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

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

Automatic analysis and identification of verbal aggression and abusive behaviors for online social games

Online multiplayer games create new social platforms, with their own etiquette, social rules of conduct and ways of expression. What counts as aggressive and abusing behavior may change depending on the platform, but most online gaming companies need to deal with aggressive and abusive players explicitly. This usually is tied to a reporting mechanism where the offended player reports an offense. In this paper, we develop tools for validating whether a verbal aggression offense report refers to a real offense or not, in the context of a very popular online social game, called Okey. Our approach relies on the analysis of player behavior and characteristics of offending players. In the proposed system, chat records and other social activities in the game are taken into account, as well as player history. This methodology is sufficiently generic, and it can be applied to similar gaming platforms, thus describing a useful tool for game companies. We report our results on data collected over a six months period, involving 100,000 users and 800,000 game records, and illustrate the viability of such analysis, while providing insights on the factors associated with verbal aggression and abusive behavior for social games.     

Enhancing non-task sociability of asynchronous CSCL environments

While from a technological perspective Computer Supported Collaborative Learning (CSCL) systems have been improved considerably, previous studies have shown that the social aspect of the CSCL is often neglected or assumed to happen automatically by simply creating such virtual learning environments. By distinguishing between students’ non-task social interactions from on-task interactions, and through a content analysis, this paper demonstrates that non-task interactions do occur frequently in CSCL environments. Furthermore, by conducting a self-reported survey, the present study operationalizes non-task sociability of CSCL environments and determines factors that affect them. The findings from the survey revealed that the sense of cohesion and awareness about others significantly impact the non-task sociability of CSCL. Furthermore, the study demonstrates that the perception of self-representation and perception of compatibility affect the sense of cohesion and awareness about others and indirectly contribute to the perceived non-pedagogical sociability of the environment. The findings of this paper can be used in future research for investigating the relationship between the non-task sociability of CSCL and other CSCL factors. The study also provides the CSCL lecturers and facilitators with a conceptual model by which sociability can be explicitly addressed in their course planning and delivery processes. And finally, this study develops and validates an instrument that guides required changes in current CSCL systems to improve the non-task social functionality of the environment.     

Defining sociability and social presence in Social TV

Social TV, a new interactive television service, has been rapidly developing. With the conceptual model of sociability, this study empirically investigates the effects of perceived sociability on the motivations and attitudes toward Social TV. A model is created to validate the relationship of perceived sociality to social presence, usability, and intention. Empirical findings show the key influence of sociability on users’ acceptance and intent to continue using Social TV. Implications of the findings are discussed in terms of building a theory of sociability and providing practical insights into developing a meaningful sociable TV interface.     

浅谈街道密度与城市生活

本文通过对杭州典型街区的道路密度的调查研究,进行分析研究论述,揭示道路密度对于城市及街道生活的影响。希望能够对今后的城市规划和城市建设有所启示,从而提高我们城市生活的总体水平,促进城市健康持续的发展。     

Avatopia: a cross-media community for societal action

A cross-media platform was designed for a community of young teenagers oriented towards societal change. The platform involved an interactive web-forum featuring creative and communicative collaborative tools in a 3D avatar environment, and a weekly show in national public-service television. Informal assessment of the work indicated that (1) an integrated spiral of production and consumption across the two media channels involved is a viable design concept to support community building, (2) off-the-shelf avatar technology and consumer-grade Internet connectivity can form a feasible infrastructure for collaborative storytelling tools, and (3) a participatory design process wherein participants transition into the role of mentors and norm carriers upon deployment can be a feasible way to support subcultural community building towards “difficult” topics, even though it entails considerable resource demands. All of these findings are potentially transferable to other design domains and audiences.     

Explaining social presence and the quality of online learning with the SIPS model

The concept of Social Presence is often cited by researchers trying to understand the mechanisms governing beneficial learning climates and interpersonal connections among online learners. However, convoluted definitions and problematic measurements of social presence have made it difficult to understand how exactly social presence and related social variables come to be, hindering the investigation of reliable design recommendations. This study attempts to advance the SIPS (Sociability, Social Interaction, Social Presence, Social Space) model. It shows how these variables are related to each other and to relevant outcome variables like satisfaction. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to assess the predictive capabilities of the model regarding the outcome variables. Results support the notion that a sociable learning environment fosters social interaction, leading to social presence and the emergence of a sound social space, in turn explaining the quality of the learning experience. Social presence, when measured in a non-convoluted way, has no effect on satisfaction.     

A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage

Social networking sites (SNS) are quickly becoming one of the most popular tools for social interaction and information exchange. Previous research has shown a relationship between users’ personality and SNS use. Using a general population sample (N = 300), this study furthers such investigations by examining the personality correlates (Neuroticism, Extraversion, Openness-to-Experience, Agreeableness, Conscientiousness, Sociability and Need-for-Cognition) of social and informational use of the two largest SNS: Facebook and Twitter. Age and Gender were also examined. Results showed that personality was related to online socialising and information seeking/exchange, though not as influential as some previous research has suggested. In addition, a preference for Facebook or Twitter was associated with differences in personality. The results reveal differential relationships between personality and Facebook and Twitter usage.     

Understanding factors affecting perceived sociability of social software

Sociability is considered to be important to the success of social software. The goal of the current study is to identify factors that affect the users’ perception of the sociability of social software and to examine the impact of sociability on the users’ attitude and behavior intentions. In a pilot study, 35 web users were interviewed to gain understanding of how they use social software to supplement their social life and to explore the possible factors that influence the users’ utilization of social software. In the first study, a questionnaire was developed, and 163 valid responses were collected. From the factor analysis results, seven important factors for social software design emerged, which accounts for 63.3% of the total variance. In the second study, 246 participants were asked to evaluate one of ten popular social applications with respect to the seven factors, their perceived sociability, and their attitudes and intention regarding the use of the applications. Results show that sociability is influenced by social climate, benefits and purposes, people, interaction richness, self-presentation, and support for formal interaction. System competency is not a sociability factor, but it significantly influences the user’s experience. Sociability and system competency, when combined, can predict 43% of users’ attitude towards social software and 51% of their intentions to use social software.     

Introducing a procedure for developing a novel centrality measure (Sociability Centrality) for social networks using TOPSIS method and genetic algorithm

Centrality is one of the most important fields of social network research. To date, some centrality measures based on topological features of nodes in social networks have been proposed in which the importance of nodes is investigated from a certain point of view. Such measures are one dimensional and thus not feasible for measuring sociological features of nodes. Given that the main basis of Social Network Analysis (SNA) is related to social issues and interactions, a novel procedure is hereby proposed for developing a new centrality measure, named Sociability Centrality, based on the TOPSIS method and Genetic Algorithm (GA). This new centrality is not only based on topological features of nodes, but also a representation of their psychological and sociological features that is calculable for large size networks (e.g. online social networks) and has high correlation with the nodes' social skill questionnaire scores. Finally, efficiency of the proposed procedure for developing sociability centrality was tested via implementation on the Abrar Dataset. Our results show that this centrality measure outperforms its existing counterparts in terms of representing the social skills of nodes in a social network.