FaceMashup: An End-User Development Tool for Social Network Data
نویسندگان
چکیده
Every day, each active social network user produces and shares texts, images and videos. While developers can access such data through application programming interfaces (APIs) for creating games, visualizations and routines, end users have less control on such information. Their access is mediated by the social application features, which limits them in combining sources, filtering results and performing actions on groups of elements. In order to fill this gap, we introduce FaceMashup, an end user development (EUD) environment supporting the manipulation of the Facebook graph. We describe the tool interface, documenting the choices we made during the design iterations. Data types are represented through widgets containing user interface (UI) elements similar to those used in the social network application. Widgets can be connected with each other with the drag and drop of their inner fields, and the application updates their content. Finally, we report the results of a user-test on the FaceMashup prototype, which shows a good acceptance of the environment by end-users.
منابع مشابه
Development of An Artificial Neural Network Model for Asphalt Pavement Deterioration Using LTPP Data
Deterioration models are important and essential part of any Pavement Management System (PMS). These models are used to predict future pavement situation based on existence condition, parameters causing deterioration and implications of various maintenance and rehabilitation policies on pavement. The majority of these models are based on roughness which is one of the most important indices in p...
متن کاملMEFUASN: A Helpful Method to Extract Features using Analyzing Social Network for Fraud Detection
Fraud detection is one of the ways to cope with damages associated with fraudulent activities that have become common due to the rapid development of the Internet and electronic business. There is a need to propose methods to detect fraud accurately and fast. To achieve to accuracy, fraud detection methods need to consider both kind of features, features based on user level and features based o...
متن کاملImproving Accuracy of Recommender Systems using Social Network Information and Longitudinal Data
The rapid development of technology, the Internet, and the development of electronic commerce have led to the emergence of recommender systems. These systems will assist the users in finding and selecting their desired items. The accuracy of the advice in recommender systems is one of the main challenges of these systems. Regarding the fuzzy systems capabilities in determining the borders of us...
متن کاملImproving the performance of recommender systems in the face of the cold start problem by analyzing user behavior on social network
The goal of recommender system is to provide desired items for users. One of the main challenges affecting the performance of recommendation systems is the cold-start problem that is occurred as a result of lack of information about a user/item. In this article, first we will present an approach, uses social streams such as Twitter to create a behavioral profile, then user profiles are clusteri...
متن کاملModeling, Designing and Evaluating A Social Network in the Field of Health
Background and Aim: Social networks that provide users with health data not only educate them but also play an active role in the health decision-making process. Health social networks, in addition to being a good tool for better patient communication with health care providers, can play an effective role in connecting similar patients with each other to receive social support. Social networkin...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Future Internet
دوره 8 شماره
صفحات -
تاریخ انتشار 2016