用SDCF捕获社会交互:移动传感和无处不在的数据收集的可扩展框架

MSM '13 Pub Date : 2013-05-01 DOI:10.1145/2463656.2463662
M. Atzmüller, Katy Hilgenberg
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引用次数: 37

摘要

社交媒体和移动设备已经融入日常生活,调解各种隐性和显性的社交互动。交互数据的分析和建模,包括物理和在线社交交互,正受到越来越多的关注。然后,通过有效的数据收集方法给出了一个先决条件,包括传感器数据和社交媒体工件。本文介绍了传感器数据收集框架(SDCF),这是一个紧凑,通用且易于扩展的开源框架,用于移动传感和无处不在的数据收集。它提供了对核心概念和体系结构的概述。此外,我们还讨论了在协作工作组环境中应用该框架的初步经验和结果。
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Towards capturing social interactions with SDCF: an extensible framework for mobile sensing and ubiquitous data collection
Social media as well as mobile devices have woven themselves into everyday life, mediating various implicit and explicit social interactions. The analysis and modeling of the interaction data, including both physical and online social interactions is receiving increasing interest. A prerequisite is then given by effective approaches for data collection, covering both sensor data and social media artifacts. This paper describes the Sensor Data Collection Framework (SDCF), a compact, versatile and easily extensible open source framework for mobile sensing and ubiquitous data collection. It provides an overview on core concepts and architecture. Furthermore, we discuss first experiences and results of applying the framework in a collaborative workgroup context.
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