Search (34 results, page 1 of 2)

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Abstract

Although there is evidence that counting the readers of an article in the social reference site, Mendeley, may help to capture its research impact, the extent to which this is true for different scientific fields is unknown. In this study, we compare Mendeley readership counts with citations for different social sciences and humanities disciplines. The overall correlation between Mendeley readership counts and citations for the social sciences was higher than for the humanities. Low and medium correlations between Mendeley bookmarks and citation counts in all the investigated disciplines suggest that these measures reflect different aspects of research impact. Mendeley data were also used to discover patterns of information flow between scientific fields. Comparing information flows based on Mendeley bookmarking data and cross-disciplinary citation analysis for the disciplines revealed substantial similarities and some differences. Thus, the evidence from this study suggests that Mendeley readership data could be used to help capture knowledge transfer across scientific disciplines, especially for people that read but do not author articles, as well as giving impact evidence at an earlier stage than is possible with citation counts.

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Abstract

Recent studies have shown that counting citations from books can help scholarly impact assessment and that Google Books (GB) is a useful source of such citation counts, despite its lack of a public citation index. Searching GB for citations produces approximate matches, however, and so its raw results need time-consuming human filtering. In response, this article introduces a method to automatically remove false and irrelevant matches from GB citation searches in addition to introducing refinements to a previous GB manual citation extraction method. The method was evaluated by manual checking of sampled GB results and comparing citations to about 14,500 monographs in the Thomson Reuters Book Citation Index (BKCI) against automatically extracted citations from GB across 24 subject areas. GB citations were 103% to 137% as numerous as BKCI citations in the humanities, except for tourism (72%) and linguistics (91%), 46% to 85% in social sciences, but only 8% to 53% in the sciences. In all cases, however, GB had substantially more citing books than did BKCI, with BKCI's results coming predominantly from journal articles. Moderate correlations between the GB and BKCI citation counts in social sciences and humanities, with most BKCI results coming from journal articles rather than books, suggests that they could measure the different aspects of impact, however.

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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

Purpose The four major Subject Repositories (SRs), arXiv, Research Papers in Economics (RePEc), Social Science Research Network (SSRN) and PubMed Central (PMC), are all important within their disciplines but no previous study has systematically compared how often they are cited in academic publications. In response, the purpose of this paper is to report an analysis of citations to SRs from Scopus publications, 2000-2013. Design/methodology/approach Scopus searches were used to count the number of documents citing the four SRs in each year. A random sample of 384 documents citing the four SRs was then visited to investigate the nature of the citations. Findings Each SR was most cited within its own subject area but attracted substantial citations from other subject areas, suggesting that they are open to interdisciplinary uses. The proportion of documents citing each SR is continuing to increase rapidly, and the SRs all seem to attract substantial numbers of citations from more than one discipline. Research limitations/implications Scopus does not cover all publications, and most citations to documents found in the four SRs presumably cite the published version, when one exists, rather than the repository version. Practical implications SRs are continuing to grow and do not seem to be threatened by institutional repositories and so research managers should encourage their continued use within their core disciplines, including for research that aims at an audience in other disciplines. Originality/value This is the first simultaneous analysis of Scopus citations to the four most popular SRs.

Date

20. 1.2015 18:30:22

Object

Social Science Research Network

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Abstract

Scientists and managers using citation-based indicators to help evaluate research cannot evaluate recent articles because of the time needed for citations to accrue. Reading occurs before citing, however, and so it makes sense to count readers rather than citations for recent publications. To assess this, Mendeley readers and citations were obtained for articles from 2004 to late 2014 in five broad categories (agriculture, business, decision science, pharmacy, and the social sciences) and 50 subcategories. In these areas, citation counts tended to increase with every extra year since publication, and readership counts tended to increase faster initially but then stabilize after about 5 years. The correlation between citations and readers was also higher for longer time periods, stabilizing after about 5 years. Although there were substantial differences between broad fields and smaller differences between subfields, the results confirm the value of Mendeley reader counts as early scientific impact indicators.

Date

16.11.2016 11:07:22

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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

Goodreads is an Amazon-owned book-based social web site for members to share books, read, review books, rate books, and connect with other readers. Goodreads has tens of millions of book reviews, recommendations, and ratings that may help librarians and readers to select relevant books. This article describes a first investigation of the properties of Goodreads users, using a random sample of 50,000 members. The results suggest that about three quarters of members with a public profile are female, and that there is little difference between male and female users in patterns of behavior, except for females registering more books and rating them less positively. Goodreads librarians and super-users engage extensively with most features of the site. The absence of strong correlations between book-based and social usage statistics (e.g., numbers of friends, followers, books, reviews, and ratings) suggests that members choose their own individual balance of social and book activities and rarely ignore one at the expense of the other. Goodreads is therefore neither primarily a book-based website nor primarily a social network site but is a genuine hybrid, social navigation site.

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Abstract

General sentiment analysis for the social web has become increasingly useful for shedding light on the role of emotion in online communication and offline events in both academic research and data journalism. Nevertheless, existing general-purpose social web sentiment analysis algorithms may not be optimal for texts focussed around specific topics. This article introduces 2 new methods, mood setting and lexicon extension, to improve the accuracy of topic-specific lexical sentiment strength detection for the social web. Mood setting allows the topic mood to determine the default polarity for ostensibly neutral expressive text. Topic-specific lexicon extension involves adding topic-specific words to the default general sentiment lexicon. Experiments with 8 data sets show that both methods can improve sentiment analysis performance in corpora and are recommended when the topic focus is tightest.

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Abstract

Increasing interdisciplinarity has been a policy objective since the 1990s, promoted by many governments and funding agencies, but the question is: How deeply has this affected the social sciences? Although numerous articles have suggested that research has become more interdisciplinary, yet no study has compared the extent to which the interdisciplinarity of different social science subjects has changed. To address this gap, changes in the level of interdisciplinarity since 1980 are investigated for subjects with many articles in the Social Sciences Citation Index (SSCI), using the percentage of cross-disciplinary citing documents (PCDCD) to evaluate interdisciplinarity. For the 14 SSCI subjects investigated, the median level of interdisciplinarity, as measured using cross-disciplinary citations, declined from 1980 to 1990, but rose sharply between 1990 and 2000, confirming previous research. This increase was not fully matched by an increase in the percentage of articles that were assigned to more than one subject category. Nevertheless, although on average the social sciences have recently become more interdisciplinary, the extent of this change varies substantially from subject to subject. The SSCI subject with the largest increase in interdisciplinarity between 1990 and 2000 was Information Science & Library Science (IS&LS) but there is evidence that the level of interdisciplinarity of IS&LS increased less quickly during the first decade of this century.

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Abstract

Social network sites (SNSs) such as MySpace and Facebook are important venues for interpersonal communication, especially among youth. One way in which members can communicate is to write public messages on each other's profile, but how is this unusual means of communication used in practice? An analysis of 2,293 public comment exchanges extracted from large samples of U.S. and U.K. MySpace members found them to be relatively rapid, but rarely used for prolonged exchanges. They seem to fulfill two purposes: making initial contact and keeping in touch occasionally such as at birthdays and other important dates. Although about half of the dialogs seem to exchange some gossip, the dialogs seem typically too short to play the role of gossip-based social grooming for typical pairs of Friends, but close Friends may still communicate extensively in SNSs with other methods.

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Abstract

Data collected by social media platforms have been introduced as new sources for indicators to help measure the impact of scholarly research in ways that are complementary to traditional citation analysis. Data generated from social media activities can be used to reflect broad types of impact. This article aims to provide systematic evidence about how often Twitter is used to disseminate information about journal articles in the biomedical sciences. The analysis is based on 1.4 million documents covered by both PubMed and Web of Science and published between 2010 and 2012. The number of tweets containing links to these documents was analyzed and compared to citations to evaluate the degree to which certain journals, disciplines, and specialties were represented on Twitter and how far tweets correlate with citation impact. With less than 10% of PubMed articles mentioned on Twitter, its uptake is low in general but differs between journals and specialties. Correlations between tweets and citations are low, implying that impact metrics based on tweets are different from those based on citations. A framework using the coverage of articles and the correlation between Twitter mentions and citations is proposed to facilitate the evaluation of novel social-media-based metrics.

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Abstract

Academic social network sites Academia.edu and ResearchGate, and reference sharing sites Mendeley, Bibsonomy, Zotero, and CiteULike, give scholars the ability to publicize their research outputs and connect with each other. With millions of users, these are a significant addition to the scholarly communication and academic information-seeking eco-structure. There is thus a need to understand the role that they play and the changes, if any, that they can make to the dynamics of academic careers. This article investigates attributes of philosophy scholars on Academia.edu, introducing a median-based, time-normalizing method to adjust for time delays in joining the site. In comparison to students, faculty tend to attract more profile views but female philosophers did not attract more profile views than did males, suggesting that academic capital drives philosophy uses of the site more than does friendship and networking. Secondary analyses of law, history, and computer science confirmed the faculty advantage (in terms of higher profile views) except for females in law and females in computer science. There was also a female advantage for both faculty and students in law and computer science as well as for history students. Hence, Academia.edu overall seems to reflect a hybrid of scholarly norms (the faculty advantage) and a female advantage that is suggestive of general social networking norms. Finally, traditional bibliometric measures did not correlate with any Academia.edu metrics for philosophers, perhaps because more senior academics use the site less extensively or because of the range informal scholarly activities that cannot be measured by bibliometric methods.

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Abstract

The uptake of social network sites (SNSs) has been highly trend-driven, with Friendster, MySpace, and Facebook being successively the most popular. Given that teens are often early adopters of communication technologies, it seems reasonable to assume that the typical user of any particular SNS would change over time, probably becoming older and covering different segments of the population. This article analyzes changes in MySpace self-reported member demographics and behavior from 2007 to 2010 using four large samples of members and focusing on the United States. The results indicate that despite its take-up rate declining, with only about 1 in 10 members being active a year after joining, the dominant (modal) age for active U.S. members remains midadolescence, but has shifted by about 2 years from 15 to 17, and the U.S. dominance of MySpace is shrinking. There also has been a dramatic increase in the median number of Friends for new U.S. members, from 12 to 96-probably due to MySpace's automated Friend Finder. Some factors show little change, however, including the female majority, the 5% minority gay membership, and the approximately 50% private profiles. In addition, there has been an increase in the proportion of Latino/Hispanic U.S. members, suggesting a shifting ethnic profile. Overall, MySpace has surprisingly stable membership demographics and is apparently maintaining its primary youth appeal, perhaps because of its music orientation.

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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

Scholars writing books that are widely used to support teaching in higher education may be undervalued because of a lack of evidence of teaching value. Although sales data may give credible evidence for textbooks, these data may poorly reflect educational uses of other types of books. As an alternative, this article proposes a method to search automatically for mentions of books in online academic course syllabi based on Bing searches for syllabi mentioning a given book, filtering out false matches through an extensive set of rules. The method had an accuracy of over 90% based on manual checks of a sample of 2,600 results from the initial Bing searches. Over one third of about 14,000 monographs checked had one or more academic syllabus mention, with more in the arts and humanities (56%) and social sciences (52%). Low but significant correlations between syllabus mentions and citations across most fields, except the social sciences, suggest that books tend to have different levels of impact for teaching and research. In conclusion, the automatic syllabus search method gives a new way to estimate the educational utility of books in a way that sales data and citation counts cannot.

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Abstract

Although peer-review and citation counts are commonly used to help assess the scholarly impact of published research, informal reader feedback might also be exploited to help assess the wider impacts of books, such as their educational or cultural value. The social website Goodreads seems to be a reasonable source for this purpose because it includes a large number of book reviews and ratings by many users inside and outside of academia. To check this, Goodreads book metrics were compared with different book-based impact indicators for 15,928 academic books across broad fields. Goodreads engagements were numerous enough in the arts (85% of books had at least one), humanities (80%), and social sciences (67%) for use as a source of impact evidence. Low and moderate correlations between Goodreads book metrics and scholarly or non-scholarly indicators suggest that reader feedback in Goodreads reflects the many purposes of books rather than a single type of impact. Although Goodreads book metrics can be manipulated, they could be used guardedly by academics, authors, and publishers in evaluations.

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Abstract

Purpose Despite the social, educational and therapeutic benefits of book clubs, little is known about which books participants are likely to have read. In response, the purpose of this paper is to investigate the public bookshelves of those that have joined a group within the Goodreads social network site. Design/methodology/approach Books listed as read by members of 50 large English-language Goodreads groups - with a genre focus or other theme - were compiled by author and title. Findings Recent and youth-oriented fiction dominate the 50 books most read by book club members, whilst almost half are works of literature frequently taught at the secondary and postsecondary level (literary classics). Whilst J.K. Rowling is almost ubiquitous (at least 63 per cent as frequently listed as other authors in any group, including groups for other genres), most authors, including Shakespeare (15 per cent), Goulding (6 per cent) and Hemmingway (9 per cent), are little read by some groups. Nor are individual recent literary prize winners or works in languages other than English frequently read. Research limitations/implications Although these results are derived from a single popular website, knowing more about what book club members are likely to have read should help participants, organisers and moderators. For example, recent literary prize winners might be a good choice, given that few members may have read them. Originality/value This is the first large scale study of book group members' reading patterns. Whilst typical reading is likely to vary by group theme and average age, there seems to be a mainly female canon of about 14 authors and 19 books that Goodreads book club members are likely to have read.

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Abstract

ResearchGate is a social network site for academics to create their own profiles, list their publications, and interact with each other. Like Academia.edu, it provides a new way for scholars to disseminate their work and hence potentially changes the dynamics of informal scholarly communication. This article assesses whether ResearchGate usage and publication data broadly reflect existing academic hierarchies and whether individual countries are set to benefit or lose out from the site. The results show that rankings based on ResearchGate statistics correlate moderately well with other rankings of academic institutions, suggesting that ResearchGate use broadly reflects the traditional distribution of academic capital. Moreover, while Brazil, India, and some other countries seem to be disproportionately taking advantage of ResearchGate, academics in China, South Korea, and Russia may be missing opportunities to use ResearchGate to maximize the academic impact of their publications.

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Abstract

In theory, articles can attract readers on the social reference sharing site Mendeley before they can attract citations, so Mendeley altmetrics could provide early indications of article impact. This article investigates the influence of time on the number of Mendeley readers of an article through a theoretical discussion and an investigation into the relationship between counts of readers of, and citations to, 4 general library and information science (LIS) journals. For this discipline, it takes about 7 years for articles to attract as many Scopus citations as Mendeley readers, and after this the Spearman correlation between readers and citers is stable at about 0.6 for all years. This suggests that Mendeley readership counts may be useful impact indicators for both newer and older articles. The lack of dates for individual Mendeley article readers and an unknown bias toward more recent articles mean that readership data should be normalized individually by year, however, before making any comparisons between articles published in different years.

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Abstract

Although gender differences are known to exist in the publishing industry and in reader preferences, there is little public systematic data about them. This article uses evidence from the book-based social website Goodreads to provide a large scale analysis of 50 major English book genres based on author genders. The results show gender differences in authorship in almost all categories and gender differences the level of interest in, and ratings of, books in a minority of categories. Perhaps surprisingly in this context, there is not a clear gender-based relationship between the success of an author and their prevalence within a genre. The unexpected almost universal authorship gender differences should give new impetus to investigations of the importance of gender in fiction and the success of minority genders in some genres should encourage publishers and librarians to take their work seriously, except perhaps for most male-authored chick-lit.