There is currently a number of research work performed in the area of bridging the gap between Information Retrieval (IR) and Online Social Networks (OSN). This is mainly done by enhancing the IR process with information coming from social networks, a process called Social Information Retrieval (SIR). The main question one might ask is What would be the benefits of using social information (no matter whether it is content or structure) into the information retrieval process and how is this currently done?
With the growing number of efforts towards the combination of IR and social networks, it is necessary to build a clearer picture of the domain and synthesize the efforts in a structured and meaningful way. This paper reviews different efforts in this domain. It intends to provide a clear understanding of the issues as well as a clear structure of the contributions. More precisely, we propose (i) to review some of the most important contributions in this domain to understand the principles of SIR, (ii) a taxonomy to categorize these contributions, and finally, (iii) an analysis of some of these contributions and tools with respect to several criteria, which we believe are crucial to design an effective SIR approach. This paper is expected to serve researchers and practitioners as a reference to help them structuring the domain, position themselves and, ultimately, help them to propose new contributions or improve existing ones.
The representation and retrieval of books on the Skoob and GoodReads platforms is explored. In order to investigate the procedures and criteria of social indexing in the book platforms of Skoob and GoodReads, exploratory research was carried out in two phases: bibliographical research on social indexing, and analysis of the attribution and retrieval of representative terms in the book platforms of Skoob and GoodReads. The research results showed that both platforms offer the same basic services: organizing the users' readings and enabling interaction between them regarding their readings. What sets them apart are small details: GoodReads does not allow social indexing, although users can assign representative terms to the books that make up their personal shelf; on Skoob, the users perform the social indexing. Both platforms do not have any type of controlled vocabulary, directly affecting the representation and retrieval of books.
Tagging systems represent the conceptual knowledge of a community. We experimentally tested whether people harness this collective knowledge when navigating through the Web. As a within-factor we manipulated people's prior knowledge (no knowledge vs. prior knowledge that was congruent/incongruent to the collective knowledge inherent in the tags). As between-factor we manipulated whether people had tag clouds available or not. In line with the Information Foraging Theory and with the Co-Evolution Model of individual learning and collective knowledge building, we found that people's prior knowledge and tag clouds influenced their navigation
The article deals with the rapidly spreading phenomenon of collective tagging and its impact on library community. The term collective tagging implies the method of organization which is used in order to organize, preserve, search, and exchange the c...
Instagram is widely known and used as a social media application for visual content. In order to categorize and describe their posted content as well as to make it retrievable, users can assign hashtags to each posting. What kind of hashtags do female and male Instagram users assign to their picture postings? Which differences and similarities exist? This study analyzes gender-specific image tagging behavior on Instagram.
umblr is one of the most popular content sharing websites, where the use of keyword tags that enhance the searchability and visibility of posts is prominent. However, this resource has been creatively exploited by some users beyond its folksonomic use: Since Tumblr does not have a separate comment section for posts, the tag section may also be used for tags with discourse functions such as expressing an opinion, a reaction, or including asides. This article explores the practice of including comments in tags, taking into account the specific technological features of Tumblr’s tagging system, as well as the role of the communities within the website.
The article contributes to conceptual studies of information behaviour research by examining the conceptualisations of information seeking and related terms such as information search and browsing.
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