ترغب بنشر مسار تعليمي؟ اضغط هنا

XTribe: a web-based social computation platform

127   0   0.0 ( 0 )
 نشر من قبل Vito Domenico Pietro Servedio
 تاريخ النشر 2014
  مجال البحث الهندسة المعلوماتية
والبحث باللغة English




اسأل ChatGPT حول البحث

In the last few years the Web has progressively acquired the status of an infrastructure for social computation that allows researchers to coordinate the cognitive abilities of human agents in on-line communities so to steer the collective user activity towards predefined goals. This general trend is also triggering the adoption of web-games as a very interesting laboratory to run experiments in the social sciences and whenever the contribution of human beings is crucially required for research purposes. Nowadays, while the number of on-line users has been steadily growing, there is still a need of systematization in the approach to the web as a laboratory. In this paper we present Experimental Tribe (XTribe in short), a novel general purpose web-based platform for web-gaming and social computation. Ready to use and already operational, XTribe aims at drastically reducing the effort required to develop and run web experiments. XTribe has been designed to speed up the implementation of those general aspects of web experiments that are independent of the specific experiment content. For example, XTribe takes care of user management by handling their registration and profiles and in case of multi-player games, it provides the necessary user grouping functionalities. XTribe also provides communication facilities to easily achieve both bidirectional and asynchronous communication. From a practical point of view, researchers are left with the only task of designing and implementing the game interface and logic of their experiment, on which they maintain full control. Moreover, XTribe acts as a repository of different scientific experiments, thus realizing a sort of showcase that stimulates users curiosity, enhances their participation, and helps researchers in recruiting volunteers.

قيم البحث

اقرأ أيضاً

Lets HPC (www.letshpc.org) is an open-access online platform to supplement conventional classroom oriented High Performance Computing (HPC) and Parallel & Distributed Computing (PDC) education. The web based platform provides online plotting and anal ysis tools which allow users to learn, evaluate, teach and see the performance of parallel algorithms from a systems viewpoint. The user can quantitatively compare and understand the importance of numerous deterministic as well as non-deterministic factors of both the software and the hardware that impact the performance of parallel programs. At the heart of this platform is a database archiving the performance and execution environment related data of standard parallel algorithms executed on different computing architectures using different programming environments, this data is contributed by various stakeholders in the HPC community. The plotting and analysis tools of our platform can be combined seamlessly with the database to aid self-learning, teaching, evaluation and discussion of different HPC related topics. Instructors of HPC/PDC related courses can use the platforms tools to illustrate the importance of proper analysis in understanding factors impacting performance, to encourage peer learning among students, as well as to allow students to prepare a standard lab/project report aiding the instructor in uniform evaluation. The platforms modular design enables easy inclusion of performance related data from contributors as well as addition of new features in the future.
As an emerging business phenomenon especially in China, instant messaging (IM) based social commerce is growing increasingly popular, attracting hundreds of millions of users and is becoming one important way where people make everyday purchases. Suc h platforms embed shopping experiences within IM apps, e.g., WeChat, WhatsApp, where real-world friends post and recommend products from the platforms in IM group chats and quite often form lasting recommending/buying relationships. How and why do users engage in IM based social commerce? Do such platforms create novel experiences that are distinct from prior commerce? And do these platforms bring changes to user social lives and relationships? To shed light on these questions, we launched a qualitative study where we carried out semi-structured interviews on 12 instant messaging based social commerce users in China. We showed that IM based social commerce: 1) enables more reachable, cost-reducing, and immersive user shopping experience, 2) shapes user decision-making process in shopping through pre-existing social relationship, mutual trust, shared identity, and community norm, and 3) creates novel social interactions, which can contribute to new tie formation while maintaining existing social relationships. We demonstrate that all these unique aspects link closely to the characteristics of IM platforms, as well as the coupling of user social and economic lives under such business model. Our study provides important research and design implications for social commerce, and decentralized, trusted socio-technical systems in general.
In this paper we present an experimental framework to gather data on face-to-face social interactions between individuals, with a high spatial and temporal resolution. We use active Radio Frequency Identification (RFID) devices that assess contacts w ith one another by exchanging low-power radio packets. When individuals wear the beacons as a badge, a persistent radio contact between the RFID devices can be used as a proxy for a social interaction between individuals. We present the results of a pilot study recently performed during a conference, and a subsequent preliminary data analysis, that provides an assessment of our method and highlights its versatility and applicability in many areas concerned with human dynamics.
In information-rich environments, the competition for users attention leads to a flood of content from which people often find hard to sort out the most relevant and useful pieces. Using Twitter as a case study, we applied an attention economy soluti on to generate the most informative tweets for its users. By considering the novelty and popularity of tweets as objective measures of their relevance and utility, we used the Huberman-Wu algorithm to automatically select the ones that will receive the most attention in the next time interval. Their predicted popularity was confirmed by using Twitter data collected for a period of 2 months.
Web archiving services play an increasingly important role in todays information ecosystem, by ensuring the continuing availability of information, or by deliberately caching content that might get deleted or removed. Among these, the Wayback Machine has been proactively archiving, since 200
التعليقات
جاري جلب التعليقات جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
mircosoft-partner

هل ترغب بارسال اشعارات عن اخر التحديثات في شمرا-اكاديميا