Social Collaborative Retrieval

Socially-based recommendation systems have recently attracted significant interest, and a number of studies have shown that social information can dramatically improve a system's predictions of user interests. Meanwhile, there are now many potential applications that involve aspects of both recommendation and information retrieval, and the task of collaborative retrieval---a combination of these two traditional problems---has recently been introduced. Successful collaborative retrieval requires overcoming severe data sparsity, making additional sources of information, such as social graphs, particularly valuable. In this paper we propose a new model for collaborative retrieval, and show that our algorithm outperforms current state-of-the-art approaches by incorporating information from social networks. We also provide empirical analyses of the ways in which cultural interests propagate along a social graph using a real-world music dataset.Comment: 10 page

Hard to recall but easy to judge: retrieval strategies in social information processing

The present research distinguishes two different retrieval modes: exhaustive and heuristic retrieval. Whereas exhaustive retrieval is elemental and retrieves specific memory traces, the output of heuristic retrieval is a memory composite. Different memory tasks depend upon these two retrieval modes in various degrees. Using a part-list cueing paradigm, we found a dissociation: providing part-list cues hindered the retrieval of the non-cued behaviors in free recall but boosted frequency estimates. In a second study, using a collaborative recall paradigm, each of three participants recalled one of the previously presented behaviors in turn. We hypothesized that behaviors recalled by other participants would become hyper-accessible, inhibiting the retrieval of non-recalled behaviors but boosting the corresponding frequency estimates relative to non-collaborative recall conditions. The results supported the hypotheses. The parallelism of the results of the two studies suggests that retrieval interference or inhibition is a crucial feature of social memory.info:eu-repo/semantics/acceptedVersio

Evaluating Collaborative Information Seeking Interfaces with a Search-Oriented Inspection Method and Re-framed Information Seeking Theory

Despite the many implicit references to the social contexts of search within Information Seeking and Retrieval research, there has been relatively little work that has specifically investigated the additional requirements for collaborative information seeking interfaces. Here, we re-assess a recent analytical inspection framework, designed for individual information seeking, and then apply it to evaluate a recent collaborative information seeking interface: SearchTogether. The framework was built upon two models of solitary information seeking, and so as part of the re-assessment we first re-frame the models for collaborative contexts. We re-frame a model of search tactics, providing revised definitions that consider known collaborators. We then re-frame a model of user profiles to analyse support for different group dynamics. After presenting an analysis of SearchTogether, we reflect on its accuracy, showing that the framework identified 8 known truths, 8 new insights, and no known-to-be-untrue insights into the design. We conclude that the framework a) can still be applied to collaborative information seeking interfaces; b) can successfully produce additional requirements for collaborative information seeking interfaces; and c) can successfully model different dynamics of collaborating searchers

Personalization of tagging systems

Social media systems have encouraged end user participation in the Internet, for the purpose of storing and distributing Internet content, sharing opinions and maintaining relationships. Collaborative tagging allows users to annotate the resulting user-generated content, and enables effective retrieval of otherwise uncategorised data. However, compared to professional web content production, collaborative tagging systems face the challenge that end-users assign tags in an uncontrolled manner, resulting in unsystematic and inconsistent metadata. This paper introduces a framework for the personalization of social media systems. We pinpoint three tasks that would benefit from personalization: collaborative tagging, collaborative browsing and collaborative s

User-Centered Social Information Retrieval Model Exploiting Annotations and Social Relationships

International audienceSocial Information Retrieval (SIR) has extended the classical information retrieval models and systems to take into account social information of the user within his social networks. We assume that a SIR system can exploit the informational social context (ISC) of the user in order to refine his retrieval, since different users may express different information needs as the same query. Hence, we present a SIR model that takes into account the user's social data, such as his annotations and his social relationships through social networks. We propose to integrate the user's ISC into the documents indexing process, allowing the SIR system to personalize the list of documents returned to the user. Our approach has shown interesting results on a test collection built from the social collaborative bookmarking network Delicious

Collaborative tagging as a knowledge organisation and resource discovery tool

The purpose of the paper is to provide an overview of the collaborative tagging phenomenon and explore some of the reasons for its emergence. Design/methodology/approach - The paper reviews the related literature and discusses some of the problems associated with, and the potential of, collaborative tagging approaches for knowledge organisation and general resource discovery. A definition of controlled vocabularies is proposed and used to assess the efficacy of collaborative tagging. An exposition of the collaborative tagging model is provided and a review of the major contributions to the tagging literature is presented. Findings - There are numerous difficulties with collaborative tagging systems (e.g. low precision, lack of collocation, etc.) that originate from the absence of properties that characterise controlled vocabularies. However, such systems can not be dismissed. Librarians and information professionals have lessons to learn from the interactive and social aspects exemplified by collaborative tagging systems, as well as their success in engaging users with information management. The future co-existence of controlled vocabularies and collaborative tagging is predicted, with each appropriate for use within distinct information contexts: formal and informal. Research limitations/implications - Librarians and information professional researchers should be playing a leading role in research aimed at assessing the efficacy of collaborative tagging in relation to information storage, organisation, and retrieval, and to influence the future development of collaborative tagging systems. Practical implications - The paper indicates clear areas where digital libraries and repositories could innovate in order to better engage users with information. Originality/value - At time of writing there were no literature reviews summarising the main contributions to the collaborative tagging research or debate

Recommendation, collaboration and social search

This chapter considers the social component of interactive information retrieval: what is the role of other people in searching and browsing? For simplicity we begin by considering situations without computers. After all, you can interactively retrieve information without a computer; you just have to interact with someone or something else. Such an analysis can then help us think about the new forms of collaborative interactions that extend our conceptions of information search, made possible by the growth of networked ubiquitous computing technology. Information searching and browsing have often been conceptualized as a solitary activity, however they always have a social component. We may talk about 'the' searcher or 'the' user of a database or information resource. Our focus may be on individual uses and our research may look at individual users. Our experiments may be designed to observe the behaviors of individual subjects. Our models and theories derived from our empirical analyses may focus substantially or exclusively on an individual's evolving goals, thoughts, beliefs, emotions and actions. Nevertheless there are always social aspects of information seeking and use present, both implicitly and explicitly. We start by summarizing some of the history of information access with an emphasis on social and collaborative interactions. Then we look at the nature of recommendations, social search and interfaces to support collaboration between information seekers. Following this we consider how the design of interactive information systems is influenced by their social elements

Collaborative facilitation and collaborative inhibition in virtual environments

Worldwide, organizations and small and medium-sized enterprises have already disruptively changed in many ways their physiological inner mechanisms, because of information and communication technologies (ICT) revolution. Nevertheless, the still ongoing COVID-19 worldwide emergency definitely promoted a wide adoption of teleworking modalities for many people around the world, making it more relevant than before to understand the real impact of virtual environments (VEs) on teamwork dynamics. From a psychological point of view, a critical question about teleworking modalities is how the social and cognitive dynamics of collaborative facilitation and collaborative inhibition would affect teamwork within VEs. This study analyzed the impact of a virtual environment (VE) on the recall of individuals and members of nominal and collaborative groups. The research assessed costs and benefits for collaborative retrieval by testing the effect of experimental conditions, stimulus materials, group size, experimental conditions order, anxiety state, personality traits, gender group composition and social interactions. A total of 144 participants were engaged in a virtual Deese-Roediger-McDermott (DRM) classical paradigm, which involved remembering word lists across two successive sessions, in one of four protocols: I-individual/nominal, I I -nominal/individual, I I I -nominal/collaborative, I V -collaborative/nominal. Results suggested, in general, a reduced collaborative inhibition effect in the collaborative condition than the nominal and individual condition. A combined effect between experimental condition and difficulty of the task appears to explain the presence of collaborative inhibition or facilitation. Nominal groups appeared to enhance the collaborative groups’ performance when virtual nominal groups come before collaborative groups. Variables such as personality traits, gender and social interactions may have a contribution to collaborative retrieval. In conclusion, this study indicated how VEs could maintain those peculiar social dynamics characterizing the participants’ engagement in a task, both working together and individually, and could affect their intrinsic motivation as well as performances. These results could be exploited in order to design brand new and evidenced-based practices, to improve teleworking procedures and workers well-being, as well as teleworking teamwork effectiveness.</jats:p