and positive attitude towards the Internet. There were no effects of either sex or age on the total IROWAR score, but the Internet search anxiety sum score decreased with the length of use. This scale will be useful in several domains, including research on the determinants of web anxiety, individuals' experience of web anxiety and ways of supporting them and Internet learning. [ABSTRACT FROM AUTHOR]

Researchers have examined avoidance of traditional media advertising (e.g., television advertising) and general Internet advertising (e.g., banner advertising), but less attention has been paid to search engine advertising (SEA) avoidance, particularly in the Chinese context. Therefore, I analyzed the effects of 3 components of user perception of SEA (perceived goal impediment, perceived advertising clutter, and prior negative experience) and 2 components of user characteristics (monthly income and advertising location awareness) on SEA avoidance in a sample of 348 working professionals who use Chinese search engines. Results showed that user perception had a significantly positive impact on SEA avoidance, monthly income attenuated the positive impact of perceived advertising clutter but intensified the positive impact of prior negative experience on SEA avoidance, and advertising location awareness enhanced the positive impact of perceived advertising clutter on SEA avoidance. Implications of the findings for effective advertising on search engines are discussed. [ABSTRACT FROM AUTHOR]

Several studies indicate the benefit of mapping gamification elements to personality. However, this mapping requires a strong understanding of the relationship between gamification elements and personality. The existing research that has tried to address this relationship is based on a self-report questionnaire that is obtained from only those learners who complete the entire study. Unfortunately, a bias may result from first forcing learners to complete an entire study and then ignoring learners who drop out in the middle of a study. To overcome this bias, we use a more objective approach to understand the relationship between personality and gamification. In our study, we use the dropout rate as a proxy for learner motivation. We hypothesize that learners who are more motivated by gamification elements will use the gamified website longer. Furthermore, because we use a different method than previous studies used, we analyse our data differently. Our solution is to use survival analysis to analyse our data, which confirms the benefit of using gamification to enhance learner motivation. Our results point to the relationship between the response of different personalities and gamification elements. In further studies, we recommend to use this same approach but with more gamification elements. RESEARCH HIGHLIGHTS Gamification plays an important role in enhancing learners' motivation and engagement. Different personalities respond differently to gamification elements. The dropout rate can be used to measure learners' motivation. Enhancing the motivation of learners does not necessarily improve their learning. [ABSTRACT FROM AUTHOR]

A new approach to understanding human online behavior in regard to psychological functioning is proposed through the developed user's activity model incorporating the influences of social behavior, network, and content. Microscopic levels of user characteristics induced by personality traits were interpolated as interaction rules, whilst an unsupervised clustering algorithm was applied to penetrate the individual complexity. Temporal behavior of disparate users was mimicked, and streaming network data was generated and computationally analyzed. A comprehensive understanding of how individuality, friendship, and varying temperaments dramatically reshaped the networks was gained from insight synthesis of network properties characterized by small-world, scale-free, and centrality measures. Evidence illustrates that users with high extraversion possess high numbers of friends and spread massive information, while high conscientious and high intellect users are seriously discreet in accepting friends and often produce influential content. These results not only provide a wealth of challenges for product recommendation, network structure optimization, and design, but also are useful for the prediction of future network structural evolution. [ABSTRACT FROM AUTHOR]

Twitter has become a popular microblogging service that allows millions of active users share news, emergent social events, personal opinions, etc. That leads to a large amount of data producing every day and the problem of managing tweets becomes extremely difficult. To categorize the tweets and make easily in searching, the users can use the hashtags embedding in their tweets. However, valid hashtags are not restricted which lead to a very heterogeneous set of hashtags created on Twitter, increasing the difficulty of tweet categorization. In this paper, we propose a hashtag recommendation method based on analyzing the content of tweets, user characteristics, and currently popular hashtags on Twitter. The proposed method uses personal profiles of the users to discover the relevant hashtags. First, a combination of tweet contents and user characteristics is used to find the top-k similar tweets. We exploit the content of historical tweets, used hashtags, and the social interaction to build the user profiles. The user characteristics can help to find the close users and enhance the accuracy of finding the similar tweets to extract the hashtag candidates. Then a set of hashtag candidates is ranked based on their popularity in long and short periods. The experiments on tweet data showed that the proposed method significantly improves the performance of hashtag recommendation systems. [ABSTRACT FROM AUTHOR]

Identity and the different roles identities play in social question-answering communities have long been discussed from both a theoretical and empirical standpoint. Identity is usually analysed in ways that emphasise a transaction, and many studies use third-party raters to assign value judgements to these factors, which may not be relevant to a community. In this article, we examine identity in Stack Overflow, a question and answer site dedicated to solving computer-programming problems, which has a competitive community run reputation system. Profiles on Stack Overflow are highly customizable, allowing users to choose the level of personal information they want to share: from extensive to none. We develop a categorisation scheme using grounded theory to develop definitions of identity, and analyse behaviour based on these definitions. We find that the choice of identity is diverse within the community and that there is a correlation with identifiers and increased reputation earning among the general population. An analysis of elite users, however, indicates that identity is closely tied to membership length, but not to performance. The results indicate that allowing identity choices does affect system efficacy or user outcomes. [ABSTRACT FROM AUTHOR]

In order to improve the precision of similarity calculation and recommendation accuracy and reduce data sparseness, we propose a collaborative filtering recommendation algorithm based on item attribute values and user features. Firstly, based on the user preference for item attribute values，we calculate the rating distribution of item attribute values and rating expectations，and obtain the user-attribute value rating matrix. In the meantime, we use a data similarity measure method to find user characteristics neighbors and fill the sparse user-attribute value rating matrix，thus obtaining the preference set of the nearest-neighbors. Thirdly, we calculate the rating of the unrated attribute values, and sort the means of the rating of all item attribute values, thus obtaining a Top-N recommendation list for the target user. Experiment on the Movie Lens data set and Book Crossing data set show that the algorithm can better overcome the data sparsity problem and enhance recommendation accuracy. [ABSTRACT FROM AUTHOR]

A blog acts as a platform of virtual communication to share comments or views about products, events and social issues. Like other social web activities, blogging actions spread to a large number of people. Users influence others in many ways, such as buying a product, having a particular political or social opinion or initiating new activity. Finding the top influential bloggers is an active research domain as it helps us in various fields, such as online marketing, e-commerce, product search and e-advertisements. There exist various models to find the influential bloggers, but they consider limited features using non-modular approach. This paper proposes a new model, Popularity and Productivity Model (PPM), based on a modular approach to find the top influential bloggers. It consists of popularity and productivity modules which exploit various features. We discuss the role of each proposed and existing features and evaluate the proposed model against the standard baseline models using datasets from the real-world blogs. The analysis using standard performance evaluation measures verifies that both productivity and popularity modules play a vital role to find influential bloggers in blogging community in an effective manner. [ABSTRACT FROM PUBLISHER]

Background: Recent reports suggest an increase in use of extremely potent cannabis concentrates such as Butane Hash Oil (BHO) in some developed countries. The aims of this study were to examine the characteristics of BHO users and the effect profiles of BHO.Design: Anonymous online survey in over 20 countries in 2014 and 2015. Participants aged 18 years or older were recruited through onward promotion and online social networks. The overall sample size was 181,870. In this sample, 46% (N=83,867) reported using some form of cannabis in the past year, and 3% reported BHO use (n=5922).Measurements: Participants reported their use of 7 types of cannabis in the past 12 months, the source of their cannabis, reasons for use, use of other illegal substances, and lifetime diagnosis for depression, anxiety and psychosis. Participants were asked to rate subjective effects of BHO and high potency herbal cannabis.Findings: Participants who reported a lifetime diagnosis of depression (OR=1.15, p=0.003), anxiety (OR=1.72, p<0.001), and a larger number of substance use (OR=1.29, p<0.001) were more likely to use BHO than only using high potency herbal cannabis. BHO users also reported stronger negative effects and less positive effects when using BHO than high potency herbal cannabis (p<0.001) CONCLUSION: Mental health problems and other illicit drug use were associated with use of BHO. BHO was reported to have stronger negative and weaker positive effects than high potency herbal cannabis. [ABSTRACT FROM AUTHOR]

Collaborative filtering was an effective technique addressing the information overload problem. Aiming at the memory based recommendation suffered from difficulty in scalability，model-based recommendation had a multitude of parameters to train conducted a study，thus this paper proposed K-means user clustering algorithm based on user characteristics. Then，by using distributed collaborative filtering framework mixed with item based and user based collaborative filtering to train a model to every cluster. The experimental result shows that the proposed algorithm can greatly improve the recommendation precision. And solves the limitations of model based and memory based recommendations to a certain extent at the same time. [ABSTRACT FROM AUTHOR]

User Interface Design is an essential part of any software application. Accordingly, online examination is an equally important system within eLearning. Consequently, online examination design features are a significant factor in enhancing exam efficiency as well as convenience for examinees. Nine main design features are generally applied in the online exam, namely font (i.e., type, size, colour, and style), background colour, sound alert, questions group, time counters, and number of questions per page. The values of these features are closely related to user characteristics, whether relating to the physical, cognitive, psychomotor, demographics or experience. Our experiment was conducted on 119 students to identify the commonly preferred online examination design. The results show that the students had variations in their choice of online exam interface design, where students preferred to group questions by Topic and then by Type. The most popular font type was Arial with a size of 14 or 12 and using regular font style. Moreover, white background and black text were the most preferred. Most of the students selected 5 and 3 questions/page respectively. Countdown Timer was the most preferred time counter. Regarding sound alert, the 15 and 5 min remains were the most selected by students. [ABSTRACT FROM AUTHOR]

Casual carpooling is an informal form of commuter ridesharing operating in Washington, D.C.; Houston, Texas; and San Francisco, California. In contrast to new forms of shared-use mobility, casual carpooling has been in existence for over 30 years and uses no information communication technology, and is entirely run informally by its users. Researchers have been fascinated by this phenomenon and have conducted studies in the past, but there remains a lack of up-to-date quantitative data. This study examines the motivations and behaviors of casual carpoolers in the San Francisco Bay Area to understand user characteristics and motivations. In Winter 2014, the authors observed and counted participants and vehicles at four casual carpooling locations, interviewed participants riding in carpooling vehicles ( N =16), and conducted intercept surveys ( N =503) at 10 East Bay pickup locations. The results indicate that the motivations for casual carpooling participation include convenience, time savings, and monetary savings, while environmental and community-based motivations ranked low. Casual carpooling is an efficient transportation option for these commuters, while environmental sustainability benefits are a positive byproduct. Seventy-five percent of casual carpool users were previously public transit riders, and over 10% formerly drove alone. Logit modeling found that casual carpool role (i.e., always a rider or sometimes a driver), age, and employment status were key drivers in modal choice. Further research on a larger scale is needed to identify the elements needed for system replication in different areas. [ABSTRACT FROM AUTHOR]

The short product life cycle of information and communication technology (ICT) applications makes it critical for developers to expedite the diffusion process by reducing user resistance. At the individual level, the adoption of an ICT application largely depends on how a person is ready to use the computerized tool in place of the corresponding traditional method for a certain purpose. To find out how to facilitate the transition, this study investigates the human choice behavior involved in technology adoption with the Activity Theory that allows for the inclusion of different tools in one unit of analysis. The understanding of user situated experiences from the activity perspective leads to hypothesized relationships between user-, tool- and task-related factors and the dependent variable in terms of tool readiness. The empirical results support that tool experiences have stronger effects on specific tool readiness at the within-subject level, user characteristics have weaker effects on general tool readiness at the between-subject level, and task situations influence both levels of tool readiness. The findings provide insights on how to facilitate innovation diffusion for different tools, tasks and users. [ABSTRACT FROM AUTHOR]

An effective user authentication mechanism should embrace both security and usability aspects as its purpose is to ensure safety of operation of online services but as well usability and transparency to its end users. In an attempt to improve the usability and overall experience of user interactions during authentication, this paper proposes an alternative approach of personalizing user authentication tasks based on individual differences in cognitive processing. The presented approach is mainly driven by theories on individual differences in cognitive styles which argue that individuals recall and process textual and graphical information differently. In this realm, the paper presents a 4-month user study in which 153 participants interacted with a personalized user authentication mechanism in an ecological valid context. Analysis of results shows that the presented user authentication approach is a promising alternative to current state of user authentication practices. [ABSTRACT FROM AUTHOR]

The ability to successfully navigate in healthcare facilities is an important goal for patients, visitors, and staff. Despite the fundamental nature of such behavior, it is not infrequent for planners to consider wayfinding only after the fact, once the building or building complex is complete. This review argues that more recognition is needed for the pivotal role of wayfinding in healthcare facilities. First, to provide context, the review presents a brief overview of the relationship between environmental psychology and healthcare facility design. Then, the core of the article covers advances in wayfinding research with an emphasis on healthcare environments, including the roles of plan configuration and manifest cues, technology, and user characteristics. Plan configuration and manifest cues, which appeared early on in wayfinding research, continue to play a role in wayfinding success and should inform design decisions. Such considerations are joined by emerging technologies (e.g., mobile applications, virtual reality, and computational models of wayfinding) as a way to both enhance our theoretical knowledge of wayfinding and advance its applications for users. Among the users discussed here are those with cognitive and/or visual challenges (e.g., Down syndrome, age-related decrements such as dementia, and limitations of vision). In addition, research on the role of cross-cultural comprehension and the effort to develop a system of universal healthcare symbols is included. The article concludes with a summary of the status of these advances and directions for future research. [ABSTRACT FROM AUTHOR]

The increasing maturity of information technologies (IT) in hospitals and their infrastructure development is improving the quality and efficiency of healthcare services. In these circumstances, an investigation of the diffusion of IT in this context would provide some insight into adopters’ behaviours and further the diffusion of IT in the near future. The purpose of this paper is to conduct an investigation of the diffusion of IT’s innovations in hospitals. Technology acceptance model and innovation diffusion theory have been applied in this research trying to find factors that permit an effective discrimination between early and late adopters. The differences in characteristics between these two categories are assessed and implications based on the research findings are discussed. [ABSTRACT FROM PUBLISHER]

After analyzing the sparsity of traditional collaborative filtering algorithm and the merit and demerit of current solutions, this paper proposed a collaborative filtering recommendation algorithm based on user characteristics and item attributes which was mainly based on the item-based collaborative algorithm. It predicted the unrated items by analyzing different users' interests to various attributes of items and integrating the attributes of rated items to reduce the sparsity of data sets, and then to improve the accuracy of items' similarity calculation. The experimental results based on MovieLens data set show that the sparsity of extreme data sets can be reduced effectively, to a certain extent the proposed algorithm alleviates the cold starting problem in collaborative filtering algorithm and achieves better prediction accuracy. [ABSTRACT FROM AUTHOR]

Abstract: In order to introduce social robots successfully, we must first understand the underlying reasons whereupon potential users accept these robots to reside within their own homes. An extensive literature review has been conducted and provides an overview of variables influencing the acceptance of social robots categorized by utilitarian variables, hedonic variables, user characteristics, social normative beliefs and control beliefs. In a user study, in which 60 participants interacted with a social robot, both the robot itself and the interaction experience the users had with the robot were evaluated. The results indicate that especially the variables of usefulness, adaptability, enjoyment, sociability, companionship and perceived behavioral control are important evaluating the user acceptance of social robots. Hence, the present study contributes to human–robot interaction research by designating the variables that lead to social robot acceptance. Subsequently, this study may serve as a onset in developing an integral model which takes into consideration the relevant determinants of social robot acceptance. [Copyright &y& Elsevier]

Background: The use of reactive strategies to disseminate effective Internet-delivered lifestyle interventions restricts their level of reach within the target population. This stresses the need to invest in proactive strategies to offer these interventions to the target population. The present study used a proactive strategy to increase reach of an Internet-delivered multi component computer tailored intervention, by embedding the intervention in an existing online health monitoring system of the Regional Public Health Services in the Netherlands. Methods: The research population consisted of Dutch adults who were invited to participate in the Adult Health Monitor (N = 96,388) offered by the Regional Public Health Services. This Monitor consisted of an online or a written questionnaire. A prospective design was used to determine levels of reach, by focusing on actual participation in the lifestyle intervention. Furthermore, adequacy of reach among the target group was assessed by composing detailed profiles of intervention users. Participants' characteristics, like demographics, behavioral and mental health status and quality of life, were included in the model as predictors. Results: A total of 41,155 (43%) people participated in the Adult Health Monitor, of which 41% (n = 16,940) filled out the online version. More than half of the online participants indicated their interest (n = 9169; 54%) in the computer tailored intervention and 5168 participants (31%) actually participated in the Internet-delivered computer tailored intervention. Males, older respondents and individuals with a higher educational degree were significantly more likely to participate in the intervention. Furthermore, results indicated that especially participants with a relatively healthier lifestyle and a healthy BMI were likely to participate. Conclusions: With one out of three online Adult Health Monitor participants actually participating in the computer tailored lifestyle intervention, the employed proactive dissemination strategy succeeded in ensuring relatively high levels of reach. Reach among at-risk individuals (e.g. low socioeconomic status and unhealthy lifestyle) was modest. It is therefore essential to further optimize reach by putting additional effort into increasing interest in the lifestyle intervention among at-risk individuals and to encourage them to actually use the intervention. Trial registration: Dutch Trial Register (NTR1786) and Medical Ethics Committee of Maastricht University and the University Hospital Maastricht (NL2723506809/MEC0903016). [ABSTRACT FROM AUTHOR]

This study examined how internet users' psychological characteristics, amount of internet use and demographic factors contribute to particular dimensions of internet addiction. The sample consisted of 384 adolescents, ranging in age from 15 to 18 years. Participants were asked to complete the Internet Addiction Test (IAT), measures of Locus of Control, Depression, Loneliness, Self-esteem, and Social Anxiety as well as an inventory that included demographic factors and questions about the amount of Internet use. Results revealed significant associations between variables and different sets of predictors across the four dimensions of Internet use behaviour identified in the study. However, locus of control, depression, and amount of internet use were significant predictors of all internet addiction dimensions. Recommendations are provided on how researchers can strengthen the field of research concerning how internet addiction is manifested and which adolescent internet users are more susceptible to different manifestations of addiction. [ABSTRACT FROM AUTHOR]

This paper deals with the use of learning styles in technology-enhanced learning by introducing a "Unified Learning Style Model" (ULSM). The article aims at providing answers to three main questions: "What is ULSM?", "Why do we need it?" and "How can we use it?" First, a critical analysis regarding learning styles is provided; the identified challenges are addressed by proposing the use of a new model, specifically designed for TEL use. This model integrates learning preferences extracted from several traditional learning style models, related to perception modality in a way for processing and organizing information, as well as motivational and social aspects. A detailed description of the ULSM components is provided together with its rationale and its advantages. The practical applicability of the model is also shown by briefly introducing an adaptive web-based educational system based on it (called WELSA). [ABSTRACT FROM AUTHOR]

Abstract: Concessionary fares are offered to those aged 60 and over for bus travel in Britain. This study examines the effects of replacing a half-fare concession in England by free travel in April 2006. Aggregate data are used to examine trends; in addition, a large sample was obtained of pass holders in the Salisbury area, which enables a clear distinction to be drawn between increased travel by those who already held a half-fare pass, and travel by those taking up the pass for the first time. These data are then used to derive fare elasticities, and compare the characteristics of new passholders and those previously holding a half-fare pass. Comparisons are made with studies elsewhere. Overall policy implications are reviewed. [Copyright &y& Elsevier]

The present study examined the PDA menu navigation performance of younger and older adults. The research focus was directed to the understanding of the combination and interaction of user characteristics with PDA menu navigation performance. In order to detail individual factors that influence user's performance, users' age, spatial ability, verbal memory, the confidence to use technical devices and computer-expertise were studied and related to performance outcomes. Younger and older adults, experienced with the usage of different technical devices, but PDA novices, had to complete four common tasks in the digital diary of an emulated PDA and users' effectiveness and efficiency were surveyed. Even though the users of both age groups had a comparably high computer experience, participants had considerable difficulties to solve the PDA tasks successfully. Especially older adults were strongly disadvantaged when navigating through the PDA menu. Among the user characteristics which were revealed to be essential for performance, spatial abilities were the best predictor to explain PDA performance. In addition, an adequate mental representation of the PDA data structure was decisive for navigation performance, especially in the older adult group. [ABSTRACT FROM AUTHOR]

Rangelands cover about 54 percent of total land in Iran. In spite of their very high importance, rangelands are degrading each year. The national plan of balancing livestock with grazing capacity (BLGC) is intended to aid in rangeland preservation and promotion. There are three main activities in the plan: (1) preparation and implementation of rangeland projects, (2) exercise of management in the grazing of rangelands, and (3) conversion of low-yield rain-fed lands to fodder crop fields. Two important objectives are followed in the process: (1)decreasing the number of rangeland users and (2) preventing an excess of livestock over rangeland capacity. Diffusion of innovation theory has been employed in this study to describe how rangeland users would go about accepting the projects in the plan BLGC. The purpose of this study is to find out the role of BLGC plan attributes, individual user characteristics, and extension methods in acceptance of the plan. The collaborating population in the study comes from 15 provinces in Iran. The statistical population consisted of 119 rangeland users. Spearman Test indicated a positive and meaningful correlation between BLGC attributes, extension methods, and the rate of BLGC plan adoption. Among BLGC plan-related attributes, relative advantage exhibits the most effect as indicated by results obtained from regression analysis. From among individual characteristics, education, and from among extension methods, symbolic ceremonies as well as contact with change agents and experts have been observed to be the most influential in the rate of BLGC plan adoption. [ABSTRACT FROM AUTHOR]

Objectives To determine the number of women fitted with a diaphragm or cervical cap at family planning clinics across the Australian State of New South Wales (NSW) from 2000 to 2005. To compare the demographic characteristics of women fitted with this form of contraceptive with women prescribed the combined oral contraceptive pill (COCP). Method An audit of women presenting for contraceptive services between 2000 and 2005 was undertaken. The demographic characteristics of women fitted with a barrier method or prescribed the COCP between 1st April, 2002, and 31st October, 2004, were obtained from the Family Planning NSW Activity Data Set (FADS). Results The proportion of women fitted with a diaphragm or cap remained constant between 2001 and 2005 at approximately 5%. During the 31 months that the study period lasted, 793 women were fitted with a diaphragm or cervical cap compared with 8047 women prescribed the COCP during the same time frame (including 76 women who received both a diaphragm and COCP prescription during this period). Women fitted with the barrier contraceptive were significantly more likely to be older, to have received a tertiary level education and to have private health insurance than their counterparts prescribed the COCP. They were less likely to come from a non-English speaking background. Discussion The diaphragm and cervical cap are viable contraceptive methods for a specific group of older, well-educated women. The possible benefits of female-controlled barrier devices in the prevention of sexually transmissible infections may result in a wider demographic use in the future. [ABSTRACT FROM AUTHOR]

A multisite evaluation of community mental health services is used to answer two questions: (a) How do diagnosis, functioning, and self-assessments of consumer/survivor initiative (CSI) and assertive community treatment (ACT) participants compare?, and (b) What other supports/services are CSI and ACT participants using? The sample is from an Ontario evaluation of consumer/survivor peer initiatives in four communities (n=73). The reference group is new (n=48) and ongoing (n=134) clients of four ACT teams. Self-help organizations are serving a broader population of individuals who include a significant subgroup of persons with severe mental illness along with others with a mixed picture of higher functioning and greater instability. There is little overlap in the use of these modes of service delivery, which suggests that maintaining options within systems of care is critical to ensuring coverage and access for the broader population. [ABSTRACT FROM AUTHOR]

This editorial paper introduces an emerging area for human–computer interaction research, which concerns interaction design and children. To avoid treating children as a homogeneous user group, it discusses some perspectives on their development, their use of technology for entertainment and education and, finally, how to involve children in the various stages of the design process. [Copyright &y& Elsevier]

Creativity support systems (CSS) aim at enhancing the creativity of users. There is an emerging stream of research in which the effects of CSS on the creative output of respondents are measured. In this research, it is important to make a clear distinction between the dependent variable, creative output, and the independent variable use of CSS. Furthermore, the research design should take the potential effect of other factors on creative output into account, most notably, creative ability as a trait of the respondents. An experimental study on the value of creativity support systems was recently reported in MIS Quarterly (Massetti 1996). That study yielded interesting insights with respect to the value of CSS. However, because of the methodology applied in analyzing the data, the study underestimated the effects of CSS on the creative output of decision makers. In this note, Massetti's experiment is positioned in the broader perspective of current research in the area of CSS, and an alternative framework for analyzing the data is proposed. [ABSTRACT FROM AUTHOR]