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Background: Bangladesh reports one of the highest rates of intimate partner violence (IPV) in the world. Despite wide recognition of IPV as an important public health and human rights issue, evidence for IPV prevention is still inadequate. Lack of guidance on effective IPV prevention in Bangladesh resulted in targeting only women in most of the programmes. Methods: This paper assesses impact of SAFE, a 20-month intervention (March 2012 to October 2013) in slums of Dhaka on IPV and tests effectiveness of female only groups vs. no groups; and female + male groups vs. female only groups on IPV in the community using a three-arm cluster randomized controlled trial. SAFE’s core activities included interactive group sessions, community mobilisation, and services. The last two activities were common across arms. Findings: Regression analyses (female survey: baseline n = 2,666; endline n = 2,670) showed no effect of SAFE on IPV against women aged 15–29. However, sub-group analyses demonstrated 21% risk reduction of physical IPV against adolescent girls aged 15–19 in the female + male group intervention arm. A consistent reduction in sexual violence was observed in both female and female + male arms for both groups of women, but the results were not statistically significant. Interpretation: The findings emphasise the importance of combining male and female interventions for reducing physical IPV against adolescent girls. Implications for future research have been discussed. [ABSTRACT FROM AUTHOR]

The paper estimates the effect of students’ position in the classroom register on their academic performance. We use a unique dataset from Poland which contains information on the academic outcomes of students in the humanities, science and mathematics lower secondary school exams as well as the position students occupy in their classroom register. We find that students whose names are recorded near the end of the class list have lower performance than those students whose names are recorded near the beginning of the list. The effect appears to be larger for performance in the humanities exam, and for low-achieving boys who attend large classes. [ABSTRACT FROM AUTHOR]

While numerous papers have illuminated the worthiness of research collaboration, relatively few have addressed its prerequisites. In our study, seven prerequisites for research collaboration were extracted from the existing literature, and 460 student researchers were surveyed for their perceptions of the prerequisites’ importance. Focusing on voluntary research collaborations rather than brokered ones, it was found that socially oriented prerequisites such as reciprocal interactions, accountability, trust, and equality are perceived of more importance than prerequisites of psychical proximity, networking channels, and funds and material supplies (substance- and entity-related prerequisites). With latent regression analyses, we also found that Chinese and older, more experienced researchers are inclined to stress the importance of equality. Researchers of different cohorts prioritise substance- and entity-related prerequisites disparately. Specifically, Chinese researchers emphasise the necessity of funds, while researchers from first-tier universities place more value on networking channels. Disciplinary differences for the prerequisite of proximity were also discovered. Based on these results, discussion and implications were referred. Further suggestions on research collaboration studies are rendered. [ABSTRACT FROM AUTHOR]

The ‘irrational’ preference for fairness has attracted increasing attention. Although previous studies have focused on the effects of spitefulness on the evolution of fairness, they did not consider non-monotonic rejections shown in behavioral experiments. In this paper, we introduce a non-monotonic rejection in an evolutionary model of the Ultimatum Game. We propose strategy intervention to study the evolution of fairness in general structured populations. By sequentially adding five strategies into the competition between a fair strategy and a selfish strategy, we arrive at the following conclusions. First, the evolution of fairness is inhibited by altruism, but it is promoted by spitefulness. Second, the non-monotonic rejection helps fairness overcome selfishness. Particularly for group-structured populations, we analytically investigate how fairness, selfishness, altruism, and spitefulness are affected by population size, mutation, and migration in the competition among seven strategies. Our results may provide important insights into understanding the evolutionary origin of fairness. [ABSTRACT FROM AUTHOR]

Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks. [ABSTRACT FROM AUTHOR]

This paper reports on a social discounting experiment conducted with university students in South Africa. In line with other social discounting task experiments, participants identify target individuals at different degrees of intimacy in their social network and then make 10 choices involving sums of money for themselves or their targets. For an altruism premium to exist, senders’ donations to recipients should be positive, statistically and economically significant, and independent of relationship closeness. We hypothesize that in addition to the altruism premium for kin documented in the literature, there may be other premia for family in general and for partners and friends. We find that, apart from the “kinship” premium, there is a sizeable “intimacy” premium, which together translates into a substantial “family” premium. The study also finds a “friendship premium”, as is documented in various experiments. The closeness of relationships among family and kin, especially close kin, has a significant and large effect on altruism. The results also attest to the importance of the extended family in regards to the “kinship” premium on altruism. These various premiums on altruism emphasise the importance of the supportive role of various social systems. Nevertheless, altruism within families and among close kin might also be enhanced by building more cohesive and stronger families using developmental social welfare programmes. [ABSTRACT FROM AUTHOR]

Micro-blogging systems have become one of the most important ways for information sharing. Network structure and users’ interactions such as forwarding behaviors have aroused considerable research attention, while mention, as a key feature in micro-blogging platforms which can improve the visibility of a message and direct it to a particular user beyond the underlying social structure, is seldom studied in previous works. In this paper, we empirically study the mention effect in information diffusion, using the dataset from a population-scale social media website. We find that users with high number of followers would receive much more mentions than others. We further investigate the effect of mention in information diffusion by examining the response probability with respect to the number of mentions in a message and observe a saturation at around 5 mentions. Furthermore, we find that the response probability is the highest when a reciprocal followship exists between users, and one is more likely to receive a target user’s response if they have similar social status. To illustrate these findings, we propose the response prediction task and formulate it as a binary classification problem. Extensive evaluation demonstrates the effectiveness of discovered factors. Our results have consequences for the understanding of human dynamics on the social network, and potential implications for viral marketing and public opinion monitoring. [ABSTRACT FROM AUTHOR]

Psychological and other persuasive mechanisms across diverse contexts are well researched, with many studies of the effectiveness of specific persuasive techniques on distinct types of human behaviour. In the present paper, our specific interest lies in the development of a generalized modular psychometric tool to measure individuals’ susceptibility to persuasion. The scale is constructed using items from previously developed and validated particulate scales established in the domains of social psychology and behavioural economics. In the first study we establish the Susceptibility to Persuasion–II (StP-II) scale, containing 54 items, 10 subscales and further 6 sub-sub scales. In Study 2 we establish the scale’s construct validity and reconfirm its reliability. We present a valid and reliable modular psychometric tool that measures general susceptibility to persuasive techniques. Since its inception, we have successfully implemented the StP-II scale to measure susceptibility to persuasion of IT security officers, the role of psychology of persuasion in cybercrime victims and general persuadability levels of Facebook users; these manuscripts are in preparation. We argue that the StP-II scale shows promise in measuring individual differences in susceptibility to persuasion, and is applicable across diverse contexts such as Internet security and cybercrime. [ABSTRACT FROM AUTHOR]

In recent years, major global institutions have amplified their efforts to address intimate partner violence (IPV) against women—a global health and human rights violation affecting 15–71% of reproductive aged women over their lifetimes. Still, some scholars remain concerned about the validity of instruments used for IPV assessment in population-based studies. In this paper, we conducted two validation analyses using novel data from 450 women-men dyads across nine villages in Northern Tanzania. , we examined the level of inter-partner agreement in reporting of men’s physical, sexual, emotional and economic IPV against women in the last three and twelve months prior to the survey, ever in the relationship, and during pregnancy. , we conducted a convergent validity analysis to compare the relative efficacy of men’s self-reports of perpetration and women’s of victimization as a valid indicator of IPV against Tanzanian women using logistic regression models with village-level clustered errors. We found that, for every violence type across the recall periods of the last three months, the last twelve months and ever in the relationship, at least one in three couples disagreed about IPV occurrences in the relationship. Couples’ agreement about physical, sexual and economic IPV during pregnancy was high with 86–93% of couples reporting concordantly. Also, men’s self-reported perpetration had statistically significant associations with at least as many validated risk factors as had women’s self-reported victimization. This finding suggests that men’s self-reports are at least as valid as women’s as an indicator of IPV against women in Northern Tanzania. We recommend more validation studies are conducted in low-income countries, and that data on relationship factors affecting IPV reports and reporting are made available along with data on IPV occurrences. Keywords: Intimate partner violence; measurement; validity; survey research; Tanzania. [ABSTRACT FROM AUTHOR]

Objective: To examine the use of the term ‘metric’ in health and social sciences’ literature, focusing on the interval scale implication of the term in Modern Test Theory (MTT). Materials and methods: A systematic search and review on MTT studies including ‘metric’ or ‘interval scale’ was performed in the health and social sciences literature. The search was restricted to 2001–2005 and 2011–2015. A Text Mining algorithm was employed to operationalize the eligibility criteria and to explore the uses of ‘metric’. The paradigm of each included article (Rasch Measurement Theory (RMT), Item Response Theory (IRT) or both), as well as its type (Theoretical, Methodological, Teaching, Application, Miscellaneous) were determined. An inductive thematic analysis on the first three types was performed. Results: 70.6% of the 1337 included articles were allocated to RMT, and 68.4% were application papers. Among the number of uses of ‘metric’, it was predominantly a synonym of ‘scale’; as adjective, it referred to measurement or quantification. Three incompatible themes ‘only RMT/all MTT/no MTT models can provide interval measures’ were identified, but ‘interval scale’ was considerably more mentioned in RMT than in IRT. Conclusion: ‘Metric’ is used in many different ways, and there is no consensus on which MTT metric has interval scale properties. Nevertheless, when using the term ‘metric’, the authors should specify the level of the metric being used (ordinal, ordered, interval, ratio), and justify why according to them the metric is at that level. [ABSTRACT FROM AUTHOR]

Demonstrability—the extent to which group members can recognize a correct solution to a problem—has a significant effect on group performance. However, the interplay between group size, demonstrability and performance is not well understood. This paper addresses these gaps by studying the joint effect of two factors—the difficulty of solving a problem and the difficulty of verifying the correctness of a solution—on the ability of groups of varying sizes to converge to correct solutions. Our empirical investigations use problem instances from different computational complexity classes, NP-Complete (NPC) and PSPACE-complete (PSC), that exhibit similar solution difficulty but differ in verification difficulty. Our study focuses on nominal groups to isolate the effect of problem complexity on performance. We show that NPC problems have higher demonstrability than PSC problems: participants were significantly more likely to recognize correct and incorrect solutions for NPC problems than for PSC problems. We further show that increasing the group size can actually decrease group performance for some problems of low demonstrability. We analytically derive the boundary that distinguishes these problems from others for which group performance monotonically improves with group size. These findings increase our understanding of the mechanisms that underlie group problem-solving processes, and can inform the design of systems and processes that would better facilitate collective decision-making. [ABSTRACT FROM AUTHOR]

An extended car-following model is proposed in this paper to analyze the impacts of V2V (vehicle to vehicle) communication on the micro driving behavior at the un-signalized intersection. A four-leg un-signalized intersection with twelve streams (left-turn, through movement, and right turn from each leg) is used. The effect of the guidance strategy on the reduction of the rate of stops and total delay is explored by comparing the proposed model and the traditional FVD car-following model. The numerical results illustrate that potential conflicts between vehicles can be predicted and some stops can be avoided by decelerating in advance. The driving comfort and traffic efficiency can be improved accordingly. More benefits could be obtained under the long communication range, low to medium traffic density, and simple traffic pattern conditions. [ABSTRACT FROM AUTHOR]

This paper reports the results of a lab experiment designed to study the role of observability for peer effects in the setting of a simple production task. In our experiment, participants in the role of workers engage in a team real-effort task. We vary whether they can observe, or be observed by, one of their co-workers. In contrast to earlier findings from the field, we find no evidence that low-productivity workers perform better when they are observed by high-productivity co-workers. Instead, our results imply that peer effects in our experiment are heterogeneous, with some workers reciprocating a high-productivity co-worker but others taking the opportunity to free ride. [ABSTRACT FROM AUTHOR]

The existence of a shared classification system is essential to knowledge production, transfer, and sharing. Studies of knowledge classification, however, rarely consider the fact that knowledge categories exist within hierarchical information systems designed to facilitate knowledge search and discovery. This neglect is problematic whenever information about categorical membership is itself used to evaluate the quality of the items that the category contains. The main objective of this paper is to show that the effects of category membership depend on the position that a category occupies in the hierarchical knowledge classification system of Wikipedia—an open knowledge production and sharing platform taking the form of a freely accessible on-line encyclopedia. Using data on all English-language Wikipedia articles, we examine how the position that a category occupies in the classification hierarchy affects the attention that articles in that category attract from Wikipedia editors, and their evaluation of quality of the Wikipedia articles. Specifically, we show that Wikipedia articles assigned to coarse-grained categories (i. e., categories that occupy higher positions in the hierarchical knowledge classification system) garner more attention from Wikipedia editors (i. e., attract a higher volume of text editing activity), but receive lower evaluations (i. e., they are considered to be of lower quality). The negative relation between attention and quality implied by this result is consistent with current theories of social categorization, but it also goes beyond available results by showing that the effects of categorization on evaluation depend on the position that a category occupies in a hierarchical knowledge classification system. [ABSTRACT FROM AUTHOR]

It is difficult to know whether different dimensions of trust have different effects on local residents’ acceptance of nuclear power plants (NPPs). In previous research such trust has been considered as a single dimensional concept. This paper divides trust into goodwill trust and competence trust, and we explore the ways in which trust affects acceptance of NPPs through structural equation modeling. A survey of 491 people was conducted in Haiyan County, China, where the Qinshan nuclear power plant is located. We find that goodwill trust is significantly correlated with competence trust, and each can indirectly promote residents’ acceptance of NPPs but by different paths. Goodwill trust improves acceptance of NPPs by decreasing risk perception, while competence trust improves acceptance of NPPs by increasing benefit perception. However, the associations between goodwill trust and benefit perception, competence trust and risk perception, are not significant. [ABSTRACT FROM AUTHOR]

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework. [ABSTRACT FROM AUTHOR]

Background: The population of Ghana is increasingly becoming urbanized with about 70% of the estimated 27 million people living in urban and peri-urban areas. Nonetheless, eight out of the ten regions in Ghana remain predominantly rural where only 32% of the national health sector workforce works. Moreover, the rural-urban disparities in the density of health tutors (staff responsible for pre-service training of health professionals) are enormous. This paper explores perceived needs of health tutors in rural and urban health training institutions in Ghana. Methods: This is a descriptive qualitative study conducted in the Greater Accra and Northern regions of Ghana. The Study used the deductive thematic and sub-thematic analysis approaches. Five health training institutions were randomly sampled, and 72 tutors engaged in separate focus group discussions with an average size of 14 participants per group in each training institution. Results: Perceived rural-urban disparities among health tutors were found in the payment of extra duty allowances; school infrastructure including libraries and internet connectivity; staff accommodation; and opportunities for scholarships and higher education. Health tutors in rural areas generally expressed more frustration with these work conditions than those in urban areas. Conclusions: There is the need to initiate and sustain work incentives that promote motivation of rural health tutors to control ongoing rural-urban migration of qualified staff. It is recommended the following incentives be prioritized to promote retention of qualified health tutors in rural health training schools: payment of research, book and rural allowances; early promotion of rural staff; prioritizing rural tutors for scholarships, and introduction of national best health tutor awards. [ABSTRACT FROM AUTHOR]

For the past 50 years, acknowledgments have been studied as important paratextual traces of research practices, collaboration, and infrastructure in science. Since 2008, funding acknowledgments have been indexed by Web of Science, supporting large-scale analyses of research funding. Applying advanced linguistic methods as well as Correspondence Analysis to more than one million acknowledgments from research articles and reviews published in 2015, this paper aims to go beyond funding disclosure and study the main types of contributions found in acknowledgments on a large scale and through disciplinary comparisons. Our analysis shows that technical support is more frequently acknowledged by scholars in Chemistry, Physics and Engineering. Earth and Space, Professional Fields, and Social Sciences are more likely to acknowledge contributions from colleagues, editors, and reviewers, while Biology acknowledgments put more emphasis on logistics and fieldwork-related tasks. Conflicts of interest disclosures (or lack of thereof) are more frequently found in acknowledgments from Clinical Medicine, Health and, to a lesser extent, Psychology. These results demonstrate that acknowledgment practices truly do vary across disciplines and that this can lead to important further research beyond the sole interest in funding. [ABSTRACT FROM AUTHOR]

Introduction: Inconsistency in the time trade-off (TTO) task in EQ-5D-5L occurs when a respondent gives a higher value to a logically worse health state, the occurrence of inconsistency compromises the quality of the data. It is not yet clear which factors are associated with individual level inconsistency. Relating inconsistency to the characteristics of the respondent, interviewer, and the interview process could be helpful in understanding the causes of inconsistency. The objective of this paper is to discover the factors associated with individual level inconsistencies. Methods: Twenty interviewers interviewed 1,296 respondents and each respondent valued 10 health states using the EQ-VT platform in 5 cities in China. At the respondent level, inconsistency was identified in terms of severity and quantity and related to the respondent’s background characteristics, the time and iterations spent on the wheelchair example task, and the formal TTO tasks, using multilevel multinomial regression analyses. Interviewers’ impact on inconsistencies was analyzed using single level multinomial regression analyses. Results: In the full dataset, slight inconsistency was more related to the interview process (Time spent on TTO task: RRR = 1.246 with 95%CI: 1.076,1.441; time spent on Wheelchair example: RRR = 0.815 with 95%CI:0.699,0.952) while severe inconsistency was more related to respondent’s gender (Gender: RRR = 2.347 with 95%CI:1.429,3.855). One Interviewer (Interviewer 7: RRR = 7.335 with 95%CI:1.908,28.195) and interviewer’s experience (Sequence: RRR = 0.511 with 95%CI:0.385,0.678) in general showed strong influence over inconsistency in the TTO task. Conclusion: In conclusion, logical inconsistency in the valuation of EQ-5D-5L health states is associated not only with respondents’ characteristics but also with interviewers’ performance and the interview process. The role of interviewers and the importance of interviewer training may be more crucial than hitherto believed. This finding could be generalizable to other interviewer-administered health-state valuation study. [ABSTRACT FROM AUTHOR]

In the animal world, various kinds of collective motions have been found and proven to be efficient ways of carrying out some activities such as searching for food and avoiding predators. Many scholars research the interactions of collective behaviors of human beings according to the rules of collective behaviors of animals. Based on the Lennard-Jones potential function and a self-organization process, our paper proposes a topological communication model to simulate the collective behaviors of human beings. In the results of simulations, we find various types of collective behavior and fission behavior and discover the threshold for the emergence of collective behavior, which is the range five to seven for the number of topology K. According to the analysis of network properties of the model, the in-degree of individuals is always equal to the number of topology. In the stable state, the out-degrees of individuals distribute around the value of the number of topology K, except that the out-degree of a single individual is approximately double the out-degrees of the other individuals. In addition, under different initial conditions, some features of different kinds of networks emerge from the model. We also find the leader and herd mentality effects in the characteristics of the behaviors of human beings in our model. Thus, this work could be used to discover how to promote the emergence of beneficial group behaviors and prevent the emergence of harmful behaviors. [ABSTRACT FROM AUTHOR]

This paper explores how information flow properties of a network affect the formation of categories shared between individuals, who are communicating through that network. Our work is based on the established multi-agent model of the emergence of linguistic categories grounded in external environment. We study how network information propagation efficiency and the direction of information flow affect categorization by performing simulations with idealized network topologies optimizing certain network centrality measures. We measure dynamic social adaptation when either network topology or environment is subject to change during the experiment, and the system has to adapt to new conditions. We find that both decentralized network topology efficient in information propagation and the presence of central authority (information flow from the center to peripheries) are beneficial for the formation of global agreement between agents. Systems with central authority cope well with network topology change, but are less robust in the case of environment change. These findings help to understand which network properties affect processes of social adaptation. They are important to inform the debate on the advantages and disadvantages of centralized systems. [ABSTRACT FROM AUTHOR]

Traffic congestion continues to be a persistent problem throughout the world. As vehicle-to-vehicle communication develops, there is an opportunity of using cooperation among close proximity vehicles to tackle the congestion problem. The intuition is that if vehicles could cooperate opportunistically when they come close enough to each other, they could, in effect, spread themselves out among alternative routes so that vehicles do not all jam up on the same roads. Our previous work proposed a decentralized multiagent based vehicular congestion management algorithm entitled Congestion Avoidance and Route Allocation using Virtual Agent Negotiation (CARAVAN), wherein the vehicles acting as intelligent agents perform cooperative route allocation using inter-vehicular communication. This paper focuses on evaluating the practical applicability of this approach by testing its robustness and performance (in terms of travel time reduction), across variations in: (a) environmental parameters such as road network topology and configuration; (b) algorithmic parameters such as vehicle agent preferences and route cost/preference multipliers; and (c) agent-related parameters such as equipped/non-equipped vehicles and compliant/non-compliant agents. Overall, the results demonstrate the adaptability and robustness of the decentralized cooperative vehicles approach to providing global travel time reduction using simple local coordination strategies. [ABSTRACT FROM AUTHOR]

Introduction: This research paper aims to assess factors reported by parents associated with the successful transition of children with complex additional support requirements that have undergone a transition between school environments from 8 European Union member states. Methods: Quantitative data were collected from 306 parents within education systems from 8 EU member states (Bulgaria, Cyprus, Greece, Ireland, the Netherlands, Romania, Spain and the UK). The data were derived from an online questionnaire and consisted of 41 questions. Information was collected on: parental involvement in their child’s transition, child involvement in transition, child autonomy, school ethos, professionals’ involvement in transition and integrated working, such as, joint assessment, cooperation and coordination between agencies. Survey questions that were designed on a Likert-scale were included in the Principal Components Analysis (PCA), additional survey questions, along with the results from the PCA, were used to build a logistic regression model. Results: Four principal components were identified accounting for 48.86% of the variability in the data. Principal component 1 (PC1), ‘child inclusive ethos,’ contains 16.17% of the variation. Principal component 2 (PC2), which represents child autonomy and involvement, is responsible for 8.52% of the total variation. Principal component 3 (PC3) contains questions relating to parental involvement and contributed to 12.26% of the overall variation. Principal component 4 (PC4), which involves transition planning and coordination, contributed to 11.91% of the overall variation. Finally, the principal components were included in a logistic regression to evaluate the relationship between inclusion and a successful transition, as well as whether other factors that may have influenced transition. All four principal components were significantly associated with a successful transition, with PC1 being having the most effect (OR: 4.04, CI: 2.43–7.18, p<0.0001). Discussion: To support a child with complex additional support requirements through transition from special school to mainstream, governments and professionals need to ensure children with additional support requirements and their parents are at the centre of all decisions that affect them. It is important that professionals recognise the educational, psychological, social and cultural contexts of a child with additional support requirements and their families which will provide a holistic approach and remove barriers for learning. [ABSTRACT FROM AUTHOR]

A 2007 study by Regier, Kay, and Khetarpal purports to show that universal categories emerge as a result of optimal partitioning of color space. Regier, Kay, and Khetarpal only consider color categorizations of up to six categories. However, in most industrialized societies eleven color categories are observed. This paper shows that when applied to the case of eleven categories, Regier, Kay, and Khetarpal’s optimality criterion yields unsatisfactory results. Applications of the criterion to the intermediate cases of seven, eight, nine, and ten color categories are also briefly considered and are shown to yield mixed results. We consider a number of possible explanations of the failure of the criterion in the case of eleven categories, and suggest that, as color categorizations get more complex, further criteria come to play a role, alongside Regier, Kay, and Khetarpal’s optimality criterion. [ABSTRACT FROM AUTHOR]

Remote Internet voting places the control and secrecy of the immediate voting environment on the shoulder of the individual voter but it also turns voting into yet another on-line activity thus endangering the well-known social nature of voting and possibly reducing the crucial sense of civic duty that is important for a healthy democracy. There is however a complete lack of evidence to what degree this actually materializes once electronic voting is introduced. This paper uses individual level log data on Internet voting in Estonian elections between 2013–2015 to inspect if Internet voting retains the social nature of the voting act. We do so by examining if Internet voting in groups takes place and what implications it has for voting speed. We find strong evidence of e-voting in pairs. Same aged male-female pairs seem to be voting in close proximity to each other, consistent with spouses or partners voting together. Also, female-female and female-male pairs with large age differences seem to be voting together, consistent with a parent voting with an adult aged offspring. With regards to voting speed we see the second vote in a vote pair being considerably faster than the first vote, again indicating a shared voting act. We end with a discussion of how the onset of electronic voting does not make elections less social, but does make vote secrecy more a choice rather than a requirement. [ABSTRACT FROM AUTHOR]

A popular objective criterion for partitioning a set of actors into core and periphery subsets is the maximization of the correlation between an ideal and observed structure associated with intra-core and intra-periphery ties. The resulting optimization problem has commonly been tackled using heuristic procedures such as relocation algorithms, genetic algorithms, and simulated annealing. In this paper, we present a computationally efficient simulated annealing algorithm for maximum correlation core/periphery partitioning of binary networks. The algorithm is evaluated using simulated networks consisting of up to 2000 actors and spanning a variety of densities for the intra-core, intra-periphery, and inter-core-periphery components of the network. Core/periphery analyses of problem solving, trust, and information sharing networks for the frontline employees and managers of a consumer packaged goods manufacturer are provided to illustrate the use of the model. [ABSTRACT FROM AUTHOR]

People reliably encode information more effectively when it is related in some way to the self—a phenomenon known as the self-reference effect. This effect has been recognized in psychological research for almost 40 years, and its scope as a tool for investigating the self-concept is still expanding. The self-reference effect has been used within a broad range of psychological research, from cultural to neuroscientific, cognitive to clinical. Traditionally, the self-reference effect has been investigated in a laboratory context, which limits its applicability in non-laboratory samples. This paper introduces an online version of the self-referential encoding paradigm that yields reliable effects in an easy-to-administer procedure. Across four studies (total N = 658), this new online tool reliably replicated the traditional self-reference effect: in all studies self-referentially encoded words were recalled significantly more than semantically encoded words (d = 0.63). Moreover, the effect sizes obtained with this online tool are similar to those obtained in laboratory samples, and are robust to experimental variations in encoding time (Studies 1 and 2) and recall procedure (Studies 3 and 4), and persist independent of primacy and recency effects (all studies). [ABSTRACT FROM AUTHOR]

Labeling theory suggests that criminal justice interventions amplify offending behavior. Theories of intergenerational transmission suggest why children of convicted parents have a higher risk of offending. This paper combines these two perspectives and investigates whether labeling effects might be stronger for children of convicted parents. We first investigated labeling effects within the individual: we examined the impact of a conviction between ages 19–26 on self-reported offending behavior between 27–32 while controlling for self-reported behavior between 15–18. Our results show that a conviction predicted someone’s later self-reported offending behavior, even when previous offending behavior was taken into account. Second, we investigated whether having a convicted parent influenced this association. When we added this interaction to the analysis, a labeling effect was only visible among people with convicted parents. This supports the idea of cumulative disadvantage: Labeling seems stronger for people who are already in a disadvantaged situation having a convicted parent. [ABSTRACT FROM AUTHOR]

Multi-stakeholder platforms (MSPs) are seen as a promising vehicle to achieve agricultural development impacts. By increasing collaboration, exchange of knowledge and influence mediation among farmers, researchers and other stakeholders, MSPs supposedly enhance their ‘capacity to innovate’ and contribute to the ‘scaling of innovations’. The objective of this paper is to explore the capacity to innovate and scaling potential of three MSPs in Burundi, Rwanda and the South Kivu province located in the eastern part of Democratic Republic of Congo (DRC). In order to do this, we apply Social Network Analysis and Exponential Random Graph Modelling (ERGM) to investigate the structural properties of the collaborative, knowledge exchange and influence networks of these MSPs and compared them against value propositions derived from the innovation network literature. Results demonstrate a number of mismatches between collaboration, knowledge exchange and influence networks for effective innovation and scaling processes in all three countries: NGOs and private sector are respectively over- and under-represented in the MSP networks. Linkages between local and higher levels are weak, and influential organisations (e.g., high-level government actors) are often not part of the MSP or are not actively linked to by other organisations. Organisations with a central position in the knowledge network are more sought out for collaboration. The scaling of innovations is primarily between the same type of organisations across different administrative levels, but not between different types of organisations. The results illustrate the potential of Social Network Analysis and ERGMs to identify the strengths and limitations of MSPs in terms of achieving development impacts. [ABSTRACT FROM AUTHOR]

The purpose of this paper is twofold: to validate the properties of the Italian version of the Baller Identity Measurement Scale (i.e., BIMS-IT), a self-report questionnaire based on the athletic and academic identities; and to investigate differences in psychosocial factors such as gender, age, type of sport, and competition level. The dimensionality of the BIMS-IT was explored by means of the exploratory factor analysis, considering the scale’s internal consistency too (Confirmatory Factor Analysis). Results related to exploratory and confirmatory factor analysis supported a model of measurement composed of two correlated factors: the athletic and academic identities and affectivity related to identities. For both factors, differences emerged between age, and competition level sub groups. In particular, higher identity scores emerged for ≤ 24 years old student-athletes with respect to their age counterparts. National sub-elite student-athletes reported lower identity values than those of national elite and international levels. Results suggest that the Italian version of the BIMS-IT is psychometrically robust and could be adopted for empirical uses. The higher identity scores reported by younger and higher competition level participants suggest a correspondent higher involvement into the student-athlete role. However, BIMS-IT represents a distinct model with respect to the original American BIMS, determining the need of further research on the student-athletes’ identity to better clarify any socio-cultural contest effects. [ABSTRACT FROM AUTHOR]

Background: Poor menstrual knowledge and access to sanitary products have been proposed as barriers to menstrual health and school attendance. In response, interventions targeting these needs have seen increasing implementation in public and private sectors. However, there has been limited assessment of their effectiveness. Objectives: Assess the impact of providing reusable sanitary pads and puberty education on girls’ school attendance and psychosocial wellbeing outcomes. Methods: A cluster quasi-randomised controlled trial was conducted across 8 schools, including 1124 girls, in rural Uganda. Schools were allocated to one of four conditions: the provision of puberty education alone; reusable sanitary pads alone; puberty education and reusable sanitary pads; and a control (no intervention). The primary outcome was school attendance. Secondary outcomes reflected psychosocial wellbeing. Results: At follow-up, school attendance had worsened for girls across all conditions. Per-protocol analysis revealed that this decline was significantly greater for those in the control condition d = 0.52 (95%CI 0.26–0.77), with those in control schools having a 17.1% (95%CI: 8.7–25.5) greater drop in attendance than those in any intervention school. There were no differences between the intervention conditions. High rates of school drop-out and transfer meant the trial suffered from substantial participant drop-out. Intention-to-treat analyses using two different imputation strategies were consistent with the main results, with mean differences of 5.2% attendance in best-case and 24.5% in worst-case imputations. Results were robust to adjustments for clustering. There was no impact of the interventions on girls’ self-reported shame or insecurity during menstruation. Conclusion: Results of the trial support the hypothesised positive impact of providing sanitary pads or puberty education for girls’ school attendance in a developing country context. Findings must be interpreted with caution in light of poor participant retention, intervention fidelity, and the attendance measures used. Trial Registration: Pan African Clinical Trials Registry [ABSTRACT FROM AUTHOR]

This paper investigates how social influence can alter physiological, psychological, and functional responses to a placebo product and how such responses influence the ultimate endorsement of the product. Participants consumed a product, “AquaCharge Energy Water,” falsely-labeled as containing 200 mg of caffeine but which was actually plain spring water, in one of three conditions: a no social influence condition, a disconfirming social influence condition, and a confirming social influence condition. Results demonstrated that the effect of the product labeling on physiological alertness (systolic blood pressure), psychological alertness (self-reported alertness), functional alertness (cognitive interference), and product endorsement was moderated by social influence: participants experienced more subjective, physiological and functional alertness and stronger product endorsement when they consumed the product in the confirming social influence condition than when they consumed the product in the disconfirming social influence condition. These results suggest that social influence can alter subjective, physiological, and functional responses to a faux product, in this case transforming the effects of plain water. [ABSTRACT FROM AUTHOR]

Melioration learning is an empirically well-grounded model of reinforcement learning. By means of computer simulations, this paper derives predictions for several repeatedly played two-person games from this model. The results indicate a likely convergence to a pure Nash equilibrium of the game. If no pure equilibrium exists, the relative frequencies of choice may approach the predictions of the mixed Nash equilibrium. Yet in some games, no stable state is reached. [ABSTRACT FROM AUTHOR]

How to understand individual human actions is a fundamental question to modern science, which drives and incurs many social, technological, racial, religious and economic phenomena. Human dynamics tries to reveal the temporal pattern and internal mechanism of human actions in letter or electronic communications, from the perspective of continuous interactions among friends or acquaintances. For interactions between stranger to stranger, taxi industry provide fruitful phenomina and evidence to investigate the action decisions. In fact, one striking disturbing events commonly reported in taxi industry is passenger refusing or denial, whose reasons vary, including skin color, blind passenger, being a foreigner or too close destination, religion reasons and anti specific nationality, so that complaints about taxi passenger refusing have to be concerned and processed carefully by local governments. But more universal factors for this phenomena are of great significance, which might be fulfilled by big data research to obtain novel insights in this question. In this paper, we demonstrate the big data analytics application in revealing novel insights from massive taxi trace data, which, for the first time, validates the passengers denial in taxi industry and estimates the denial ratio in Beijing city. We first quantify the income differentiation facts among taxi drivers. Then we find out that choosing the drop-off places also contributes to the high income for taxi drivers, compared to the previous explanation of mobility intelligence. Moreover, we propose the pick-up, drop-off and grid diversity concepts and related diversity analysis suggest that, high income taxi drivers will deny passengers in some situations, so as to choose the passengers’ destination they prefer. Finally we design an estimation method for denial ratio and infer that high income taxi drivers will deny passengers with 8.52% likelihood in Beijing. Our work exhibits the power of big data analysis in revealing some dark side investigation. [ABSTRACT FROM AUTHOR]

This paper advances theories of social learning through an empirical examination of how social networks change over time. Social networks are important for learning because they constrain individuals’ access to information about the behaviors and cognitions of other people. Using data on a large social network of mobile device users over a one-month time period, we test three hypotheses: 1) attraction homophily causes individuals to form ties on the basis of attribute similarity, 2) aversion homophily causes individuals to delete existing ties on the basis of attribute dissimilarity, and 3) social influence causes individuals to adopt the attributes of others they share direct ties with. Statistical models offer varied degrees of support for all three hypotheses and show that these mechanisms are more complex than assumed in prior work. Although homophily is normally thought of as a process of attraction, people also avoid relationships with others who are different. These mechanisms have distinct effects on network structure. While social influence does help explain behavior, people tend to follow global trends more than they follow their friends. [ABSTRACT FROM AUTHOR]

Background: Online broadcasting substantially affects the production, distribution, and profit of TV series. In addition, online word-of-mouth significantly affects the diffusion of TV series. Because on-demand streaming rates are the most important factor that influences the earnings of online video suppliers, streaming statistics and forecasting trends are valuable. In this paper, we investigate the effects of periodic impulsive stimulation and pre-launch promotion on on-demand streaming dynamics. We consider imbalanced audience feverish distribution using an impulsive susceptible-infected-removed(SIR)-like model. In addition, we perform a correlation analysis of online buzz volume based on Baidu Index data. Methods: We propose a PI-SIR model to evolve audience dynamics and translate them into on-demand streaming fluctuations, which can be observed and comprehended by online video suppliers. Six South Korean TV series datasets are used to test the model. We develop a coarse-to-fine two-step fitting scheme to estimate the model parameters, first by fitting inter-period accumulation and then by fitting inner-period feverish distribution. Results: We find that audience members display similar viewing habits. That is, they seek new episodes every update day but fade away. This outcome means that impulsive intensity plays a crucial role in on-demand streaming diffusion. In addition, the initial audience size and online buzz are significant factors. On-demand streaming fluctuation is highly correlated with online buzz fluctuation. Conclusion: To stimulate audience attention and interpersonal diffusion, it is worthwhile to invest in promotion near update days. Strong pre-launch promotion is also a good marketing tool to improve overall performance. It is not advisable for online video providers to promote several popular TV series on the same update day. Inter-period accumulation is a feasible forecasting tool to predict the future trend of the on-demand streaming amount. The buzz in public social communities also represents a highly correlated analysis tool to evaluate the advertising value of TV series. [ABSTRACT FROM AUTHOR]

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users’ location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users’ location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users’ location information profiles and used generalization and encryption to ensure the safety of the user’s location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user’s location privacy. [ABSTRACT FROM AUTHOR]

Product aspect recognition is a key task in fine-grained opinion mining. Current methods primarily focus on the extraction of aspects from the product reviews. However, it is also important to cluster synonymous extracted aspects into the same category. In this paper, we focus on the problem of product aspect clustering. The primary challenge is to properly cluster and generalize aspects that have similar meanings but different representations. To address this problem, we learn two types of background knowledge for each extracted aspect based on two types of effective aspect relations: relevant aspect relations and irrelevant aspect relations, which describe two different types of relationships between two aspects. Based on these two types of relationships, we can assign many relevant and irrelevant aspects into two different sets as the background knowledge to describe each product aspect. To obtain abundant background knowledge for each product aspect, we can enrich the available information with background knowledge from the Web. Then, we design a hierarchical clustering algorithm to cluster these aspects into different groups, in which aspect similarity is computed using the relevant and irrelevant aspect sets for each product aspect. Experimental results obtained in both camera and mobile phone domains demonstrate that the proposed product aspect clustering method based on two types of background knowledge performs better than the baseline approach without the use of background knowledge. Moreover, the experimental results also indicate that expanding the available background knowledge using the Web is feasible. [ABSTRACT FROM AUTHOR]

Cooperation amongst resource users holds the key to overcoming the social dilemma that characterizes community-based common-pool resource management. But is cooperation alone enough to achieve sustainable resource use? The short answer is no. Developing management strategies in a complex social-ecological environment also requires ecological knowledge and approaches to deal with perceived environmental uncertainty. Recent behavioral experimental research indicates variation in the degree to which a group of users can identify a sustainable exploitation level. In this paper, we identify social-ecological micro-foundations that facilitate cooperative sustainable common-pool resource use. We do so by using an agent-based model (ABM) that is informed by behavioral common-pool resource experiments. In these experiments, groups that cooperate do not necessarily manage the resource sustainably, but also over- or underexploit. By reproducing the patterns of the behavioral experiments in a qualitative way, the ABM represents a social-ecological explanation for the experimental observations. We find that the ecological knowledge of each group member cannot sufficiently explain the relationship between cooperation and sustainable resource use. Instead, the development of a sustainable exploitation level depends on the distribution of ecological knowledge among the group members, their influence on each other’s knowledge, and the environmental uncertainty the individuals perceive. The study provides insights about critical social-ecological micro-foundations underpinning collective action and sustainable resource management. These insights may inform policy-making, but also point to future research needs regarding the mechanisms of social learning, the development of shared management strategies and the interplay of social and ecological uncertainty. [ABSTRACT FROM AUTHOR]

Recently, increasing numbers of users have adopted microblogging services as their main information source. However, most of them find themselves drowning in the millions of posts produced by other users every day. To cope with this, identifying a set of the most influential people is paramount. Moreover, finding a set of related influential users to expand the coverage of one particular topic is required in real world scenarios. Most of the existing algorithms in this area focus on topology-related methods such as PageRank. These methods mine link structures to find the expected influential rank of users. However, because they ignore the interaction data, these methods turn out to be less effective in social networks. In reality, a variety of topics exist within the information diffusing through the network. Because they have different interests, users play different roles in the diffusion of information related to different topics. As a result, distinguishing influential leaders according to different topics is also worthy of research. In this paper, we propose a multi-topic influence diffusion model (MTID) based on traces acquired from historic information. We decompose the influential scores of users into two parts: the direct influence determined by information propagation along the link structure and indirect influence that extends beyond the restrictions of direct follower relationships. To model the network from a multi-topical viewpoint, we introduce topic pools, each of which represents a particular topic information source. Then, we extract the topic distributions from the traces of tweets, determining the influence propagation probability and content generation probability. In the network, we adopt multiple ground nodes representing topic pools to connect every user through bidirectional links. Based on this multi-topical view of the network, we further introduce the topic-dependent rank (TD-Rank) algorithm to identify the multi-topic influential users. Our algorithm not only effectively overcomes the shortages of PageRank but also effectively produces a measure of topic-related rank. Extensive experiments on a Weibo dataset show that our model is both effective and robust. [ABSTRACT FROM AUTHOR]

Social media analysis has shown tremendous potential to understand public's opinion on a wide variety of topics. In this paper, we have mined Twitter to understand the public's perception of the Internet of Things (IoT). We first generated the discussion trends of the IoT from multiple Twitter data sources and validated these trends with Google Trends. We then performed sentiment analysis to gain insights of the public’s attitude towards the IoT. As anticipated, our analysis indicates that the public's perception of the IoT is predominantly positive. Further, through topic modeling, we learned that public tweets discussing the IoT were often focused on business and technology. However, the public has great concerns about privacy and security issues toward the IoT based on the frequent appearance of related terms. Nevertheless, no unexpected perceptions were identified through our analysis. Our analysis was challenged by the limited fraction of tweets relevant to our study. Also, the user demographics of Twitter users may not be strongly representative of the population of the general public. [ABSTRACT FROM AUTHOR]

Human social interaction is often intermittent. Two acquainted persons can have extended periods without social interaction punctuated by periods of repeated interaction. In this case, the repeated interaction can be characterized by a seed initiative by either of the persons and a number of follow-up interactions. The tendency to initiate social interaction plays an important role in the formation of social networks and is in general not symmetric between persons. In this paper, we study the dynamics of initiative by analysing and modeling a detailed call and text message network sampled from a group of 700 individuals. We show that in an average relationship between two individuals, one part is almost twice as likely to initiate communication compared to the other part. The asymmetry has social consequences and ultimately might lead to the discontinuation of a relationship. We explain the observed asymmetry by a positive feedback mechanism where individuals already taking initiative are more likely to take initiative in the future. In general, people with many initiatives receive attention from a broader spectrum of friends than people with few initiatives. Lastly, we compare the likelihood of taking initiative with the basic personality traits of the five factor model. [ABSTRACT FROM AUTHOR]

The problem of link prediction has recently received increasing attention from scholars in network science. In social network analysis, one of its aims is to recover missing links, namely connections among actors which are likely to exist but have not been reported because data are incomplete or subject to various types of uncertainty. In the field of criminal investigations, problems of incomplete information are encountered almost by definition, given the obvious anti-detection strategies set up by criminals and the limited investigative resources. In this paper, we work on a specific dataset obtained from a real investigation, and we propose a strategy to identify missing links in a criminal network on the basis of the topological analysis of the links classified as marginal, i.e. removed during the investigation procedure. The main assumption is that missing links should have opposite features with respect to marginal ones. Measures of node similarity turn out to provide the best characterization in this sense. The inspection of the judicial source documents confirms that the predicted links, in most instances, do relate actors with large likelihood of co-participation in illicit activities. [ABSTRACT FROM AUTHOR]

In a connected world where people influence each other, what can cause a globalized monoculture, and which measures help to preserve the coexistence of cultures? Previous research has shown that factors such as homophily, population size, geography, mass media, and type of social influence play important roles. In the present paper, we investigate for the first time the impact that institutions have on cultural diversity. In our first three studies, we extend existing agent-based models and explore the effects of institutional influence and agent loyalty. We find that higher institutional influence increases cultural diversity, while individuals' loyalty to their institutions has a small, preserving effect. In three further studies, we test how bottom-up and top-down processes of institutional influence impact our model. We find that bottom-up democratic practices, such as referenda, tend to produce convergence towards homogeneity, while top-down information dissemination practices, such as propaganda, further increase diversity. In our last model—an integration of bottom-up and top-down processes into a feedback loop of information—we find that when democratic processes are rare, the effects of propaganda are amplified, i.e., more diversity emerges; however, when democratic processes are common, they are able to neutralize or reverse this propaganda effect. Importantly, our models allow for control over the full spectrum of diversity, so that a manipulation of our parameters can result in preferred levels of diversity, which will be useful for the study of other factors in the future. We discuss possible mechanisms behind our results, applications, and implications for political and social sciences. [ABSTRACT FROM AUTHOR]

In this paper, we have captured an underlying mechanism of emergence of collective panic in pedestrian evacuations by using a modification of the lattice-gas model. We classify the motion of pedestrians into two modes according to their moods. One is gentle (mode I), the other is flustered (mode II). First, to research the cause for crowd, we fix the motion modes of pedestrians and increase the proportion of pedestrians with motion mode II (ρII). The simulation results show that the pedestrians with motion mode II are lack of evacuation efficiency and cause more casualties. Further, we use the SIS (susceptible-infective-susceptible) model to describe the spreading of the panic mood. The system can be in the high-mix state when the infection probability λ is greater than a fuzzy threshold. In addition, the distances S from wounded people to the exit are researched, the number of wounded people gets maximum at the internal S = 5 ∼ 10, which is independent of ρII and λ. This research can help us to understand and prevent the emergence of collective panic and reduce wounds in the real evacuation. [ABSTRACT FROM AUTHOR]

Thanks to the work of politics and religion scholars, we now know a lot about the relationship between religion and voting in American presidential general elections. However, we know less about the influence of religion on individual vote choice in presidential primaries. This article fills that gap by exploring the relationship between religion and candidate preference in the 2008 and 2012 Republican primaries. Using pre-Super Tuesday surveys conducted by the Pew Research Center, I find that the Republican candidate who most explicitly appealed to religious voters (Mike Huckabee in 2008 and Rick Santorum in 2012) was the preferred candidate of Republican respondents who attended religious services at the highest levels, and that as attendance increased, so did the likelihood of preferring that candidate. I also find that identification as a born again Christian mattered to candidate preference. Specifically, born again Christians were more likely than non-born again Christians to prefer Huckabee to Mitt Romney, John McCain and Ron Paul in 2008, and Santorum to Romney in 2012. Although ideology was not the primary subject of this article, I find that ideology was also a statistically significant predictor of Republican candidate preference in both 2008 and 2012. This robust finding reinforces scholars’ prior work on the importance of ideology in explaining presidential primary vote choice. The overall findings of the paper provide evidence that religion variables can add to our understanding of why voters prefer one candidate over another in presidential primaries. [ABSTRACT FROM AUTHOR]

People divide their time unequally among their social contacts due to time constraints and varying strength of relationships. It was found that high diversity of social communication, dividing time more evenly among social contacts, is correlated with economic well-being both at macro and micro levels. Besides economic well-being, it is not clear how the diversity of social communication is also associated with the two components of individuals’ subjective well-being, positive and negative affect. Specifically, positive affect and negative affect are two independent dimensions representing the experience (feeling) of emotions. In this paper, we investigate the relationship between the daily diversity of social communication and dynamic affect states that people experience in their daily lives. We collected two high-resolution datasets that capture affect scores via daily experience sampling surveys and social interaction through wearable sensing technologies: sociometric badges for face-to-face interaction and smart phones for mobile phone calls. We found that communication diversity correlates with desirable affect states–e.g. an increase in the positive affect state or a decrease in the negative affect state–for some personality types, but correlates with undesirable affect states for others. For example, diversity in phone calls is experienced as good by introverts, but bad by extroverts; diversity in face-to-face interaction is experienced as good by people who tend to be positive by nature (trait) but bad for people who tend to be not positive by nature. More broadly, the moderating effect of personality type on the relationship between diversity and affect was detected without any knowledge of the type of social tie or the content of communication. This provides further support for the power of unobtrusive sensing in understanding social dynamics, and in measuring the effect of potential interventions designed to improve well-being. [ABSTRACT FROM AUTHOR]

Emotion entrainment, which is generally defined as the synchronous convergence of human emotions, performs many important social functions. However, what the specific mechanisms of emotion entrainment are beyond in-person interactions, and how human emotions evolve under different entrainment patterns in large-scale social communities, are still unknown. In this paper, we aim to examine the massive emotion entrainment patterns and understand the underlying mechanisms in the context of social media. As modeling emotion dynamics on a large scale is often challenging, we elaborate a pragmatic framework to characterize and quantify the entrainment phenomenon. By applying this framework on the datasets from two large-scale social media platforms, we find that the emotions of online users entrain through social networks. We further uncover that online users often form their relations via dual entrainment, while maintain it through single entrainment. Remarkably, the emotions of online users are more convergent in nonreciprocal entrainment. Building on these findings, we develop an entrainment augmented model for emotion prediction. Experimental results suggest that entrainment patterns inform emotion proximity in dyads, and encoding their associations promotes emotion prediction. This work can further help us to understand the underlying dynamic process of large-scale online interactions and make more reasonable decisions regarding emergency situations, epidemic diseases, and political campaigns in cyberspace. [ABSTRACT FROM AUTHOR]

Sports fans are able to watch games from many locations using TV services while interacting with other fans online. In this paper, we identify the factors that affect sports viewers’ online interactions. Using a large-scale dataset of more than 25 million chat messages from a popular social TV site for baseball, we extract various game-related factors, and investigate the relationships between these factors and fans’ interactions using a series of multiple regression analyses. As a result, we identify several factors that are significantly related to viewer interactions. In addition, we determine that the influence of these factors varies according to the user group; i.e., active vs. less active users, and loyal vs. non-loyal users. [ABSTRACT FROM AUTHOR]

Based on our site investigation conducted in 2013, we found that the pedestrian red light crossing at the midblock connecting the campus of Southwest University and living area was low, where most of pedestrians are university students and staff. This paper reports a supplementary work applying the Theory of Planned Behaviour (TPB) to identify any psychological differences toward pedestrian red light crossing between university students and their peers. Three social groups participated in the investigation. The first group is the university students in Grade one (Group 1), the other two groups are their previous senior middle school classmates who are now working full time (Group 2) or who are now out of work and school (Group 3). The statistical results indicated The TPB components accounted for 42.9%, 55.3% and 55.4% of the variance of red signal crossing intention for Group 1, Group 2 and Group 3 in the depicted road crossing scenario. The data also showed that there are obvious differences among the participants’ responses to “refrain from crossing” between university students and others, and the subsequent regression analysis revealed the ability to “refrain from crossing” played the most important role in the intention of red light crossing in the depicted scenario. [ABSTRACT FROM AUTHOR]