Search (31 results, page 2 of 2)

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Abstract

Twitter is utilized by many, including professional businesses and organizations; however, there are very few studies on how other entities interact with these organizations in the Twittersphere. This article presents a study that investigates tweets related to 5 major library and information science (LIS) professional organizations in the United States. This study applies a systematic tweets analysis framework, including descriptive analytics, network analytics, and co-word analysis of hashtags. The findings shed light on user engagement with LIS professional organizations and the trending discussion topics on Twitter, which is valuable for enabling more successful social media use and greater influence.

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Abstract

Digital exclusion is high on the international agenda and covers a variety of inequalities in access to and use of digital technologies, and in the skills and motivation needed for their adoption. This research contributes to the discussion on solving digital exclusion issues by addressing the emergent roles and challenges of Lithuanian public libraries in reducing the digital divide. The article combines a multilevel model of the digital divide with the concept of business idea and analyzes the future scenarios of Lithuanian public libraries. The findings highlight the public libraries' importance in conducting training, consultancy, and experiential learning to stimulate digital inclusion. Potentially, libraries can motivate users to adopt digital technologies, but this role is still not sufficiently visible. The findings show that libraries face challenges of redefining their social value and obtaining the sustaining funds, skills, and infrastructure necessary for digital inclusion programs. However, they can use collaboration networks, effective cost management, and external expertise to overcome these obstacles.

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Abstract

Purpose This study aims to develop an in-depth understanding of the underlying dynamics of an emergent shared information practice within a Facebook group, and the resources the group develops to sustain this practice. Design/methodology/approach In-depth semi-structured interviews were carried out with twenty members from the group. The findings are based on comparative analysis combined with narrative analysis and were interpreted using theories of situated learning and Community of Practice. Findings The study shows that although members of this multicultural mothers group endorsed different, sometimes opposing parenting practices, the group had to find common ground when sharing information. Managing these challenges was key to maintaining the group as an open information resource for all members. The group produced a shared repertoire of resources to maintain its activities, including norms, rules, shared understandings, and various monitoring activities. The shared online practice developed by the community is conceptualised in this article as an information practice requiring shared, community-specific understandings of what, when, and how information can or should be sought or shared in ways that are valued in this specific community. The findings show that this shared information practice is not static but continually evolves as members negotiate what is, or not, important for the group. Originality/value The research provides novel insights into the underlying dynamics of the emergence, management, and sustainability of a shared information practice within a contemporary mothers group on Facebook.

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Abstract

Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture "crowd wisdom" and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user-generated stock predictions, based upon which they can make better investment decisions.

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Abstract

In using the Internet to solve everyday problems, older adults tend to find fewer correct answers compared to younger adults. Some authors have argued that these differences could be explained by age-related decline. The present study aimed to analyze the relationship between web-searching navigation and users' age, considering the Intelligence Quotient (IQ) and frequency of Internet and personal computer use. The intent was to identify differences due to age and not to other variables (that is, cognitive decline, expertise with the tool). Eighteen students (18-30?years) and 18 older adults (60-75?years) took part in the experiment. Inclusion criteria were the frequent use of computers and a web-searching activity; the older adults performed the Mini-Mental State Examination to exclude cognitive impairment. Participants were requested to perform the Kaufman Brief Intelligence Test 2nd ed. to measure their IQ level, and nine everyday web-searching tasks of differing complexity. The results showed that older participants spent more time on solving tasks than younger participants, but with the same accuracy as young people. Furthermore, nonverbal IQ improved performance in terms of time among the older participants. Age did not influence web-searching behavior in users with normal expertise and intelligence.

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Abstract

Email is the primary method of communication with authors of scientific publications. This study sought to measure the reliability, over time, of contact email addresses from biomedical publications, particularly depending on email type. Emails were written to randomly selected email addresses from publications in MEDLINE, and email bounce rates were modeled probabilistically. The use of personal email addresses was quantified and compared to the use of other types of email addresses. Eighteen percent of authors' contact email addresses in MEDLINE were estimated to be invalid. A steadily growing share of email addresses was personal: 32% of all new email addresses in MEDLINE in 2018 were of this kind. These email addresses were less likely to be invalid than email addresses from other types of providers. While the percentage of invalid email addresses was significant, it was lower than previously estimated. Personal email addresses are taking an increasingly more important role by supplying more reliable email addresses to scientists. To mitigate the problem of invalid email addresses, institutions should provide email forwarding, scientific directories should offer the possibility of contacting authors, or scientific authors should use more stable email addresses.

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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

Web search is commonly used by fact checking systems as a source of evidence for claim verification. In this work, we demonstrate that the task of retrieving pages useful for fact checking, called evidential pages, is indeed different from the task of retrieving topically relevant pages that are typically optimized by search engines; thus, it should be handled differently. We conduct a comprehensive study on the performance of retrieving evidential pages over a test collection we developed for the task of re-ranking Web pages by usefulness for fact-checking. Results show that pages (retrieved by a commercial search engine) that are topically relevant to a claim are not always useful for verifying it, and that the engine's performance in retrieving evidential pages is weakly correlated with retrieval of topically relevant pages. Additionally, we identify types of evidence in evidential pages and some linguistic cues that can help predict page usefulness. Moreover, preliminary experiments show that a retrieval model leveraging those cues has a higher performance compared to the search engine. Finally, we show that existing systems have a long way to go to support effective fact checking. To that end, our work provides insights to guide design of better future systems for the task.

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Abstract

Wikimedia Deutschland hat rund 150 hauptamtliche Mitarbeitende. Von den Erlösen aber kauft sich niemand eine Yacht. Ein Gastbeitrag. Online-Plattformen dominieren in vielen Bereichen unser Leben. Wie wir einkaufen, wie wir miteinander kommunizieren, wie wir Informationen sammeln - all das wird von einigen wenigen kommerziellen Plattformen mitbestimmt. Längst drängt sich der Eindruck auf, das Netz sei durchkommerzialisiert. Dabei gibt es sie noch: einige wenige Projekte im Netz, die nicht auf Profit ausgerichtet sind, sondern dem Gemeinwohl zugutekommen.

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Abstract

The spread of misinformation on social media has become a major societal issue during recent years. In this work, we used the ongoing COVID-19 pandemic as a case study to systematically investigate factors associated with the spread of multi-topic misinformation related to one event on social media based on the heuristic-systematic model. Among factors related to systematic processing of information, we discovered that the topics of a misinformation story matter, with conspiracy theories being the most likely to be retweeted. As for factors related to heuristic processing of information, such as when citizens look up to their leaders during such a crisis, our results demonstrated that behaviors of a political leader, former US President Donald J. Trump, may have nudged people's sharing of COVID-19 misinformation. Outcomes of this study help social media platform and users better understand and prevent the spread of misinformation on social media.

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Abstract

The rapid and wide dissemination of up-to-date, localized information is a central issue during disasters. Being attributed to the original 140-character length, Twitter provides its users with quick-posting and easy-forwarding features that facilitate the timely dissemination of warnings and alerts. However, a concern arises with respect to the terseness of tweets that restricts the amount of information conveyed in a tweet and thus increases a tweet's uncertainty. We tackle such concerns by proposing entropy as a measure for a tweet's uncertainty. Based on the perspectives of Uncertainty Reduction Theory (URT), we theorize that the more uncertain information of a disaster tweet, the higher the entropy, which will lead to a lower retweet count. By leveraging the statistical and predictive analyses, we provide evidence supporting that entropy validly and reliably assesses the uncertainty of a tweet. This study contributes to improving our understanding of information propagation on Twitter during disasters. Academically, we offer a new variable of entropy to measure a tweet's uncertainty, an important factor influencing disaster tweets' retweeting. Entropy plays a critical role to better comprehend URLs and emoticons as a means to convey information. Practically, this research suggests a set of guidelines for effectively crafting disaster messages on Twitter.