Recently, SNS (Social Network Service), blog and microblog have become very popular. Stream data, a large collection of diverse contents that are created dynamically in the form of streams, have become an important part of the Internet resources. At the same time, it has become easier to collect peopleʼs activities as their lifelogs, not only in the cyber space, but also in the physical world by means of ubiquitous and sensing technology. Either stream data or lifelogs represent different aspects of peopleʼs information behaviors and social activities, which we call Social Streams. In this study, we try to integrate and organize these social stream data, such as Twitter Tweets, into Ubiquitous Personal Study (UPS) proposed in our previous study. In this paper, we introduce and define a set of new metaphors: Drop, Stream, River and Ocean, to represent a variety of social stream data in different stages, in order to enable UPS socialized toward an individualized information portal. We further propose a Framework of Organic Streams to meaningfully organize these stream data. We discuss the design and implementation issues of a prototype system, and describe the algorithms to realize our proposed metaphors. Moreover, we show a scenario of using the socialized UPS to support learning activities, with experimental data and analysis results.
Chen, H., Zhou, X. and Jin, Q., 2012. Socialized ubiquitous personal study: Toward an individualized information portal. Journal of Computer and System Sciences, 78(6), pp.1775-1792.
This article, for the selection of “Socialized ubiquitous personal study: Toward an individualized information portal” as a notable paper in computing in 2012.
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