Search (145 results, page 1 of 8)

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Abstract

Purpose Continuous knowledge sharing by active users, who are highly active in answering questions, is crucial to the sustenance of social question-and-answer (Q&A) sites. The purpose of this paper is to examine such knowledge sharing considering reason-based elaborate decision and habit-based automated cognitive processes. Design/methodology/approach To verify the research hypotheses, survey data on subjective intentions and web-crawled data on objective behavior are utilized. The sample size is 337 with the response rate of 27.2 percent. Negative binomial and hierarchical linear regressions are used given the skewed distribution of the dependent variable (i.e. the number of answers). Findings Both elaborate decision (linking satisfaction, intentions and continuance behavior) and automated cognitive processes (linking past and continuance behavior) are significant and substitutable. Research limitations/implications By measuring both subjective intentions and objective behavior, it verifies a detailed mechanism linking continuance intentions, past behavior and continuous knowledge sharing. The significant influence of automated cognitive processes implies that online knowledge sharing is habitual for active users. Practical implications Understanding that online knowledge sharing is habitual is imperative to maintaining continuous knowledge sharing by active users. Knowledge sharing trends should be monitored to check if the frequency of sharing decreases. Social Q&A sites should intervene to restore knowledge sharing behavior through personalized incentives. Originality/value This is the first study utilizing both subjective intentions and objective behavior data in the context of online knowledge sharing. It also introduces habit-based automated cognitive processes to this context. This approach extends the current understanding of continuous online knowledge sharing behavior.

Date

20. 1.2015 18:30:22

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Abstract

Social question-and-answer (Q&A) sites are platforms where users can freely ask, share, and rate knowledge. For the sustainable growth of social Q&A sites, maintaining askers is as critical as maintaining answerers. Based on motivational affordances theory and self-determination theory, this study explores the influence of the design elements of social Q&A sites (i.e., upvotes, downvotes, edits, user profile, and comments) on the survival of new askers. In addition, the moderating effect of having an alternative experience is examined. Online data on 25,000 new askers from the top five Q&A sites in the Technology category of the Stack Exchange network are analyzed using logistic regression. The results show that the competency- and autonomy-related design features of social Q&A sites motivate new askers to continue participating. Surprisingly, having an alternative experience shows a negative moderating effect, implying that alternative experiences increase switching costs in the Stack Exchange network. This study provides valuable insights for administrators of social Q&A sites as well as academics.

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Abstract

Great Sites are closely related to the residents' life, urban and rural development. In the process of rapid urbanization in China, the protection and utilization of Great Sites are facing unprecedented pressure. Effective knowl­edge organization with ontology and linked data of Great Sites is a prerequisite for their protection and utilization. In this paper, an interview is conducted to understand the users' awareness towards Great Sites to build the user-centered ontology. As for designing the Great Site ontology, firstly, the scope of Great Sites is determined. Secondly, CIDOC- CRM and OWL-Time Ontology are reused combining the results of literature research and user interviews. Thirdly, the top-level structure and the specific instances are determined to extract knowl­edge concepts of Great Sites. Fourthly, they are transformed into classes, data properties and object properties of the Great Site ontology. Later, based on the linked data technology, taking the Great Sites in Xi'an Area as an example, this paper uses D2RQ to publish the linked data set of the knowl­edge of the Great Sites and realize its opening and sharing. Semantic services such as semantic annotation, semantic retrieval and reasoning are provided based on the ontology.

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Abstract

Scientifically significant sites are the source of, and long-term repository for, considerable amounts of data-particularly in the natural sciences. However, the unique data practices of the researchers and resource managers at these sites have been relatively understudied. Through case studies of two scientifically significant sites (the hot springs at Yellowstone National Park and the fossil deposits at the La Brea Tar Pits), I developed rich descriptions of site-based research and data curation, and high-level data models of information classes needed to support integrative data reuse. Each framework treats the geospatial site and its changing natural characteristics as a distinct class of information; more commonly considered information classes such as observational and sampling data, and project metadata, are defined in relation to the site itself. This work contributes (a) case studies of the values and data needs for researchers and resource managers at scientifically significant sites, (b) an information framework to support integrative reuse at these sites, and (c) a discussion of data practices at scientifically significant sites.

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Abstract

As the prevalence of online misinformation grows increasingly apparent, our need to understand its spread becomes more essential. Trolling, in particular, may aggravate the spread of misinformation online. While many studies have investigated the negative impact of trolling and misinformation on social media, less attention has been devoted to the relationships between the two and their manifestation on social question and answer (SQA) sites. We examine the extent of and relationships between trolling and misinformation on SQA sites. Through content analysis of 8,401 posts (159 questions and 8,242 answers) from the Yahoo Answers! Politics & Government and Society & Culture categories, we identified levels of and relationships between misinformation and trolling. We find that trolling and misinformation tend to reinforce themselves and each other and that trolling and misinformation are more common in the Politics & Government category than in the Society & Culture category. Our study is among the first to consider the prevalence of and relationship between misinformation and trolling on SQA sites.

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Abstract

This study investigates the influence of individual and information characteristics on university students' information channel selection (that is, search engines, social question & answer sites, online health websites, and social networking sites) of online health information (OHI) for three different types of search tasks (factual, exploratory, and personal experience). Quantitative data were collected via an online questionnaire distributed to students on various postgraduate programs at a large UK university. In total, 291 responses were processed for descriptive statistics, Principal Component Analysis, and Poisson regression. Search engines are the most frequently used among the four channels of information discussed in this study. Credibility, ease of use, style, usefulness, and recommendation are the key factors influencing users' judgments of information characteristics (explaining over 62% of the variance). Poisson regression indicated that individuals' channel experience, age, student status, health status, and triangulation (comparing sources) as well as style, credibility, usefulness, and recommendation are substantive predictors for channel selection of OHI.

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Abstract

Conclusion There is a reason why Google Scholar and Web of Science/Scopus are kings of the hills in their various arenas. They have strong brand recogniton, a head start in development and a mass of eyeballs and users that leads to an almost virtious cycle of improvement. Competing against such well established competitors is not easy even when one has deep pockets (Microsoft) or a killer idea (scite). It will be interesting to see how the landscape will look like in 2030. Stay tuned for part II where I review each particular index.

Date

17.11.2020 12:22:59

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Content

Vgl. den Europol-Bericht "ChatGPT: The impact of Large Language Models on Law Enforcement" unter: https://www.europol.europa.eu/cms/sites/default/files/documents/Tech%20Watch%20Flash%20-%20The%20Impact%20of%20Large%20Language%20Models%20on%20Law%20Enforcement.pdf.

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Abstract

Purpose This article describes the third part of a three-stage study investigating the information behaviour of fans and fan communities, the first stage of which is described in the study by Price and Robinson (2017). Design/methodology/approach Using tag analysis as a method, a comparative case study was undertaken to explore three aspects of fan information behaviour: information gatekeeping; classifying and tagging and entrepreneurship and economic activity. The case studies took place on three sites used by fans-Tumblr, Archive of Our Own (AO3) and Etsy. Supplementary semi-structured interviews with site users were used to augment the findings with qualitative data. Findings These showed that fans used tags in a variety of ways quite apart from classification purposes. These included tags being used on Tumblr as meta-commentary and a means of dialogue between users, as well as expressors of emotion and affect towards posts. On AO3 in particular, fans had developed a practice called "tag wrangling" to mitigate the inherent "messiness" of tagging. Evidence was also found of a "hybrid market economy" on Etsy fan stores. From the study findings, a taxonomy of fan-related tags was developed. Research limitations/implications Findings are limited to the tagging practices on only three sites used by fans during Spring 2016, and further research on other similar sites are recommended. Longitudinal studies of these sites would be beneficial in understanding how or whether tagging practices change over time. Testing of the fan-tag taxonomy developed in this paper is also recommended. Originality/value This research develops a method for using tag analysis to describe information behaviour. It also develops a fan-tag taxonomy, which may be used in future research on the tagging practices of fans, which heretofore have been a little-studied section of serious leisure information users.

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Abstract

Diese Note legt dar, dass der sogenannte h-Index (Hirschs bibliometrischer Index) im Wesentlichen dieselbe Information wiedergibt wie die Gesamtanzahl von Zitationen von Publikationen einer Autorin oder eines Autors, also ein nutzloser bibliometrischer Index ist. Dies basiert auf einem faszinierenden Satz der Wahrscheinlichkeitstheorie, der hier ebenfalls erläutert wird.

Content

Vgl.: DOI: 10.1515/dmvm-2021-0050. Auch abgedruckt u.d.T.: 'Der h-Index - "ein nutzloser bibliometrischer Index"' in Open Password Nr. 1007 vom 06.12.2021 unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzM3NCwiZDI3MzMzOTEwMzUzIiwwLDAsMzQ4LDFd.

Object

h-index

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Abstract

Gratitude is a fundamental aspect of social interaction that positively influences emotional and social well-being. It is also crucial for promoting online community health by motivating participation. However, how gratitude occurs and can be encouraged in online communities is not yet well understood. This exploratory study investigated how online community users experience gratitude, focusing on how gratitude expression and acknowledgment occurs, can break down or can be reinforced. Semistructured Critical Incident interviews were conducted with 8 users of various online communities, including discussion and support groups, social Q&A sites, and review sites, eliciting 17 memorable examples of giving and receiving thanks online. The findings gave rise to a process model of gratitude in online communities-the "gratitude cycle," which provides a detailed, holistic understanding of the experience of gratitude online that can inform the design of online community platforms that aim to motivate users to perpetuate the cycle. An enriched understanding of gratitude in online communities can help ensure future platforms better support the expression and acknowledgment of thanks, encouraging participation.

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Abstract

Scholarly identity refers to endeavors by scholars to promote their reputation, work and networks using online platforms such as ResearchGate, Academia.edu and Twitter. This exploratory research investigates benefits and drawbacks of scholarly identity efforts and avenues for potential library support. Design/methodology/approach Data from 30 semi-structured phone interviews with faculty, doctoral students and academic librarians were qualitatively analyzed using the constant comparisons method (Charmaz, 2014) and Goffman's (1959, 1967) theoretical concept of impression management. Findings Results reveal that use of online platforms enables academics to connect with others and disseminate their research. scholarly identity platforms have benefits, opportunities and offer possibilities for developing academic library support. They are also fraught with drawbacks/concerns, especially related to confusion, for-profit models and reputational risk. Research limitations/implications This exploratory study involves analysis of a small number of interviews (30) with self-selected social scientists from one discipline (communication) and librarians. It lacks gender, race/ethnicity and geographical diversity and focuses exclusively on individuals who use social networking sites for their scholarly identity practices. Social implications Results highlight benefits and risks of scholarly identity work and the potential for adopting practices that consider ethical dilemmas inherent in maintaining an online social media presence. They suggest continuing to develop library support that provides strategic guidance and information on legal responsibilities regarding copyright. Originality/value This research aims to understand the benefits and drawbacks of Scholarly Identity platforms and explore what support academic libraries might offer. It is among the first to investigate these topics comparing perspectives of faculty, doctoral students and librarians.

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Abstract

Social cataloging websites, such as Goodreads, LibraryThing, and StoryGraph are widely popular with individuals who want to track their reading and read reviews. Goodreads is one of the most popular sites with 90 million registered users as of 2019. This paper studies a Goodreads cataloging rule, NOT A BOOK (NAB), through which users designate items as invalid to the site's scope while preserving some of their metadata. By reviewing NAB, we identify thirteen types of invalid items. We go on to discuss how these item types unevenly reflect the rule itself and the emergence of a "non-book" sense through social cataloging.

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Abstract

There is a mutual resemblance between the behavior of users of the Stack Exchange and the dynamics of the citations accumulation process in the scientific community, which enabled us to tackle the outwardly intractable problem of assessing the impact of introducing "negative" citations. Although the most frequent reason to cite an article is to highlight the connection between the 2 publications, researchers sometimes mention an earlier work to cast a negative light. While computing citation-based scores, for instance, the h-index, information about the reason why an article was mentioned is neglected. Therefore, it can be questioned whether these indices describe scientific achievements accurately. In this article we shed insight into the problem of "negative" citations, analyzing data from Stack Exchange and, to draw more universal conclusions, we derive an approximation of citations scores. Here we show that the quantified influence of introducing negative citations is of lesser importance and that they could be used as an indicator of where the attention of the scientific community is allocated.

Date

6. 1.2020 18:10:22

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Abstract

Der Data Citation Index (DCI) stellt eine durchsuchbare Sammlung bibliografischer Metadaten zu Forschungsdaten in Datensätzen und Datenstudien ausgewählter Repositorien dar. Der DCI deckt alle wissenschaftlichen Disziplinen ab.

Object

Data Citation Index

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Abstract

Friend request acceptance and information disclosure constitute 2 important privacy decisions for users to control the flow of their personal information in social network sites (SNSs). These decisions are greatly influenced by contextual characteristics of the request. However, the contextual influence may not be uniform among users with different levels of privacy concerns. In this study, we hypothesize that users with higher privacy concerns may consider contextual factors differently from those with lower privacy concerns. By conducting a scenario-based survey study and structural equation modeling, we verify the interaction effects between privacy concerns and contextual factors. We additionally find that users' perceived risk towards the requester mediates the effect of context and privacy concerns. These results extend our understanding about the cognitive process behind privacy decision making in SNSs. The interaction effects suggest strategies for SNS providers to predict user's friend request acceptance and to customize context-aware privacy decision support based on users' different privacy attitudes.

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Abstract

Question-and-answer (Q&A) sites improve access to information and ease transfer of knowledge. In recent years, they have grown in popularity and importance, enabling research on behavioral patterns of their users. We study the dynamics related to the casting of 7 M votes across a sample of 700 k posts on Stack Overflow, a large community of professional software developers. We employ log-Gaussian mixture modeling and Markov chains to formulate a simple yet elegant description of the considered phenomena. We indicate that the interevent times can naturally be clustered into 3 typical time scales: those which occur within hours, weeks, and months and show how the events become rarer and rarer as time passes. It turns out that the posts' popularity in a short period after publication is a weak predictor of its overall success, contrary to what was observed, for example, in case of YouTube clips. Nonetheless, the sleeping beauties sometimes awake and can receive bursts of votes following each other relatively quickly.

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Abstract

MEDLINE is the National Library of Medicine's (NLM) journal citation database. It contains over 28 million references to biomedical and life science journal articles, and a key feature of the database is that all articles are indexed with NLM Medical Subject Headings (MeSH). The library employs a team of MeSH indexers, and in recent years they have been asked to index close to 1 million articles per year in order to keep MEDLINE up to date. An important part of the MEDLINE indexing process is the assignment of articles to indexers. High quality and timely indexing is only possible when articles are assigned to indexers with suitable expertise. This article introduces the NLM indexer assignment dataset: a large dataset of 4.2 million indexer article assignments for articles indexed between 2011 and 2019. The dataset is shown to be a valuable testbed for expert matching and assignment algorithms, and indexer article assignment is also found to be useful domain-adaptive pre-training for the closely related task of reviewer assignment.

Date

22. 1.2023 18:49:49

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Abstract

RILM Index is a partially controlled vocabulary designated to index scholarly writings on music and related subjects, created and curated by Répertoire International de Littérature Musicale (RILM). It has been developed over 50 years and has served the music community as a primary research tool. This analytical review of the characteristics of RILM Index reveals several issues, related to the Index's history, that impinge on its usefulness. An in-progress thesaurus is presented as a possible solution to these issues. RILM Index, despite being imperfect, provides a foundation for developing an ontological structure for both indexing and information retrieval purposes.

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Source

https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN