Search (75 results, page 1 of 4)

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Abstract

Webometrics is an information science field concerned with measuring aspects of the World Wide Web (WWW) for a variety of information science research goals. It came into existence about five years after the Web was formed and has since grown to become a significant aspect of information science, at least in terms of published research. Although some webometrics research has focused on the structure or evolution of the Web itself or the performance of commercial search engines, most has used data from the Web to shed light on information provision or online communication in various contexts. Most prominently, techniques have been developed to track, map, and assess Web-based informal scholarly communication, for example, in terms of the hyperlinks between academic Web sites or the online impact of digital repositories. In addition, a range of nonacademic issues and groups of Web users have also been analyzed.

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Abstract

Webometrics, the quantitative study of Web phenomena, is a field encompassing contributions from information science, computer science, and statistical physics. Its methodology draws especially from bibliometrics. This special issue presents contributions that both push for ward the field and illustrate a wide range of webometric approaches.

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Abstract

The quality and impact of academic Web sites is of interest to many audiences, including the scholars who use them and Web educators who need to identify best practice. Several large-scale European Union research projects have been funded to build new indicators for online scientific activity, reflecting recognition of the importance of the Web for scholarly communication. In this paper we address the key question of whether higher rated scholars produce higher impact Web sites, using the United Kingdom as a case study and measuring scholars' quality in terms of university-wide average research ratings. Methodological issues concerning the measurement of the online impact are discussed, leading to the adoption of counts of links to a university's constituent single domain Web sites from an aggregated counting metric. The findings suggest that universities with higher rated scholars produce significantly more Web content but with a similar average online impact. Higher rated scholars therefore attract more total links from their peers, but only by being more prolific, refuting earlier suggestions. It can be surmised that general Web publications are very different from scholarly journal articles and conference papers, for which scholarly quality does associate with citation impact. This has important implications for the construction of new Web indicators, for example that online impact should not be used to assess the quality of small groups of scholars, even within a single discipline.

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Abstract

Word usage is of interest to linguists for its own sake as well as to social scientists and others who seek to track the spread of ideas, for example, in public debates over political decisions. The historical evolution of language can be analyzed with the tools of corpus linguistics through evolving corpora and the Web. But word usage statistics can only be gathered for known words. In this article, techniques are described and tested for identifying new words from the Web, focusing on the case when the words are related to a topic and have a hybrid form with a common sequence of letters. The results highlight the need to employ a combination of search techniques and show the wide potential of hybrid word family investigations in linguistics and social science.

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Abstract

Sentiment analysis is concerned with the automatic extraction of sentiment-related information from text. Although most sentiment analysis addresses commercial tasks, such as extracting opinions from product reviews, there is increasing interest in the affective dimension of the social web, and Twitter in particular. Most sentiment analysis algorithms are not ideally suited to this task because they exploit indirect indicators of sentiment that can reflect genre or topic instead. Hence, such algorithms used to process social web texts can identify spurious sentiment patterns caused by topics rather than affective phenomena. This article assesses an improved version of the algorithm SentiStrength for sentiment strength detection across the social web that primarily uses direct indications of sentiment. The results from six diverse social web data sets (MySpace, Twitter, YouTube, Digg, Runners World, BBC Forums) indicate that SentiStrength 2 is successful in the sense of performing better than a baseline approach for all data sets in both supervised and unsupervised cases. SentiStrength is not always better than machine-learning approaches that exploit indirect indicators of sentiment, however, and is particularly weaker for positive sentiment in news-related discussions. Overall, the results suggest that, even unsupervised, SentiStrength is robust enough to be applied to a wide variety of different social web contexts.

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Abstract

Purpose - The purpose of this paper is to claim that it is useful to assess the web connectivity of research groups, describe hyperlink-based techniques to achieve this and present brief details of European life sciences research groups as a case study. Design/methodology/approach - A commercial search engine was harnessed to deliver hyperlink data via its automatic query submission interface. A special purpose link analysis tool, LexiURL, then summarised and graphed the link data in appropriate ways. Findings - Webometrics can provide a wide range of descriptive information about the international connectivity of research groups. Research limitations/implications - Only one field was analysed, data was taken from only one search engine, and the results were not validated. Practical implications - Web connectivity seems to be particularly important for attracting overseas job applicants and to promote research achievements and capabilities, and hence we contend that it can be useful for national and international governments to use webometrics to ensure that the web is being used effectively by research groups. Originality/value - This is the first paper to make a case for the value of using a range of webometric techniques to evaluate the web presences of research groups within a field, and possibly the first "applied" webometrics study produced for an external contract.

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Abstract

Despite over 10 years of research there is no agreement on the most suitable roles for Webometric indicators in support of research policy and almost no field-based Webometrics. This article partly fills these gaps by analyzing the potential of policy-relevant Webometrics for individual scientific fields with the help of 4 case studies. Although Webometrics cannot provide robust indicators of knowledge flows or research impact, it can provide some evidence of networking and mutual awareness. The scope of Webometrics is also relatively wide, including not only research organizations and firms but also intermediary groups like professional associations, Web portals, and government agencies. Webometrics can, therefore, provide evidence about the research process to compliment peer review, bibliometric, and patent indicators: tracking the early, mainly prepublication development of new fields and research funding initiatives, assessing the role and impact of intermediary organizations and the need for new ones, and monitoring the extent of mutual awareness in particular research areas.

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Abstract

A huge number of informal messages are posted every day in social network sites, blogs, and discussion forums. Emotions seem to be frequently important in these texts for expressing friendship, showing social support or as part of online arguments. Algorithms to identify sentiment and sentiment strength are needed to help understand the role of emotion in this informal communication and also to identify inappropriate or anomalous affective utterances, potentially associated with threatening behavior to the self or others. Nevertheless, existing sentiment detection algorithms tend to be commercially oriented, designed to identify opinions about products rather than user behaviors. This article partly fills this gap with a new algorithm, SentiStrength, to extract sentiment strength from informal English text, using new methods to exploit the de facto grammars and spelling styles of cyberspace. Applied to MySpace comments and with a lookup table of term sentiment strengths optimized by machine learning, SentiStrength is able to predict positive emotion with 60.6% accuracy and negative emotion with 72.8% accuracy, both based upon strength scales of 1-5. The former, but not the latter, is better than baseline and a wide range of general machine learning approaches.

Date

22. 1.2011 14:29:23

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Abstract

Collaboration is encouraged because it is believed to improve academic research, supported by indirect evidence in the form of more coauthored articles being more cited. Nevertheless, this might not reflect quality but increased self-citations or the "audience effect": citations from increased awareness through multiple author networks. We address this with the first science wide investigation into whether author numbers associate with journal article quality, using expert peer quality judgments for 122,331 articles from the 2014-20 UK national assessment. Spearman correlations between author numbers and quality scores show moderately strong positive associations (0.2-0.4) in the health, life, and physical sciences, but weak or no positive associations in engineering and social sciences, with weak negative/positive or no associations in various arts and humanities, and a possible negative association for decision sciences. This gives the first systematic evidence that greater numbers of authors associates with higher quality journal articles in the majority of academia outside the arts and humanities, at least for the UK. Positive associations between team size and citation counts in areas with little association between team size and quality also show that audience effects or other nonquality factors account for the higher citation rates of coauthored articles in some fields.

Date

22. 6.2023 18:11:50

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Abstract

Although the analysis of citations in the scholarly literature is now an established and relatively well understood part of information science, not enough is known about citations that can be found on the Web. In particular, are there new Web types, and if so, are these trivial or potentially useful for studying or evaluating research communication? We sought evidence based upon a sample of 1,577 Web citations of the URLs or titles of research articles in 64 open-access journals from biology, physics, chemistry, and computing. Only 25% represented intellectual impact, from references of Web documents (23%) and other informal scholarly sources (2%). Many of the Web/URL citations were created for general or subject-specific navigation (45%) or for self-publicity (22%). Additional analyses revealed significant disciplinary differences in the types of Google unique Web/URL citations as well as some characteristics of scientific open-access publishing on the Web. We conclude that the Web provides access to a new and different type of citation information, one that may therefore enable us to measure different aspects of research, and the research process in particular; but to obtain good information, the different types should be separated.

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Abstract

Collaboration is a major research policy objective, but does it deliver higher quality research? This study uses citation analysis to examine the Web of Science (WoS) Information Science & Library Science subject category (IS&LS) to ascertain whether, in general, more highly cited articles are more highly collaborative than other articles. It consists of two investigations. The first investigation is a longitudinal comparison of the degree and proportion of collaboration in five strata of citation; it found that collaboration in the highest four citation strata (all in the most highly cited 22%) increased in unison over time, whereas collaboration in the lowest citation strata (un-cited articles) remained low and stable. Given that over 40% of the articles were un-cited, it seems important to take into account the differences found between un-cited articles and relatively highly cited articles when investigating collaboration in IS&LS. The second investigation compares collaboration for 35 influential information scientists; it found that their more highly cited articles on average were not more highly collaborative than their less highly cited articles. In summary, although collaborative research is conducive to high citation in general, collaboration has apparently not tended to be essential to the success of current and former elite information scientists.

Date

22. 3.2009 12:43:51

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Abstract

A feature of modern democracies is public mistrust of scientists and the politicization of science policy, e.g., concerning stem cell research and genetically modified food. While the extent of this mistrust is debatable, its political influence is tangible. Hence, science policy researchers and science policy makers need early warning of issues that resonate with a wide public so that they can make timely and informed decisions. In this article, a semi-automatic method for identifying significant public science-related concerns from a corpus of Internet-based RSS (Really Simple Syndication) feeds is described and shown to be an improvement on a previous similar system because of the introduction of feedbased aggregation. In addition, both the RSS corpus and the concept of public science-related fears are deconstructed, revealing hidden complexity. This article also provides evidence that genetically modified organisms and stem cell research were the two major policyrelevant science concern issues, although mobile phone radiation and software security also generated significant interest.

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Abstract

Social network sites like MySpace are increasingly important environments for expressing and maintaining interpersonal connections, but does online communication exacerbate or ameliorate the known tendency for offline friendships to form between similar people (homophily)? This article reports an exploratory study of the similarity between the reported attributes of pairs of active MySpace Friends based upon a systematic sample of 2,567 members joining on June 18, 2007 and Friends who commented on their profile. The results showed no evidence of gender homophily but significant evidence of homophily for ethnicity, religion, age, country, marital status, attitude towards children, sexual orientation, and reason for joining MySpace. There were also some imbalances: women and the young were disproportionately commenters, and commenters tended to have more Friends than commentees. Overall, it seems that although traditional sources of homophily are thriving in MySpace networks of active public connections, gender homophily has completely disappeared. Finally, the method used has wide potential for investigating and partially tracking homophily in society, providing early warning of socially divisive trends.

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Abstract

Although citation counts are often used to evaluate the research impact of academic publications, they are problematic for books that aim for educational or cultural impact. To fill this gap, this article assesses whether a number of simple metrics derived from Amazon.com reviews of academic books could provide evidence of their impact. Based on a set of 2,739 academic monographs from 2008 and a set of 1,305 best-selling books in 15 Amazon.com academic subject categories, the existence of significant but low or moderate correlations between citations and numbers of reviews, combined with other evidence, suggests that online book reviews tend to reflect the wider popularity of a book rather than its academic impact, although there are substantial disciplinary differences. Metrics based on online reviews are therefore recommended for the evaluation of books that aim at a wide audience inside or outside academia when it is important to capture the broader impacts of educational or cultural activities and when they cannot be manipulated in advance of the evaluation.

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Abstract

Purpose Public attitudes towards COVID-19 and social distancing are critical in reducing its spread. It is therefore important to understand public reactions and information dissemination in all major forms, including on social media. This article investigates important issues reflected on Twitter in the early stages of the public reaction to COVID-19. Design/methodology/approach A thematic analysis of the most retweeted English-language tweets mentioning COVID-19 during March 10-29, 2020. Findings The main themes identified for the 87 qualifying tweets accounting for 14 million retweets were: lockdown life; attitude towards social restrictions; politics; safety messages; people with COVID-19; support for key workers; work; and COVID-19 facts/news. Research limitations/implications Twitter played many positive roles, mainly through unofficial tweets. Users shared social distancing information, helped build support for social distancing, criticised government responses, expressed support for key workers and helped each other cope with social isolation. A few popular tweets not supporting social distancing show that government messages sometimes failed. Practical implications Public health campaigns in future may consider encouraging grass roots social web activity to support campaign goals. At a methodological level, analysing retweet counts emphasised politics and ignored practical implementation issues. Originality/value This is the first qualitative analysis of general COVID-19-related retweeting.

Date

20. 1.2015 18:30:22

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Abstract

Open-access online publication has made available an increasingly wide range of document types for scientometric analysis. In this article, we focus on citations in online presentations, seeking evidence of their value as nontraditional indicators of research impact. For this purpose, we searched for online PowerPoint files mentioning any one of 1,807 ISI-indexed journals in ten science and ten social science disciplines. We also manually classified 1,378 online PowerPoint citations to journals in eight additional science and social science disciplines. The results showed that very few journals were cited frequently enough in online PowerPoint files to make impact assessment worthwhile, with the main exceptions being popular magazines like Scientific American and Harvard Business Review. Surprisingly, however, there was little difference overall in the number of PowerPoint citations to science and to the social sciences, and also in the proportion representing traditional impact (about 60%) and wider impact (about 15%). It seems that the main scientometric value for online presentations may be in tracking the popularization of research, or for comparing the impact of whole journals rather than individual articles.

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Abstract

Although there is some evidence that online videos are increasingly used by academics for informal scholarly communication and teaching, the extent to which they are used in published academic research is unknown. This article explores the extent to which YouTube videos are cited in academic publications and whether there are significant broad disciplinary differences in this practice. To investigate, we extracted the URL citations to YouTube videos from academic publications indexed by Scopus. A total of 1,808 Scopus publications cited at least one YouTube video, and there was a steady upward growth in citing online videos within scholarly publications from 2006 to 2011, with YouTube citations being most common within arts and humanities (0.3%) and the social sciences (0.2%). A content analysis of 551 YouTube videos cited by research articles indicated that in science (78%) and in medicine and health sciences (77%), over three fourths of the cited videos had either direct scientific (e.g., laboratory experiments) or scientific-related contents (e.g., academic lectures or education) whereas in the arts and humanities, about 80% of the YouTube videos had art, culture, or history themes, and in the social sciences, about 63% of the videos were related to news, politics, advertisements, and documentaries. This shows both the disciplinary differences and the wide variety of innovative research communication uses found for videos within the different subject areas.

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Abstract

Twitter is used by a substantial minority of the populations of many countries to share short messages, sometimes including images. Nevertheless, despite some research into specific images, such as selfies, and a few news stories about specific tweeted photographs, little is known about the types of images that are routinely shared. In response, this article reports a content analysis of random samples of 800 images tweeted from the UK or USA during a week at the end of 2014. Although most images were photographs, a substantial minority were hybrid or layered image forms: phone screenshots, collages, captioned pictures, and pictures of text messages. About half were primarily of one or more people, including 10% that were selfies, but a wide variety of other things were also pictured. Some of the images were for advertising or to share a joke but in most cases the purpose of the tweet seemed to be to share the minutiae of daily lives, performing the function of chat or gossip, sometimes in innovative ways.

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Abstract

Citation counts are widely used as indicators of research quality to support or replace human peer review and for lists of top cited papers, researchers, and institutions. Nevertheless, the relationship between citations and research quality is poorly evidenced. We report the first large-scale science-wide academic evaluation of the relationship between research quality and citations (field normalized citation counts), correlating them for 87,739 journal articles in 34 field-based UK Units of Assessment (UoA). The two correlate positively in all academic fields, from very weak (0.1) to strong (0.5), reflecting broadly linear relationships in all fields. We give the first evidence that the correlations are positive even across the arts and humanities. The patterns are similar for the field classification schemes of Scopus and Dimensions.ai, although varying for some individual subjects and therefore more uncertain for these. We also show for the first time that no field has a citation threshold beyond which all articles are excellent quality, so lists of top cited articles are not pure collections of excellence, and neither is any top citation percentile indicator. Thus, while appropriately field normalized citations associate positively with research quality in all fields, they never perfectly reflect it, even at high values.

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Abstract

Introduces several new versions of PageRank (the link based Web page ranking algorithm), based on an information science perspective on the concept of the Web document. Although the Web page is the typical indivisible unit of information in search engine results and most Web information retrieval algorithms, other research has suggested that aggregating pages based on directories and domains gives promising alternatives, particularly when Web links are the object of study. The new algorithms introduced based on these alternatives were used to rank four sets of Web pages. The ranking results were compared with human subjects' rankings. The results of the tests were somewhat inconclusive: the new approach worked well for the set that includes pages from different Web sites; however, it does not work well in ranking pages that are from the same site. It seems that the new algorithms may be effective for some tasks but not for others, especially when only low numbers of links are involved or the pages to be ranked are from the same site or directory.