Developing a platform-specific framework for web credibility assessment: A case of social Q&A sites

Social question-and-answer (Q&A) sites have the potential to serve as a useful source of online information based on their content-focused and collaborative nature. Although previous research has examined various attributes of high-quality information on social Q&A sites (e.g., best answers), relatively less attention has been paid to what affects users’ credibility assessments of information in the social Q&A context. The present study developed a social Q&A platform-specific framework for web credibility assessment, including 21 criteria under six types of web credibility, based on a literature analysis and case study of two online Q&A communities, Stack Exchange and Wikipedia Reference Desk. Using the selected sites’ policies and guidelines (n = 46) as the source of evidence, the case study revealed that content-related attributes (e.g., evidence-based, pertinence) were most frequently identified (12 of 21 criteria) as potential cues and heuristics for web credibility assessments of social Q&A sites, followed by author-related (five of 21; e.g., reputation) and design-related (four of 21; e.g., engaging design) factors. Design-related criteria were rarely included in previous models of web credibility on social Q&A or similar peer-knowledge production platforms. However, our findings showing that both Stack Exchange and Wikipedia Reference Desk have policies regarding all four design-related criteria in our framework—engaging design, moderation, design appropriateness, and ease of use—indicate the potential influences of design features on users’ web credibility assessment on social Q&A sites. Some differences emerged between the two cases, such as policies regarding the answerer's credentials or semantic accuracy that are present on Wikipedia Reference Desk but absent on Stack Exchange. Such differences in the sites’ policies reflect how they position themselves as social Q&A communities—Wikipedia, of which Wikipedia Reference Desk is a part, as an encyclopedia, and Stack Exchange as a community-based platform for learning, sharing knowledge, and building careers of users.     

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.     

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.     

Model-driven formative evaluation of exploratory search: A study under a sensemaking framework

The evaluation of exploratory search relies on the ongoing paradigm shift from focusing on the search algorithm to focusing on the interactive process. This paper proposes a model-driven formative evaluation approach, in which the goal is not the evaluation of a specific system, per se, but the exploration of new design possibilities. This paper gives an example of this approach where a model of sensemaking was used to inform the evaluation of a basic exploratory search system(s) in the context of a sensemaking task. The model suggested that, rather than just looking at simple search performance measures, we should examine closely the interwoven, interactive processes of both representation construction and information seeking. Participants were asked to make sense of an unfamiliar topic using an augmented query-based search system. The processes of representation construction and information seeking were captured and analyzed using data from experiment notes, interviews, and a system log. The data analysis revealed users’ sources of ideas for structuring representations and a tightly coupled relationship between search and representation construction in their exploratory searches. For example, users strategically used search to find useful structure ideas instead of just accumulating information facts. Implications for improving current search systems and designing new systems are discussed.     

An impressionistic mapping of information behavior with special attention to contexts, rationality, and ignorance

Recent years have seen an explosion of interest in human information behavior in part attributable to the rapid development of the Internet and associated information technologies. Concomitantly there has been substantial growth in theoretic frames, research, and substantive models. However, these approaches have often been fragmentary, dependent on the goals of disparate disciplines that are interested in differing aspects of information behavior. They often have been rooted in the most rational of contexts, libraries, where individuals come with a defined problem, or information technology systems, that have their own inherent logic. Attempts to extend this work to everyday life contexts often run into disquieting findings related to the benefits of ignorance and the seeming irrationality of human information behavior. A broader view of our social world leads us to richer policy implications for our work. We live in exciting times, in an increasingly flattened world, where the ability for people to assimilate information they find into coherent personal strategies is perhaps the critical modern survival skill.     

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.     

国外信息行为模型比较分析

通过文献梳理,选取国外有代表性的信息行为模型,包括Krikelas模型、Leckie模型、Bystrom Jarveliin模型、Savolainen模型J、ohnson模型进行介绍分析,并从研究关注焦点、研究视角、研究方法、主要变量等方面对模型进行简要的比较分析。     

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.     

Children’s interaction with cross-cultural and multilingual digital libraries. II. Information seeking,success, and affective experience

This paper reports the results of a study that investigated Arabic-speaking children’s interaction with the International Children’s Digital Library (ICDL) to find Arabic books on four tasks. Children’s information seeking activities was captured by using HyperCam software. Children’s success was assessed based on a measure the researchers developed. Children’s perceptions of and affective experience in using the ICDL was gathered through group interviews. Findings revealed that children’s information seeking behavior was characterized by browsing using a single function; that is, looking under “Arabic” from the Simple interface pull-down menu. Children were more successful on the fully self-generated, open-ended task than on the assigned and semi-assigned tasks. Children made suggestions for improving the Arabic collection and the design of the ICDL. The findings have implications for practitioners, researchers, and system designers.     

Classifying web genres in context: A case study documenting the web genres used by a software engineer

This case study analyzes the Internet-based resources that a software engineer uses in his daily work. Methodologically, we studied the web browser history of the participant, classifying all the web pages he had seen over a period of 12 days into web genres. We interviewed him before and after the analysis of the web browser history. In the first interview, he spoke about his general information behavior; in the second, he commented on each web genre, explaining why and how he used them. As a result, three approaches allow us to describe the set of 23 web genres obtained: (a) the purposes they serve for the participant; (b) the role they play in the various work and search phases; (c) and the way they are used in combination with each other. Further observations concern the way the participant assesses quality of web-based resources, and his information behavior as a software engineer.     

The role of digital information use on student performance and collaboration in marginal universities

Using technology to facilitate learning in universities and other higher education institutions (HEIs) has become common practice due to its ability to reduce barriers related to time and space in traditional learning environments. However, current literature mostly focuses on the use of the technology and not on the use of the information it conveys. Also, very few studies focus on technology adoption in universities and HEIs in developing countries, especially those in Africa. Thus, we propose a model that explains the changing information behaviors of students in this digital age and the effect this has on their learning outcomes. We collected questionnaire data from 303 students and analyzed the data using structural equation modelling partial least squares (SEM-PLS). We found that our proposed model explains 60.2 % of student satisfaction, 24.2 % of academic performance, 24.1 % of information sharing, and 19.8 % of their information exchange behavior. This study confirms that the use of digital information and its antecedent factors have significant effects on the college experience of students. This has several implications for information systems research and practice, especially in the design and assessment of technology use in learning environments.     

Applying a multi-dimensional hedonic concept of intrinsic motivation on social tagging tools: A theoretical model and empirical validation

Participation in and adding content to social tagging tools is important for these tools to achieve their purpose of classifying and organizing information. Users of social tagging tools are driven to participate and add tags by extrinsic and intrinsic motivation. Extrinsic motivation is dominating research as a main predictor of why users use information systems. Social tagging tools, as a subset of social media tools, are distinguished by their unique social aspect that makes intrinsic motivation a potential driver for users to add tags to content. Intrinsic motivation, when applied to social tagging tools, could entail many shades that represent different users’ motives for using such tools. In this paper, we add a rich concept of intrinsic motivation to include hedonism as a main predictor of users’ behavior on social tagging tools. We empirically validate a previously proposed theoretical model of three dimensional concepts of hedonism with three components describing individuals’ hedonic state when interacting with social tagging tools: explorability, curiosity, and enjoyment. After a robust and thorough data analysis using structured equation modeling, the results confirm our theoretical model and suggest using a richer concept of enjoyment to reflect a hedonic dimension when investigating intrinsic motivation with interactive social media tools. Our validated model could be the spark of new factors that have the potential to influence user acceptance of information systems in general and in social media tools. This research contributes to the development of attitude-behavior theories that could explain users’ acceptance of dynamic web     

A unifying and general account of fairness measurement in recommender systems

Fairness is fundamental to all information access systems, including recommender systems. However, the landscape of fairness definition and measurement is quite scattered with many competing definitions that are partial and often incompatible. There is much work focusing on specific – and different – notions of fairness and there exist dozens of metrics of fairness in the literature, many of them redundant and most of them incompatible. In contrast, to our knowledge, there is no formal framework that covers all possible variants of fairness and allows developers to choose the most appropriate variant depending on the particular scenario. In this paper, we aim to define a general, flexible, and parameterizable framework that covers a whole range of fairness evaluation possibilities. Instead of modeling the metrics based on an abstract definition of fairness, the distinctive feature of this study compared to the current state of the art is that we start from the metrics applied in the literature to obtain a unified model by generalization. The framework is grounded on a general work hypothesis: interpreting the space of users and items as a probabilistic sample space, two fundamental measures in information theory (Kullback–Leibler Divergence and Mutual Information) can capture the majority of possible scenarios for measuring fairness on recommender system outputs. In addition, earlier research on fairness in recommender systems could be viewed as single-sided, trying to optimize some form of equity across either user groups or provider/procurer groups, without considering the user/item space in conjunction, thereby overlooking/disregarding the interplay between user and item groups. Instead, our framework includes the notion of statistical independence between user and item groups. We finally validate our approach experimentally on both synthetic and real data according to a wide range of state-of-the-art recommendation algorithms and real-world data sets, showing that with our framework we can measure fairness in a general, uniform, and meaningful way.     

Epistemic modality: From uncertainty to certainty in the context of information seeking as interactions with texts

This article introduces a type of uncertainty that resides in textual information and requires epistemic interpretation on the information seeker’s part. Epistemic modality, as defined in linguistics and natural language processing, is a writer’s estimation of the validity of propositional content in texts. It is an evaluation of chances that a certain hypothetical state of affairs is true, e.g., definitely true or possibly true. This research shifts attention from the uncertainty–certainty dichotomy to a gradient epistemic continuum of absolute, high, moderate, low certainty, and uncertainty. An analysis of a New York Times dataset showed that epistemically modalized statements are pervasive in news discourse and they occur at a significantly higher rate in editorials than in news reports. Four independent annotators were able to recognize a gradation on the continuum but individual perceptions of the boundaries between levels were highly subjective. Stricter annotation instructions and longer coder training improved intercoder agreement results. This paper offers an interdisciplinary bridge between research in linguistics, natural language processing, and information seeking with potential benefits to design and implementation of information systems for situations where large amounts of textual information are screened manually on a regular basis, for instance, by professional intelligence or business analysts.     

科技项目立项过程中申报人、管理者、评审者之间的博弈分析

在科技项目立项过程中,由于申报人、管理者、评审者追求各自利益最大化,存在申报人寻租,管理者、项目评审者接受租金而不履行职责现象,导致许多关系项目、腐败项目出现。要从加大奖惩力度、创新评审制度、加强管理部门对评审委员会的监督等方面遏制寻租行为,确保立项的公正、科学、合理。     

Information Systems and Developing Countries: Failure, Success, and Local Improvisations

This article presents evidence that--alongside the successes-- many information systems in developing countries can be categorized as failing either totally or partially. It then develops a new model that seeks to explain the high rates of failure. The model draws on contingency theory in order to advance the notion of design-actuality gaps: the match or mismatch between IS designs and local user actuality. This helps identify two high-risk archetypes that affect IS in developing countries: country context gaps and hard-soft gaps. The model is also of value in explaining the constraints that exist to local IS improvisations in developing countries. Overall, the article shows how model and theory help understand IS cases in developing countries, and equally, how those cases provide valuable data to help develop IS models and theories.     

科学使用科学咨询是提升决策公信力的关键——来自英国的经验启示

科学的、民主的公共决策流程可分为确定政策议题、制定具体政策、推行实施政策和评估修订政策四个环节。科学咨询贯穿于整个决策流程并成为确保决策质量和提高决策公信力的关键。当前我国公共决策急需一个关于如何科学使用科学咨询的宏观指导文件。本文介绍了英国科学办公室分别于1997、2000、2005、2010年颁布实施4版本有关科学咨询和政策制定的指导方针的概要情况,阐述了"英国经验"给我国公共决策机制改进带来的三点启示:一是尽早制定有关如何在公共决策过程中更好使用科学和工程咨询的规范性文件;二是明确相关管理机构;三是在决策实践中借鉴英国指导方针的部分核心理念、关键原则和有益做法。     

Multidimensional relevance: Prioritized aggregation in a personalized Information Retrieval setting

A new model for aggregating multiple criteria evaluations for relevance assessment is proposed. An Information Retrieval context is considered, where relevance is modeled as a multidimensional property of documents. The usefulness and effectiveness of such a model are demonstrated by means of a case study on personalized Information Retrieval with multi-criteria relevance. The following criteria are considered to estimate document relevance: aboutness, coverage, appropriateness, and reliability.     

Information avoidance behavior on social network sites: Information irrelevance,overload, and the moderating role of time pressure

Drawing on the stressor-strain-outcome framework, this study investigates how information irrelevance and overload induce social network fatigue, and the relationship of these variables to users’ information avoidance behavior. It also examines the conditions under which social network fatigue is more likely to be translated into information avoidance behavior. The analysis of data collected from 341 users of WeChat Moments suggests that information irrelevance directly leads to information avoidance behavior, and social media fatigue as a mediator partially mediates the impact of information overload on information avoidance behavior and fully mediates the impact of social overload on information avoidance behavior. Furthermore, time pressure strengthens the effect of social network fatigue on information avoidance behavior. This study fulfills the identified need for an in-depth investigation of actual discontinuous behavior in social network services (SNSs) by investigating information avoidance behavior and its antecedents. The findings provide SNSs providers with guidelines on how to manage users’ behavior so that they remain active users of the SNSs.