Search (183 results, page 1 of 10)

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Abstract

We discuss the needs of a knowledge organization scheme for supporting Web-based software applications. We show how it differs from traditional knowledge organization schemes due to the virtual, dynamic, ad-hoc, userspecific and application-specific nature of Web-based knowledge. The sheer size of Web resources also adds to the complexity of organizing knowledge on the Web. As such, a standard, global scheme such as a single ontology for classifying and organizing all Web-based content is unrealistic. There is nevertheless a strong and immediate need for effective knowledge organization schemes to improve the efficiency and effectiveness of Web-based applications. In this context, we propose a novel knowledge organization scheme wherein concepts in the ontology of a domain are semantically interlinked with specific pieces of Web-based content using a rich hyper-linking structure known as Superlinks with well-defined semantic roles. We illustrate how such a knowledge organization scheme improves the efficiency and effectiveness of a Web-based e-commerce retail store.

Source

Categories, contexts and relations in knowledge organization: Proceedings of the Twelfth International ISKO Conference 6-9 August 2012, Mysore, India. Eds.: Neelameghan, A. u. K.S. Raghavan

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Abstract

Twitter, Facebook, and other related systems that we call social awareness streams are rapidly changing the information and communication dynamics of our society. These systems, where hundreds of millions of users share short messages in real time, expose the aggregate interests and attention of global and local communities. In particular, emerging temporal trends in these systems, especially those related to a single geographic area, are a significant and revealing source of information for, and about, a local community. This study makes two essential contributions for interpreting emerging temporal trends in these information systems. First, based on a large dataset of Twitter messages from one geographic area, we develop a taxonomy of the trends present in the data. Second, we identify important dimensions according to which trends can be categorized, as well as the key distinguishing features of trends that can be derived from their associated messages. We quantitatively examine the computed features for different categories of trends, and establish that significant differences can be detected across categories. Our study advances the understanding of trends on Twitter and other social awareness streams, which will enable powerful applications and activities, including user-driven real-time information services for local communities.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.5, S.902-918

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Abstract

Purpose - This paper is the final one in a series which has tried to give an overview of so-called transformational areas of digital library technology. The aim has been to assess how much real transformation these applications can bring about, in terms of creating genuine user benefit and also changing everyday library practice. Design/methodology/approach - The paper provides a summary of some of the legal and ethical issues associated with web 2.0 applications in libraries, associated with a brief retrospective view of some relevant literature. Findings - Although web 2.0 innovations have had a massive impact on the larger World Wide Web, the practical impact on library service delivery has been limited to date. What probably can be termed transformational in the effect of web 2.0 developments on library and information work is their effect on some underlying principles of professional practice. Research limitations/implications - The legal and ethical challenges of incorporating web 2.0 platforms into mainstream institutional service delivery need to be subject to further research, so that the risks associated with these innovations are better understood at the strategic and policy-making level. Practical implications - This paper makes some recommendations about new principles of library and information practice which will help practitioners make better sense of these innovations in their overall information environment. Social implications - The paper puts in context some of the more problematic social impacts of web 2.0 innovations, without denying the undeniable positive contribution of social networking to the sphere of human interactivity. Originality/value - This paper raises some cautionary points about web 2.0 applications without adopting a precautionary approach of total prohibition. However, none of the suggestions or analysis in this piece should be considered to constitute legal advice. If such advice is required, the reader should consult appropriate legal professionals.

Date

22. 1.2011 17:54:04

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Abstract

Many discussions exist regarding the credibility of information on the Internet. Similar discussions happen on the interpretation of social scientific research data, for which information triangulation has been proposed as a useful method. In this article, we explore a design theory-consisting of a kernel theory, meta-requirements, and meta-designs-for software and services that triangulate Internet information. The kernel theory identifies 5 triangulation methods based on Churchman's inquiring systems theory and related meta-requirements. These meta-requirements are used to search for existing software and services that contain design features for Internet information triangulation tools. We discuss a prototyping study of the use of an information triangulator among 72 college students and how their use contributes to their opinion formation. From these findings, we conclude that triangulation tools can contribute to opinion formation by information consumers, especially when the tool is not a mere fact checker but includes the search and delivery of alternative views. Finally, we discuss other empirical propositions and design propositions for an agenda for triangulator developers and researchers. In particular, we propose investment in theory triangulation, that is, tools to automatically detect ethically and theoretically alternative information and views.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.4, S.684-701

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Abstract

Online communities are becoming an important tool in the communication and participation processes in our society. However, the most widespread applications are difficult to use for people with disabilities, or may involve some risks if no previous training has been undertaken. This work describes a novel social network for cognitively disabled people along with a clustering-based method for modeling activity and socialization processes of its users in a noninvasive way. This closed social network is specifically designed for people with cognitive disabilities, called Guremintza, that provides the network administrators (e.g., social workers) with two types of reports: summary statistics of the network usage and behavior patterns discovered by a data mining process. Experiments made in an initial stage of the network show that the discovered patterns are meaningful to the social workers and they find them useful in monitoring the progress of the users.

Date

22. 1.2016 12:02:26

Source

Journal of the Association for Information Science and Technology. 67(2016) no.2, S.305-317

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Abstract

Our consumption of online information is mediated by filtering, ranking, and recommendation algorithms that introduce unintentional biases as they attempt to deliver relevant and engaging content. It has been suggested that our reliance on online technologies such as search engines and social media may limit exposure to diverse points of view and make us vulnerable to manipulation by disinformation. In this article, we mine a massive data set of web traffic to quantify two kinds of bias: (i) homogeneity bias, which is the tendency to consume content from a narrow set of information sources, and (ii) popularity bias, which is the selective exposure to content from top sites. Our analysis reveals different bias levels across several widely used web platforms. Search exposes users to a diverse set of sources, while social media traffic tends to exhibit high popularity and homogeneity bias. When we focus our analysis on traffic to news sites, we find higher levels of popularity bias, with smaller differences across applications. Overall, our results quantify the extent to which our choices of online systems confine us inside "social bubbles."

Source

Journal of the Association for Information Science and Technology. 70(2019) no.3, S.218-229

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Abstract

This article explores the need for libraries to algorithmically access and manipulate the world's largest API: the Internet. The billions of pages on the 'Internet API' (HTTP, HTML, CSS, XPath, DOM, etc.) are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn programming language with extensive packages and community support for web page automation. Four packages (Urllib, Selenium, BeautifulSoup, Scrapy) in Python can automate almost any web page for all sized projects. An example warrant data project is explained to illustrate how well Python packages can manipulate web pages to create meaning through assembling custom datasets.

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Abstract

Online discussion forums have become a popular medium for users to discuss with and seek information from other users having similar interests. A typical discussion thread consists of a sequence of posts posted by multiple users. Each post in a thread serves a different purpose providing different types of information and, thus, may not be equally useful for all applications. Identifying the purpose and nature of each post in a discussion thread is thus an interesting research problem as it can help in improving information extraction and intelligent assistance techniques. We study the problem of classifying a given post as per its purpose in the discussion thread and employ features based on the post's content, structure of the thread, behavior of the participating users, and sentiment analysis of the post's content. We evaluate our approach on two forum data sets belonging to different genres and achieve strong classification performance. We also analyze the relative importance of different features used for the post classification task. Next, as a use case, we describe how the post class information can help in thread retrieval by incorporating this information in a state-of-the-art thread retrieval model.

Date

22. 1.2016 11:50:46

Source

Journal of the Association for Information Science and Technology. 67(2016) no.2, S.276-288

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Abstract

Webcasting systems were developed to provide remote access in real-time to live events. Today, these systems have an additional requirement: to accommodate the "second life" of webcasts as archival information objects. Research to date has focused on facilitating the production and storage of webcasts as well as the development of more interactive and collaborative multimedia tools to support the event, but research has not examined how people interact with a webcasting system to access and use the contents of those archived events. Using an experimental design, this study examined how 16 typical users interact with a webcasting system to respond to a set of information tasks: selecting a webcast, searching for specific information, and making a gist of a webcast. Using several data sources that included user actions, user perceptions, and user explanations of their actions and decisions, the study also examined the strategies employed to complete the tasks. The results revealed distinctive system-use patterns for each task and provided insights into the types of tools needed to make webcasting systems better suited for also using the webcasts as information objects.

Date

22. 1.2011 14:16:14

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.343-362

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Abstract

The degree of structure of Web content is the determining factor for the types of functionality that search engines can provide. The more well structured the Web content is, the easier it is for search engines to understand Web content and provide advanced functionality, such as faceted filtering or the aggregation of content from multiple Web sites, based on this understanding. Today, most Web sites are generated from structured data that is stored in relational databases. Thus, it does not require too much extra effort for Web sites to publish this structured data directly on the Web in addition to HTML pages, and thus help search engines to understand Web content and provide improved functionality. An early approach to realize this idea and help search engines to understand Web content is Microformats, a technique for markingup structured data about specific types on entities-such as tags, blog posts, people, or reviews-within HTML pages. As Microformats are focused on a few entity types, the World Wide Web Consortium (W3C) started in 2004 to standardize RDFa as an alternative, more generic language for embedding any type of data into HTML pages. Today, major search engines such as Google, Yahoo, and Bing extract Microformat and RDFa data describing products, reviews, persons, events, and recipes from Web pages and use the extracted data to improve the user's search experience. The search engines have started to aggregate structured data from different Web sites and augment their search results with these aggregated information units in the form of rich snippets which combine, for instance, data This chapter gives an overview of the topology of the Web of Data that has been created by publishing data on the Web using the microformats RDFa, Microdata and Linked Data publishing techniques.

Series

Data-centric systems and applications

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RSWK

Soziale Software / World Wide Web 2.0 / Kongress / Düsseldorf <2012>

Subject

Soziale Software / World Wide Web 2.0 / Kongress / Düsseldorf <2012>

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Abstract

Purpose The purpose of this paper is to investigate the relationship between internet filtering, emotions and information-seeking behaviour. Design/methodology/approach In total, 15 postgraduate students at an Iranian university participated in the study which involved a questionnaire, search tasks with think aloud narratives, and interviews. Findings Internet content filtering results in some changes in the information-seeking behaviour of users. Users who face website blocking use a variety of methods to bypass filtering, mostly by using anti-filter software. Filtering encourages users to use channels such as social networking services to share resources and it increases the use of library material by some of the users. Users who face filtering during their search are more likely to visit more pages of results and click on more hits in the results, unlike users who do not experience filtering who rarely go past the first page. Blocking users' access to content stimulates their curiosity and they become more determined to access the content. In terms of the affective aspect, filtering causes several negative emotions (e.g. anger, disgust, sadness and anxiety) and the main reason for these emotions is not the inability to access information but the feeling of being controlled and not having freedom. Research limitations/implications The study was limited to a small number of postgraduate students in social sciences and not generalisable to all user groups. The implication is that in countries where filtering is used, libraries can play an important role in serving users and reducing users negative emotions, especially if libraries can take advantage of technologies such as social media for their services. Originality/value This is first study to address the effects of internet filtering on information-seeking behaviour and emotions. The study shows that internet filtering causes negative emotions and results in some changes in information-seeking behaviour.

Date

20. 1.2015 18:30:22

Source

Aslib journal of information management. 69(2017) no.4, S.408-425

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Abstract

Research indicates that migrants' social media usage in Ireland enables a background awareness of friends and acquaintances that supports bonding capital and transnational communities in ways not previously reported. Interview data from 65 Polish and Filipino non-nationals in Ireland provide evidence that their social media practices enable a shared experience with friends and relations living outside Ireland that is not simply an elaboration of the social relations enabled by earlier Internet applications. Social media usage enables a passive monitoring of others, through the circulation of voice, video, text, and pictures, that maintains a low level mutual awareness and supports a dispersed community of affinity. This ambient, or background, awareness of others enhances and supports dispersed communities by contributing to bonding capital. This may lead to significant changes in the process of migration by slowing down the process of integration and participation in host societies while also encouraging continual movement of migrants from one society to another.

Source

Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1075-1086

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Abstract

The Digital Public Library of America brings together the riches of America's libraries, archives, and museums, and makes them freely available to the world. In order to do this, DPLA has had to build elements of the national digital platform to connect to those institutions and to serve their digitized materials to audiences. In this article, we detail the construction of two critical elements of our work: the decentralized national network of "hubs," which operate in states across the country; and a version of the Hydra repository software that is tailored to the needs of our community. This technology and the organizations that make use of it serve as the foundation of the future of DPLA and other projects that seek to take advantage of the national digital platform.

Object

Digital Public Library of America

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Abstract

The global popularity of microblogs has led to an increasing accumulation of large volumes of text data on microblogging platforms such as Twitter. These corpora are untapped resources to understand social expressions on diverse subjects. Microblog analysis aims to unlock the value of such expressions by discovering insights and events of significance hidden among swathes of text. Besides velocity; diversity of content, brevity, absence of structure and time-sensitivity are key challenges in microblog analysis. In this paper, we propose an unsupervised incremental machine learning and event detection technique to address these challenges. The proposed technique separates a microblog discussion into topics to address the key problem of diversity. It maintains a record of the evolution of each topic over time. Brevity, time-sensitivity and unstructured nature are addressed by these individual topic pathways which contribute to generate a temporal, topic-driven structure of a microblog discussion. The proposed event detection method continuously monitors these topic pathways using multiple domain-independent event indicators for events of significance. The autonomous nature of topic separation, topic pathway generation, new topic identification and event detection, appropriates the proposed technique for extensive applications in microblog analysis. We demonstrate these capabilities on tweets containing #microsoft and tweets containing #obama.

Source

Journal of the Association for Information Science and Technology. 68(2017) no.10, S.2394-2411

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Abstract

Today, people perform many types of tasks on the web, including those that require multiple web sessions. In this article, we build on research about web tasks and present an in-depth evaluation of the types of tasks people perform on the web over multiple web sessions. Multisession web tasks are goal-based tasks that often contain subtasks requiring more than one web session to complete. We will detail the results of two longitudinal studies that we conducted to explore this topic. The first study was a weeklong web-diary study where participants self-reported information on their own multisession tasks. The second study was a monthlong field study where participants used a customized version of Firefox, which logged their interactions for both their own multisession tasks and their other web activity. The results from both studies found that people perform eight different types of multisession tasks, that these tasks often consist of several subtasks, that these lasted different lengths of time, and that users have unique strategies to help continue the tasks which involved a variety of web and browser tools such as search engines and bookmarks and external applications such as Notepad or Word. Using the results from these studies, we have suggested three guidelines for developers to consider when designing browser-tool features to help people perform these types of tasks: (a) to maintain a list of current multisession tasks, (b) to support multitasking, and (c) to manage task-related information between sessions.

Source

Journal of the American Society for Information Science and Technology. 63(2012) no.6, S.1183-1197

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Abstract

Since its foundation in 2006, Twitter has enjoyed a meteoric rise in popularity, currently boasting over 500 million users. Its short text nature means that the service is open to a variety of different usage patterns, which have evolved rapidly in terms of user base and utilization. Prior work has categorized Twitter users, as well as studied the use of lists and re-tweets and how these can be used to infer user profiles and interests. The focus of this article is on studying why and how Twitter users mark tweets as "favorites"-a functionality with currently poorly understood usage, but strong relevance for personalization and information access applications. Firstly, manual analysis and classification are carried out on a randomly chosen set of favorited tweets, which reveal different approaches to using this functionality (i.e., bookmarks, thanks, like, conversational, and self-promotion). Secondly, an automatic favorites classification approach is proposed, based on the categories established in the previous step. Our machine learning experiments demonstrate a high degree of success in matching human judgments in classifying favorites according to usage type. In conclusion, we discuss the purposes to which these data could be put, in the context of identifying users' patterns of interests.

Source

Journal of the Association for Information Science and Technology. 67(2016) no.1, S.17-25

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Abstract

Social media have transformed social interactions and now look set to transform workplace communications. In this exploratory study, we investigate how employees use and get value from a variety of social networking technologies. The context of this research is 4 software firms located in China. Notwithstanding differences in corporate attitudes toward social networking, we identify common themes in the way Web 2.0 technologies are leveraged as value is created by employees at all levels. We draw on the communication ecology framework to analyze the application of various technologies. We inductively develop 5 propositions that describe how social networking technologies contribute directly to horizontal and vertical communication in organizations, and ultimately to individual, team, and organizational performance. Implications for research and practice are discussed.

Source

Journal of the Association for Information Science and Technology. 65(2014) no.10, S.2035-2047

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Abstract

This is a practical guide to using web metrics to measure impact and demonstrate value. The web provides an opportunity to collect a host of different metrics, from those associated with social media accounts and websites to more traditional research outputs. This book is a clear guide for library and information professionals as to what web metrics are available and how to assess and use them to make informed decisions and demonstrate value. As individuals and organizations increasingly use the web in addition to traditional publishing avenues and formats, this book provides the tools to unlock web metrics and evaluate the impact of this content. The key topics covered include: bibliometrics, webometrics and web metrics; data collection tools; evaluating impact on the web; evaluating social media impact; investigating relationships between actors; exploring traditional publications in a new environment; web metrics and the web of data; the future of web metrics and the library and information professional. The book will provide a practical introduction to web metrics for a wide range of library and information professionals, from the bibliometrician wanting to demonstrate the wider impact of a researcher's work than can be demonstrated through traditional citations databases, to the reference librarian wanting to measure how successfully they are engaging with their users on Twitter. It will be a valuable tool for anyone who wants to not only understand the impact of content, but demonstrate this impact to others within the organization and beyond.

Content

1. Introduction. MetricsIndicators -- Web metrics and Ranganathan's laws of library science -- Web metrics for the library and information professional -- The aim of this book -- The structure of the rest of this book -- 2. Bibliometrics, webometrics and web metrics. Web metrics -- Information science metrics -- Web analytics -- Relational and evaluative metrics -- Evaluative web metrics -- Relational web metrics -- Validating the results -- 3. Data collection tools. The anatomy of a URL, web links and the structure of the web -- Search engines 1.0 -- Web crawlers -- Search engines 2.0 -- Post search engine 2.0: fragmentation -- 4. Evaluating impact on the web. Websites -- Blogs -- Wikis -- Internal metrics -- External metrics -- A systematic approach to content analysis -- 5. Evaluating social media impact. Aspects of social network sites -- Typology of social network sites -- Research and tools for specific sites and services -- Other social network sites -- URL shorteners: web analytic links on any site -- General social media impact -- Sentiment analysis -- 6. Investigating relationships between actors. Social network analysis methods -- Sources for relational network analysis -- 7. Exploring traditional publications in a new environment. More bibliographic items -- Full text analysis -- Greater context -- 8. Web metrics and the web of data. The web of data -- Building the semantic web -- Implications of the web of data for web metrics -- Investigating the web of data today -- SPARQL -- Sindice -- LDSpider: an RDF web crawler -- 9. The future of web metrics and the library and information professional. How far we have come -- The future of web metrics -- The future of the library and information professional and web metrics.

RSWK

Bibliometrie / Semantic Web / Soziale Software

Subject

Bibliometrie / Semantic Web / Soziale Software

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Abstract

The quality of online health information for consumers has been a critical issue that concerns all stakeholders in healthcare. To gain an understanding of how quality is evaluated, this systematic review examined 165 articles in which researchers evaluated the quality of consumer-oriented health information on the web against predefined criteria. It was found that studies typically evaluated quality in relation to the substance and formality of content, as well as to the design of technological platforms. Attention to design, particularly interactivity, privacy, and social and cultural appropriateness is on the rise, which suggests the permeation of a user-centered perspective into the evaluation of health information systems, and a growing recognition of the need to study these systems from a social-technical perspective. Researchers used many preexisting instruments to facilitate evaluation of the formality of content; however, only a few were used in multiple studies, and their validity was questioned. The quality of content (i.e., accuracy and completeness) was always evaluated using proprietary instruments constructed based on medical guidelines or textbooks. The evaluation results revealed that the quality of health information varied across medical domains and across websites, and that the overall quality remained problematic. Future research is needed to examine the quality of user-generated content and to explore opportunities offered by emerging new media that can facilitate the consumer evaluation of health information.

Source

Journal of the Association for Information Science and Technology. 66(2015) no.10, S.2071-2084