TY - JOUR AU - Wilén, Raine AU - Holopainen, Mika PY - 2021/12/21 Y2 - 2024/03/28 TI - Epävarmuudesta arvokkaaseen lopputulokseen - serendipisyys tiedonhankintakäyttäytymisessä JF - Informaatiotutkimus JA - INF VL - 40 IS - 4 SE - Katsaukset DO - 10.23978/inf.112440 UR - https://journal.fi/inf/article/view/112440 SP - 66–85 AB - <p>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.</p><p>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.</p><p>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.</p><p>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.</p> ER -