Raine Wilén, Mika Holopainen
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摘要

在日常生活中,意外事件是很常见的:它意味着意想不到的信息会产生一些意想不到的信息和潜在的价值。Serendipity这个词已经存在了几百年。作为一个被研究的概念,它是相当新的。Serendipity不仅仅是意外的信息或经历,而是识别并利用它做某事的能力。偶然发现的信息不同于有目的的或已知的项目搜索,因为它更复杂,持续的时间更长。偶然或意外发现的信息仍然在信息行为的模型和框架中寻找明确的位置。目前还不清楚是什么构成了信息行为中意外发现研究领域的核心。人、信息和对象之间的交互质量在物理环境和数字环境中是不同的。不同信息之间的关联,一种创造性的关联,可能是计算机支持的。本文概述了信息寻找行为中偶然性的研究。我们主要在数字信息环境中探索意外发现。作为我们研究的背景,我们使用了McCay-Peet和Toms(2017)中提出的与数字环境相关的意外发现研究的六个主要驱动因素。驱动因素是:1;对意外发现现象的理论理解,2)物理vs数字,3)信息过载,4)过滤气泡,5)用户体验,6)用户策略。本文还介绍了Erdelez和Makri(2020)提出的一种新的改进的信息相遇时间模型。该模型为更好地理解信息获取的时间维度提供了一个框架。在宏观层面上,该模型在与用户、信息、任务和环境相关的特征相关的上下文因素中定位遇到的信息。
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Epävarmuudesta arvokkaaseen lopputulokseen - serendipisyys tiedonhankintakäyttäytymisessä
A serendipitious event in everyday life is common: it means unexpected information that yields some unintended information and potential value later on. Serendipity as a word has been around for hundreds of years. As a studied concept it is rather recent. Serendipity is not just the unexpected information or experience but rather the ability to recognize and do something with it. Serendipitious discovery of information is different from purposive or known item search as it is  more complicated and lasts  much longer. The discovery of information by chance or accident is still looking it’s explicit place in models and frameworks of information behaviour. It is still not clear what constitutes the core of the research area of serendipity in information behaviour. The qualities of interaction among people, information, and objects differ in physical vs. digital environments. The bisociation, a creative association between different peaces of information may be computer supported. This article presents an overview of the research study of serendipity in information seeking behaviour. We explore serendipity mainly in the digital information environment. As a setting for our study we use six main drivers of serendipity research relating to digital enviroments presented in McCay-Peet and Toms (2017). The drivers are: 1. Theoretical understanding of the phenomen of serendipity, 2) physical vs digital, 3) information overload, 4) filter bubbles, 5) user experience, and 6) user strategies. A new refined temporal model of information encountering by Erdelez and Makri (2020) is also presented in this article. The model presents a framework for better understanding of the temporal dimension of the information acqusition. At a macro level the model positions information encountering within contextual factors related for user, information, task and environment related characteristics.
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