Exploring sharing patterns for video recommendation on YouTube-like social media

YouTube-like video sharing sites (VSSes) have gained increasing popularity in recent years. Meanwhile, Face-book-like online social networks (OSNs) have seen their tremendous success in connecting people of common interests. These two new generation of networked services are now bridged in that many users of OSNs share video contents originating from VSSes with their friends, and it has been shown that a significant portion of views of VSS videos are attributed to this sharing scheme of social networks. To understand how the video sharing behavior, which is largely based on social relationship, impacts users’ viewing pattern, we have conducted a long-term measurement with RenRen and YouKu, the largest online social network and the largest video sharing site in China, respectively. We show that social friends have higher common interest and their sharing behaviors provide guidance to enhance recommended video lists. In this paper, we take a first step toward learning OSN video sharing patterns for video recommendation. An autoencoder model is developed to learn the social similarity of different videos in terms of their sharing in OSNs. We, therefore, propose a similarity-based strategy to enhance video recommendation for YouTube-like social media. Evaluation results demonstrate that this strategy can remarkably improve the precision and recall of recommendations, as compared to other widely adopted strategies without social information.     

Monotone circuits for monotone weighted threshold functions

Weighted threshold functions with positive weights are a natural generalization of unweighted threshold functions. These functions are clearly monotone. However, the naive way of computing them is adding the weights of the satisfied variables and checking if the sum is greater than the threshold; this algorithm is inherently non-monotone since addition is a non-monotone function. In this work we by-pass this addition step and construct a polynomial size logarithmic depth unbounded fan-in monotone circuit for every weighted threshold function, i.e., we show that weighted threshold functions are in mAC¹. (To the best of our knowledge, prior to our work no polynomial monotone circuits were known for weighted threshold functions.)Our monotone circuits are applicable for the cryptographic tool of secret sharing schemes. Using general results for compiling monotone circuits (Yao, 1989) and monotone formulae (Benaloh and Leichter, 1990) into secret sharing schemes, we get secret sharing schemes for every weighted threshold access structure. Specifically, we get: (1) information-theoretic secret sharing schemes where the size of each share is quasi-polynomial in the number of users, and (2) computational secret sharing schemes where the size of each share is polynomial in the number of users.     

What makes good games go viral? The role of technology use,efficacy, emotion and enjoyment in players’ decision to share a prosocial digital game

Serious digital games may be an effective tool for prosocial message dissemination because they offer technology and experiences that encourage players to share them with others, and spread virally. But little is known about the factors that predict players’ willingness to share games with others in their social network. This panel study explores how several factors, including sharing technology use, emotional responses, and game enjoyment, contribute to players’ decision to share the game Darfur is Dying, with others. College students played the game and completed questionnaires that assessed whether they had shared the games at two different time points: during game play and after game play. Positive emotions predicted sharing while students played the game, but negative emotions predicted whether the game was shared after initial game play. Game enjoyment predicted players’ intentions to share the game, but it did not predict actual sharing behavior. Neither players’ general use of sharing technologies nor their satisfaction related to sharing digital content predicted sharing intentions or behavior. These findings have implications for the study of viral social marketing campaigns, and serious game design and theory.     

Mosco: a privacy-aware middleware for mobile social computing

The proliferation of mobile devices coupled with Internet access is generating a tremendous amount of highly personal and sensitive data. Applications such as location-based services and quantified self harness such data to bring meaningful context to users’ behavior. As social applications are becoming prevalent, there is a trend for users to share their mobile data. The nature of online social networking poses new challenges for controlling access to private data, as compared to traditional enterprise systems. First, the user may have a large number of friends, each associated with a unique access policy. Second, the access control policies must be dynamic and fine-grained, i.e. they are content-based, as opposed to all-or-nothing. In this paper, we investigate the challenges in sharing of mobile data in social applications. We design and evaluate a middleware running on Google App Engine, named Mosco, that manages and facilitates sharing of mobile data in a privacy-preserving manner. We use Mosco to develop a location sharing and a health monitoring application. Mosco helps shorten the development process. Finally, we perform benchmarking experiments with Mosco, the results of which indicate small overhead and high scalability.     

Go anywhere: user-verifiable authentication over distance-free channel for mobile devices

Current mobile technology gives us ubiquitous services with personal mobile devices such as smart phones, tablet PCs, and laptops. With these mobile devices, the human users may wish to exchange sensitive data with others (e.g., their friends or their colleagues) over a secure channel. Public key cryptography is a good solution for establishing this secure channel. However, it is vulnerable to man-in-the-middle attack, if the entities have no shared information. A number of techniques based on human-assisted out-of-band channels have been proposed to solve this problem. Unfortunately, these works have a common shortcoming: The human users must be colocated in close proximity. In this paper, we focus on how to construct a distance-free channel, which is not location-limited for establishing a secure channel between two users (devices). The proposed distance-free channel provides identification and authentication of the devices at the different locations using taken pictures or pre-stored images. The human user participates in the authentication process by sending and verifying an image. We describe the prototype implementation operated on a smart phone and show the experimental results when actually two smart phones share a common key using Diffie–Hellman key agreement over the proposed distance-free channel.     

Private aggregation for presence streams

Collaboration technologies must support information sharing between collaborators, but must also take care not to share too much information or share information too widely. Systems that share information without requiring an explicit action by a user to initiate the sharing must be particularly cautious in this respect. Presence systems are an emerging class of applications that support collaboration. Through the use of pervasive sensors, these systems estimate user location, activities, and available communication channels. Because such presence data are sensitive, to achieve wide-spread adoption, sharing models must reflect the privacy and sharing preferences of their users. This paper looks at the role that privacy-preserving aggregation can play in addressing certain user sharing and privacy concerns with respect to presence data.We define conditions to achieve CollaPSE (Collaboration Presence Sharing Encryption) security, in which (i) an individual has full access to her own data, (ii) a third party performs computation on the data without learning anything about the data values, and (iii) people with special privileges called “analysts” can learn statistical information about groups of individuals, but nothing about the individual values contributing to the statistic other than what can be deduced from the statistic. More specifically, analysts can decrypt aggregates without being able to decrypt the individual values contributing to the aggregate. Based in part on studies we carried out that illustrate the need for the conditions encapsulated by CollaPSE security, we designed and implemented a family of CollaPSE protocols. We analyze their security, discuss efficiency tradeoffs, describe extensions, and review more recent privacy-preserving aggregation work.     

Why would online gamers share their innovation-conducive knowledge in the online game user community? Integrating individual motivations and social capital perspectives

The user community has been an important external source of a firm’s product or service innovation. Users’ innovation-conducive knowledge sharing enables the community to work as a vital source of innovation. But, traditional economic theories of innovation seem to provide few explanations about why such knowledge sharing takes place for free in the user community. Therefore, this study investigates what drives community users to freely share their innovation-conducive knowledge, using the theory of planned behavior. Based on an empirical analysis of the data from 1244 members of a South Korean online game user community, it reveals that intrinsic motivation, shared goals, and social trust are salient factors in promoting users’ innovation-conducive knowledge sharing. Extrinsic motivation and social tie, however, were found to affect such sharing adversely, contingent upon whether a user is an innovator or a non-innovator. The study illustrates how social capital, in addition to individual motivations, forms and influences users’ innovation-conducive knowledge sharing in the online gaming context.     

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

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

Exploring factors that influence knowledge sharing behavior via weblogs

Knowledge sharing is seen as one of the essential processes for knowledge management. A growing number of professionals have started weblogging, and use this tool to share their ideas. It is important to explore ways to encourage individuals to contribute personal knowledge and to assist community members to share their expertise. Through the lens of sharing culture, we explore the factors that facilitate voluntary knowledge sharing in a virtual community. Specifically, the use of three categories associated with a sharing culture – fairness, identification and openness – is considered as a linear combination, which means that enjoying helping and usefulness/relevancy thereafter promote knowledge sharing behavior. To test the theoretical model, we survey 442 members of three online communities. In addition to the positive effects of fairness and openness on community sharing culture, we also find that enjoying helping, sharing culture and usefulness/relevancy are strongly linked to member knowledge sharing behavior. This paper offers a new perspective on the mechanisms related to the sharing culture construct, which in turn facilitates weblog knowledge sharing behaviors and yields important implications for understanding knowledge sharing behavior in online communities.     

Cultural Effects on Use of Online Social Media for Health-Related Information Acquisition and Sharing in Taiwan

The aims of this study were to use the technology acceptance model to examine how the cultural characteristics of social media users in Taiwan affect their use of social media for acquiring and sharing health-related information and to examine how their use of online social media benefits their social relationships and health self-efficacy. The research model in this quantitative cross-sectional study was tested with data collected from 321 active Facebook users in Taiwan. All three cultural characteristics/dimensions considered in the research model (masculinity, collectivism, and uncertainty avoidance) significantly affected the perceived usefulness and the perceived ease of using the online social media platform. However, masculinity had a significant positive effect on perceived usefulness but not on perceived ease of use. These results imply that technology tools for people in high masculinity cultures should be designed to maximize the effectiveness of the technology for achieving goals rather than to maximize the ease of using the technology. On the other hand, the use of online social media for acquiring and sharing health-related information significantly affected the social relationships of users but not their health self-efficacy. The results of this study imply that participants in online communities share health-related information not only to enhance their health but also to form strong social connections. This study proposes a new construct of technology acceptance, acquisition, and sharing of health-related information and investigates its effects on social relationships and health self-efficacy.     

Dealing with digital traces: Understanding protective behaviors on mobile devices

With increasingly digitization, more and more information is collected from individuals and organizations, leading to several privacy concerns. These risks are further heightened in the mobile realm as data collection can occur continuously and ubiquitously. When individuals use their own devices in work settings, these issues become concerns for organization as well. The question then is how to ensure individuals perform proper information protection behaviors on mobile devices. In this research, we develop a model of mobile information protection based on an integration of the Theory of Planned Behavior and the information privacy literature to explore the antecedents of the attitude of individuals towards sharing information on their mobile devices, their intentions to use protective settings, and their actual practices. The model is tested with data from 228 iPhone users. The results indicate that mobile information protection intention leads to actual privacy settings practice, and that attitude towards information sharing and mobile privacy protection self-efficacy affect this intention. Determinants of attitude towards information sharing include mobile privacy concern and trust of the mobile platform. Finally, prior invasion experience is related to privacy concern. These findings provide insights into factors that can be targeted to enhance individuals’ protective actions to limit the amount of digital information they share via their smartphones.     

Discerning individual interests and shared interests for social user profiling

Traditionally, research about social user profiling assumes that users share some similar interests with their followees. However, it lacks the studies on what topic and to what extent their interests are similar. Our study in online sharing sites reveals that besides shared interests between followers and followees, users do maintain some individual interests which differ from their followees. Thus, for better social user profiling we need to discern individual interests (capturing the uniqueness of users) and shared interests (capturing the commonality of neighboring users) of the users in the connected world. To achieve this, we extend the matrix factorization model by incorporating both individual and shared interests, and also learn the multi-faceted similarities unsupervisedly. The proposed method can be applied to many applications, such as rating prediction, item level social influence maximization and so on. Experimental results on real-world datasets show that our work can be applied to improve the performance of social rating. Also, it can reveal some interesting findings, such as who likes the “controversial” items most, and who is the most influential in attracting their followers to rate an item.     

The role of knowledge sharing self-efficacy in sharing Open Educational Resources

In the current paper we report on a study regarding teachers’ sharing behavior regarding their Open Educational Resources (OER) in the Netherlands. Little is known about how many teachers actually share their learning materials and, therefore, an attempt was made to estimate the number of Dutch teachers and the types of OER they share. Second, we tried to find out whether knowledge sharing self-efficacy facilitated, and evaluation apprehension and trust inhibited teachers to share OER in two different contexts of sharing behavior; sharing with colleagues at their school (interpersonal sharing) and sharing with the public through Internet (Internet sharing). A survey among 1568 teachers from primary to higher education was undertaken to test the relative importance of knowledge sharing self-efficacy, evaluation apprehension and trust in determining Dutch teachers’ intention to share. The results showed that a large proportion of the Dutch teachers shared their OER, but that this sharing was limited to learning materials with low complexity (e.g., texts or images). Moreover, sharing occurred twice as much interpersonally than via websites. Our hypothesis that evaluation apprehension is significantly related to sharing behavior as well as the intention to share was not confirmed. Self-efficacy to share knowledge did, however, explain some of the differences in sharing behavior and in the intention to share of Dutch teachers, although the variables under study accounted only for a small amount of variance. Our findings should thus be replicated in further studies and other variables should be considered that could effectively predict OER sharing behavior of teachers.     

Modelling and performance analysis of content sharing and distribution in community networks with infrastructure support

We consider the problem of sharing a viral file between users in a local community network (e.g., college and office campuses). Community computing is computer networking among and between users in a geographically bounded setting for local purposes and activities. Due to the community-oriented nature of such networks, it is likely that users of a community network would like to share content. Peer-to-Peer (P2P) networks have turned out to be one of the most innovative paradigms for sharing content on the Internet. In this paper, we analyze the performance of P2P content sharing in community networks and investigate the role that infrastructure nodes (helpers) can play to enhance the performance of content sharing and distribution. We model the evolution of content demand in a community network. The use of this demand prediction model allows us to design a delicate P2P-with-helpers content distribution system. Our insights that we obtain using fluid-flow model increase our understanding of how helper provisioning affects the performance of content sharing and distribution. The derived results show that significant reduction in both the cost of distributing content and the average content download time can be realized when only few infrastructure nodes in the community network play the role helpers and cache P2P objects.     

Strategic self-presentation online: A cross-cultural study

Contemporary social networking sites (SNSs) make idealized self-presentation and image maintenance difficult because users’ audiences are becoming more diverse and individual users must negotiate often unanticipated other-provided information in the form of text posts and digital images on their profile pages. This cross-cultural study examines how audience-related variables affect a range of strategic self-presentation and image management behaviors online. Results from samples of Singaporean and American SNS users (N = 411) show that while Americans update their profiles with text-based wall posts more frequently, Singaporeans share significantly more photos. Audience diversity is positively associated with active management of other-provided information, and females share more photos and actively manage unwanted photo tagging. Cultural identity and the tendency to ‘friend’ unknown others interact on managing other-provided wall posts; individualistic cultural identity exhibited positive relationships with these reactions for those less likely to friend unknown others but negative ones for those more likely to friend unknown others. Implications for the theoretical understanding of and practical suggestions about self-presentation online are discussed.     

The structure and dynamics of knowledge network in domain-specific Q&A sites: a case study of stack overflow

Programming-specific Q&A sites (e.g., Stack Overflow) are being used extensively by software developers for knowledge sharing and acquisition. Due to the cross-reference of questions and answers (note that users also reference URLs external to the Q&A site. In this paper, URL sharing refers to internal URLs within the Q&A site, unless otherwise stated), knowledge is diffused in the Q&A site, forming a large knowledge network. In Stack Overflow, why do developers share URLs? How is the community feedback to the knowledge being shared? What are the unique topological and semantic properties of the resulting knowledge network in Stack Overflow? Has this knowledge network become stable? If so, how does it reach to stability? Answering these questions can help the software engineering community better understand the knowledge diffusion process in programming-specific Q&A sites like Stack Overflow, thereby enabling more effective knowledge sharing, knowledge use, and knowledge representation and search in the community. Previous work has focused on analyzing user activities in Q&A sites or mining the textual content of these sites. In this article, we present a methodology to analyze URL sharing activities in Stack Overflow. We use open coding method to analyze why users share URLs in Stack Overflow, and develop a set of quantitative analysis methods to study the structural and dynamic properties of the emergent knowledge network in Stack Overflow. We also identify system designs, community norms, and social behavior theories that help explain our empirical findings. Through this study, we obtain an in-depth understanding of the knowledge diffusion process in Stack Overflow and expose the implications of URL sharing behavior for Q&A site design, developers who use crowdsourced knowledge in Stack Overflow, and future research on knowledge representation and search.     

Employee creativity formation: The roles of knowledge seeking,knowledge contributing and flow experience in Web 2.0 virtual communities

Knowledge seeking and knowledge contributing are two distinct types of behaviors, both of which must occur for the presumed benefits of knowledge sharing to be realized. Self-perception theory posits that individuals come to ‘know’ their own internal beliefs by inferring them partially from observations of their own overt behavior. Building on self-perception theory and adhering to the principle that knowledge sharing facilitates knowledge creation, we develop a research model to explore the consequences of both knowledge seeking and knowledge contributing behavior given the consideration that flow plays a lubricating role in the formation of creativity. Data collected from 232 users of Web 2.0 virtual communities were used to test the model. We found that both knowledge seeking and knowledge contributing can lead to a state of flow and can further result in creativity at work. These findings and their implications for theory and practice are discussed.     

Social compensation or rich-get-richer? The role of social competence in college students’ use of the Internet to find a partner

Online dating continues to grow rapidly in popularity every day, yet the role of social competence in online dating behavior remains unclear. This study was designed to expand previous research and conduct a comprehensive investigation on how social competence is associated with college students’ online dating behaviors, perceptions, and attitudes. Two hypotheses were tested: The social compensation hypothesis (SCH)—socially incompetent individuals would engage in more online dating, and the rich-get-richer hypothesis (RGRH)—socially competent individuals would use online dating more than their incompetent counterparts. The results showed that incompetent individuals, despite their ability to see benefits in online dating, did not show a favorable attitude towards online dating. They indicated a more frequent use of and a stronger preference for face-to-face dating compared to online dating, which contradicted the SCH. There were weak associations between competence traits and online dating behavior. Socially competent individuals perceived less benefit and showed less interest in online dating, which disconfirmed the RGRH.     

Networked Participatory Scholarship: Emergent techno-cultural pressures toward open and digital scholarship in online networks

We examine the relationship between scholarly practice and participatory technologies and explore how such technologies invite and reflect the emergence of a new form of scholarship that we call Networked Participatory Scholarship: scholars’ participation in online social networks to share, reflect upon, critique, improve, validate, and otherwise develop their scholarship. We discuss emergent techno-cultural pressures that may influence higher education scholars to reconsider some of the foundational principles upon which scholarship has been established due to the limitations of a pre-digital world, and delineate how scholarship itself is changing with the emergence of certain tools, social behaviors, and cultural expectations associated with participatory technologies.     

An approach for supporting distributed user interface orchestration over the Web

Currently, a lot of the tasks engaged by users over the Web involve dealing with multiple Web sites. Moreover, whilst Web navigation was considered as a lonely activity in the past, a large proportion of users are nowadays engaged in collaborative activities over the Web. In this paper we argue that these two aspects of collaboration and tasks spanning over multiple Web sites call for a level of coordination that require Distributed User Interfaces (DUI). In this context, DUIs would play a major role by helping multiple users to coordinate their activities whilst working collaboratively to complete tasks at different Web sites. For that, we propose in this paper an approach to create distributed user interfaces featuring procedures that are aimed to orchestrate user tasks over multiple Web sites. Our approach supports flexible process modeling by allowing users to combine manual tasks and automated tasks from a repertoire of patterns of tasks performed over the Web. In our approach, whilst manual tasks can be regarded as simple instructions that tell users how to perform a task over a Web site, automated tasks correspond to tools built under the concept of Web augmentation (as it augments the repertoire of tasks users can perform over the Web) called Web augmenters. Both manual and automated tasks are usually supported by specific DOM elements available in different Web sites. Thus, by combining tasks and DOM elements distributed in diverse Web sites our approach supports the creation of procedures that allows seamless users interaction with diverse Web site. Moreover, such an approach is aimed at supporting the collaboration between users sharing procedures. The approach is duly illustrated by a case study describing a collaborative trip planning over the Web.