Collaborative information seeking: The combined activity of information seeking and collaborative grounding

Since common ground is pivotal to collaboration, this paper proposes to define collaborative information seeking as the combined activity of information seeking and collaborative grounding. While information-seeking activities are necessary for collaborating actors to acquire new information, the activities involved in information seeking are often performed by varying subgroups of actors. Consequently, collaborative grounding is necessary to share information among collaborating actors and, thereby, establish and maintain the common ground necessary for their collaborative work. By focusing on the collaborative level, collaborative information seeking aims to avoid both individual reductionism and group reductionism, while at the same time recognizing that only some information and understanding need be shared.     

Collaborative information seeking: A field study of a multidisciplinary patient care team

Multidisciplinary teams are an essential aspect of modern organizational work. These teams often work in information-rich environments but little is known about their collaborative information seeking (CIS) behavior. We have been studying the CIS behavior of teams in the context of medical care. We conducted an ethnographic field study of a multidisciplinary patient care team in an emergency department to identify (a) team information needs and (b) situations that trigger collaborative information seeking activities. We identified seven categories of information needs as expressed by questions asked by team members. The majority of questions focused on medical information, but there were a larger than expected percentage of questions focusing on organizational information. We also identified three triggers for CIS activities. These triggers are: (1) lack of expertise, (2) lack of immediately accessible information, and (3) complex information needs. The questions and triggers highlight the importance of face-to-face communication during CIS activities and how CIS activities could lead to interruptive workplaces. We also discuss organizational and technical implications for supporting CIS behavior of teams.     

A model for understanding collaborative information behavior in context: A study of two healthcare teams

Collaborative information behavior is an essential aspect of organizational work; however, we have very limited understanding of this behavior. Most models of information behavior focus on the individual seeker of information. In this paper, we report the results from two empirical studies that investigate aspects of collaborative information behavior in organizational settings. From these studies, we found that collaborative information behavior differs from individual information behavior with respect to how individuals interact with each other, the complexity of the information need, and the role of information technology. There are specific triggers for transitioning from individual to collaborative information behavior, including lack of domain expertise. The information retrieval technologies used affect collaborative information behavior by acting as important supporting mechanisms. From these results and prior work, we develop a model of collaborative information behavior along the axes of participant behavior, situational elements, and contextual triggers. We also present characteristics of collaborative information system including search, chat, and sharing. We discuss implications for the design of collaborative information retrieval systems and directions for future work.     

Uncertainty in information seeking and retrieval: A study in an academic environment

This research focuses specifically on uncertainty and information seeking in a digital environment. In this research we argue that different types of uncertainty are associated with the information seeking process and that, with the proliferation of new and different search tools, sources and channels, uncertainty, positive/desirable or negative/undesirable, continues to be a significant factor in the search process. Users may feel uncertain at any stage of the information search and retrieval process and uncertainty may remain even after completion of the process resulting in what may be called persistent uncertainty. An online questionnaire was used to collect data from users in the higher education sector. There were three parts to the questionnaire focusing on: information seeking activities, information seeking problems, and access to specific information channels or sources. Quantitative analysis was carried out on the data collected through the online questionnaire. A total of 668 responses were returned from the chosen user categories of academic staff, research staff and research students. This research has shown that there are some information seeking activities and information seeking problems that are the most common causes of uncertainty among significant number of users from different disciplines, age, gender, ICT skills, etc. This is also the case with respect to access to and use of specific information sources/channels, although the degrees of uncertainty in relation are relatively small. Possible implications of this study and further research issues are indicated.     

CIRLab: A groupware framework for collaborative information retrieval research

In this paper we describe the design of a groupware framework, CIRLab, for experimenting with collaborative information retrieval (CIR) techniques in different search scenarios. This framework has been designed applying design patterns and an object-oriented middleware platform to maximize its reusability and adaptability in new contexts with a minimum of programming efforts. Our collaborative search application comprises three main modules: the Core, which supports various modern state-of-the-art CIR techniques that can be reused or extended in a distributed collaborative environment; the Facades Mediator, an event-driven notification service which allows easy integration between the Core and front-end applications; and finally, the Actions Tracker, which allows researchers to perform experiments on the different elements involved in the collaborative search sessions. The applying of this framework is illustrated through the analysis of the collaborative search-driven development case study.     

Antecedents predicting health information seeking: A systematic review and meta-analysis

Numerous reasons regarding why people should seek health information exist, but empirical evidence has indicated that factors that influence health information seeking (HIS) differ according to the context. To make suggestions based on explicit and judicious use of the best available evidence, a meta-analytic review was undertaken. In the present review, 16 electronic databases were searched up to July 2019, empirical results of 71 primary studies that met inclusion criteria were coded, and seven antecedents that commonly affect HIS behavior were examined. We obtained 204 correlation coefficients from 90 independent subsets with a total of 74,171 respondents. The results indicated that self-efficacy (ES_r = 0.254), health literacy (ES_r = 0.222), availability (ES_r = 0.412), credibility (ES_r = 0.308), emotional response (ES_r = 0.090), and subjective norms (ES_r = 0.443) substantially influenced individuals’ HIS, and subjective norms was the most influential factor. Individuals’ behavior usually aligns with the opinions of other critical individuals in their lives, and this phenomenon was observed in the present study of the HIS context. In addition, eight variables were examined as potential moderators (i.e., roles of samples, gender, average age, topic, information channel, type of publication, data collecting method, and sampling method); statistically significant effects on some of the aggregated correlations were noted for all of these variables.     

Division of labour and sharing of knowledge for synchronous collaborative information retrieval

Synchronous collaborative information retrieval (SCIR) is concerned with supporting two or more users who search together at the same time in order to satisfy a shared information need. SCIR systems represent a paradigmatic shift in the way we view information retrieval, moving from an individual to a group process and as such the development of novel IR techniques is needed to support this. In this article we present what we believe are two key concepts for the development of effective SCIR namely division of labour (DoL) and sharing of knowledge (SoK). Together these concepts enable coordinated SCIR such that redundancy across group members is reduced whilst enabling each group member to benefit from the discoveries of their collaborators. In this article we outline techniques from state-of-the-art SCIR systems which support these two concepts, primarily through the provision of awareness widgets. We then outline some of our own work into system-mediated techniques for division of labour and sharing of knowledge in SCIR. Finally we conclude with a discussion on some possible future trends for these two coordination techniques.     

Source preferences in the context of seeking problem-specific information

The study focuses on the ways in which people define their source preferences in the context of seeking problem-specific information for non-work purposes. The conceptual framework draws on two major concepts, that is, information source horizon and information pathways. The former denotes the ways information sources are mapped in preference order in an imaginary field, while information pathways refers to the sequences in which sources placed on the information source horizon are actually used. The empirical part of the study draws on semi-structured interviews with 18 individuals active in environmental issues. Human sources and the Internet were preferred most strongly in seeking for problem-based information. The major source preferences were content of information, and availability and accessibility. Usability of information sources and user characteristics were mentioned less frequently as preference criteria. Typically, information pathways consisted of the use of 3–4 sources. On average, human and networked sources were favored in the early phases of information seeking. Printed media such as magazines and organizational sources were often used to complement information received from human sources and the Internet. However, the source preferences varied considerably, depending on the requirements of the problem at hand.     

On domain expertise-based roles in collaborative information retrieval

Collaborative information retrieval involves retrieval settings in which a group of users collaborates to satisfy the same underlying need. One core issue of collaborative IR models involves either supporting collaboration with adapted tools or developing IR models for a multiple-user context and providing a ranked list of documents adapted for each collaborator. In this paper, we introduce the first document-ranking model supporting collaboration between two users characterized by roles relying on different domain expertise levels. Specifically, we propose a two-step ranking model: we first compute a document-relevance score, taking into consideration domain expertise-based roles. We introduce specificity and novelty factors into language-model smoothing, and then we assign, via an Expectation–Maximization algorithm, documents to the best-suited collaborator. Our experiments employ a simulation-based framework of collaborative information retrieval and show the significant effectiveness of our model at different search levels.     

Online community information seeking: The queries of three communities in Southwestern Ontario

This paper presents not only mycommunityinfo.ca (MCI) as an innovative World Wide Web (WWW)-based community information (CI) site, but also how its unique approach to facilitating online CI searching on the Web reveals through empirical data how people use such information and communication technologies (ICTs) to address their everyday information needs. The geographic focus for this study is on three communities in Southwestern Ontario. MCI collects unobtrusively query data that are logged daily from its own Web site, the Web sites of three municipal governments, and one municipal agency from this region. One year’s worth of these data was supplied to determine the types of CI that are sought through Web searching. A content analysis of a large purposive sample of all of MCI’s query data reveals more specific and diverse conceptual CI needs between and within communities than those reported in other studies employing different data collection methods. As a result, using a centralized approach to online CI access via the WWW by other CI providers such as the 211 network may be a disservice to its users. Additionally, the findings demonstrate how a thorough analysis of such data may improve the informational content and overall design of municipal government Web sites. The analysis of these data also has the potential of improving current CI taxonomies.     

Beyond traditional collaborative search: Understanding the effect of awareness on multi-level collaborative information retrieval

Although there has been a great deal of research into Collaborative Information Retrieval (CIR) and Collaborative Information Seeking (CIS), the majority has assumed that team members have the same level of unrestricted access to underlying information. However, observations from different domains (e.g. healthcare, business, etc.) have suggested that collaboration sometimes involves people with differing levels of access to underlying information. This type of scenario has been referred to as Multi-Level Collaborative Information Retrieval (MLCIR). To the best of our knowledge, no studies have been conducted to investigate the effect of awareness, an existing CIR/CIS concept, on MLCIR. To address this gap in current knowledge, we conducted two separate user studies using a total of 5 different collaborative search interfaces and 3 information access scenarios. A number of Information Retrieval (IR), CIS and CIR evaluation metrics, as well as questionnaires were used to compare the interfaces. Design interviews were also conducted after evaluations to obtain qualitative feedback from participants. Results suggested that query properties such as time spent on query, query popularity and query effectiveness could allow users to obtain information about team's search performance and implicitly suggest better queries without disclosing sensitive data. Besides, having access to a history of intersecting viewed, relevant and bookmarked documents could provide similar positive effect as query properties. Also, it was found that being able to easily identify different team members and their actions is important for users in MLCIR. Based on our findings, we provide important design recommendations to help develop new CIR and MLCIR interfaces.     

Deploying lean in healthcare: Evaluating information technology effectiveness in U.S. hospital pharmacies

This case study provides a lens of operation research for evaluating the use of technology on medication distribution systems in U.S. hospital and helps better understand how technologies improve the healthcare operational performance in terms of processing time and cost. We analyze two prescribing technologies, namely no carbon required (NCR) and digital scanning technologies to quantify the advantages of the medication ordering, transcribing, and dispensing process in a multi-hospital health system. With comparison between these two technologies, the statistical analysis results show a significant reduction on process times by adopting digital scanning technology. The results indicated a reduction of 54.5% in queue time, 32.4% in order entry time, 76.9% in outgoing delay time, and 67.7% in outgoing transit time with the use of digital scanning technology. We also conducted a cost analysis on each of the two technologies, illustrating that the total cost generated by using digital scanning was as low as 37.31% of that generated by NCR. Lessons learned about how to evaluate IT effectiveness by lean methods are presented for both theoretical and practical perspectives.     

Let’s search together,but not too close! An analysis of communication and performance in collaborative information seeking

Communication is considered to be one of the most essential components of collaboration, but our understanding as to which form of communication provides the most optimal cost-benefit balance lacks severely. To help investigate effects of various communication channels on a collaborative project, we conducted a user study with 30 pairs (60 participants) in three different conditions – co-located, remotely located with text chat, and remotely located with text as well as audio chat, in an exploratory search task. Using both quantitative and qualitative data analysis, we found that teams with remotely located participants were more effective in terms of being able to explore more diverse information. Adding audio support for remote collaboration helped participants to lower their cognitive load as well as negative emotions compared to those working in the same space. We also show how these findings could help design more effective systems for collaborative information seeking tasks using adequate and appropriate communication. We argue that collaboration is an important aspect of human-centered IR, and that our work provides interesting insights into people doing information seeking/retrieval in collaboration.     

Social and interactional practices for disseminating current awareness information in an organisational setting

Current awareness services are designed to keep users informed about recent developments based around user need profiles. In organisational settings, they may operate through both electronic and social interactions aimed at delivering information that is relevant, pertinent and current. Understanding these interactions can reveal the tensions in current awareness dissemination and help inform ways of making services more effective and efficient. We report an in-depth, observational study of electronic current awareness use within a large London law firm. The study found that selection, re-aggregation and forwarding of information by multiple actors gives rise to a complex sociotechnical distribution network. Knowledge management staff act as a layer of “intelligent filters” sensitive to complex, local information needs; their distribution decisions address multiple situational relevance factors in a situation fraught with information overload and restrictive time-pressures. Their decisions aim to optimise conflicting constraints of recall, precision and information quantity. Critical to this is the use of dynamic profile updates which propagate back through the network through formal and informal social interactions. This supports changes to situational relevance judgements and so allows the network to ‘self-tune’. These findings lead to design requirements, including that systems should support rapid assessment of information items against an individual’s interests; that it should be possible to organise information for different subsequent uses; and that there should be back-propagation from information consumers to providers, to tune the understanding of their information needs.     

Fields and pathways: Contrasting or complementary views of information seeking

This research contrasts two different conceptions, fields and pathways, of individual information behavior in context. These different approaches imply different relationships between actors and their information environments and, thus, encapsulate different views of the relationship between individual actions and contexts. We discuss these different theoretical views, then empirically compare and contrast them. The operationalization of these conceptions is based on different analytic treatments of the same raw data: a battery of three questions based on respondent’s unaided recall of the sources they would consult for information on inherited cancers, a particularly rich information seeking problem. These operationalizations are then analyzed in a nomological network of related concepts drawn from an omnibus survey of 882 adults. The results indicated four clusters for fields and 16 different pathways, indicating increased fragmentation of information environments, with different underlying logics and active ingredients, although the use of the Internet appears to be an emerging common theme. The analysis of the nomological network suggests that both approaches may have applications for particular problems. In the implications, we compare and contrast these approaches, discussing their significance for future methodological, analytical, and theoretical developments.     

Electronic information sharing in local government authorities: Factors influencing the decision-making process

Local Government Authorities (LGAs) are mainly characterised as information-intensive organisations. To satisfy their information requirements, effective information sharing within and among LGAs is necessary. Nevertheless, the dilemma of Inter-Organisational Information Sharing (IOIS) has been regarded as an inevitable issue for the public sector. Despite a decade of active research and practice, the field lacks a comprehensive framework to examine the factors influencing Electronic Information Sharing (EIS) among LGAs. The research presented in this paper contributes towards resolving this problem by developing a conceptual framework of factors influencing EIS in Government-to-Government (G2G) collaboration. By presenting this model, we attempt to clarify that EIS in LGAs is affected by a combination of environmental, organisational, business process, and technological factors and that it should not be scrutinised merely from a technical perspective. To validate the conceptual rationale, multiple case study based research strategy was selected. From an analysis of the empirical data from two case organisations, this paper exemplifies the importance (i.e. prioritisation) of these factors in influencing EIS by utilising the Analytical Hierarchy Process (AHP) technique. The intent herein is to offer LGA decision-makers with a systematic decision-making process in realising the importance (i.e. from most important to least important) of EIS influential factors. This systematic process will also assist LGA decision-makers in better interpreting EIS and its underlying problems. The research reported herein should be of interest to both academics and practitioners who are involved in IOIS, in general, and collaborative e-Government, in particular.     

Characterising and evaluating information seeking behaviour in a digital environment: Spotlight on the ‘bouncer’

The paper delineates and explains an emerging, but significant, form of digital information seeking behaviour among information consumers, which the authors have called ‘bouncing’. The evidence for this behaviour has emerged from five years of deep log analysis studies – an advanced form of transaction log analysis – of a wide range of users of digital information resources. Much of the evidence and discussion provided comes from the scholarly communication field. Two main bouncing metrics were applied in the log studies: site penetration, which is the number of items or pages viewed in a session, and return visits. The evidence shows that (1) a high proportion of people view just a few items or pages during a visit to a site and, (2) a high proportion of visitors either do not come back to the site or they did so infrequently. Typically those who penetrated a site least tended to return the least frequently. These people are termed ‘bouncers’. They bounce into the site and then bounce out again, presumably, to another site, as a high proportion of them do not appear to come back again. Possible explanations – negative and positive, for the form of behaviour are discussed.     

Meta-Circuit machine: Inferencing human collaborative relationships in heterogeneous information networks

Human collaborative relationship inference is a meaningful task for online social networks and is called link prediction in network science. Real-world networks contain multiple types of interacting components and can be modeled naturally as heterogeneous information networks (HINs). The current link prediction algorithms in HINs fail to effectively extract training samples from snapshots of HINs; moreover, they underutilise the differences between nodes and between meta-paths. Therefore, we propose a meta-circuit machine (MCM) that can learn and fuse node and meta-path features efficiently, and we use these features to inference the collaborative relationships in question-and-answer and bibliographic networks. We first utilise meta-circuit random walks to obtain training samples in which the basic idea is to perform biased meta-path random walks on the input and target network successively and then connect them. Then, a meta-circuit recurrent neural network (mcRNN) is designed for link prediction, which represents each node and meta-path by a dense vector and leverages an RNN to fuse the features of node sequences. Experiments on two real-world networks demonstrate the effectiveness of our framework. This study promotes the investigation of potential evolutionary mechanisms for collaborative relationships and offers practical guidance for designing more effective recommendation systems for online social networks.     

The information seeking behaviour of the users of digital scholarly journals

The article employs deep log analysis (DLA) techniques, a more sophisticated form of transaction log analysis, to demonstrate what usage data can disclose about information seeking behaviour of virtual scholars – academics, and researchers. DLA works with the raw server log data, not the processed, pre-defined and selective data provided by journal publishers. It can generate types of analysis that are not generally available via proprietary web logging software because the software filters out relevant data and makes unhelpful assumptions about the meaning of the data. DLA also enables usage data to be associated with search/navigational and/or user demographic data, hence the name ‘deep’. In this connection the usage of two digital journal libraries, those of EmeraldInsight, and Blackwell Synergy are investigated. The information seeking behaviour of nearly three million users is analyzed in respect to the extent to which they penetrate the site, the number of visits made, as well as the type of items and content they view. The users are broken down by occupation, place of work, type of subscriber (“Big Deal”, non-subscriber, etc.), geographical location, type of university (old and new), referrer link used, and number of items viewed in a session.     

Predicting semantic preferences in a socio-semantic system with collaborative filtering: A case study

This paper proposes collaborative filtering as a means to predict semantic preferences by combining information on social ties with information on links between actors and semantics. First, the authors present an overview of the most relevant collaborative filtering approaches, showing how they work and how they differ. They then compare three different collaborative filtering algorithms using articles published by New York Times journalists from 2003 to 2005 to predict preferences, where preferences refer to journalists’ inclination to use certain words in their writing. Results show that while preference profile similarities in an actor’s neighbourhood are a good predictor of her semantic preferences, information on her social network adds little to prediction accuracy.