Could scientists use Altmetric.com scores to predict longer term citation counts?

Altmetrics from Altmetric.com are widely used by publishers and researchers to give earlier evidence of attention than citation counts. This article assesses whether Altmetric.com scores are reliable early indicators of likely future impact and whether they may also reflect non-scholarly impacts. A preliminary factor analysis suggests that the main altmetric indicator of scholarly impact is Mendeley reader counts, with weaker news, informational and social network discussion/promotion dimensions in some fields. Based on a regression analysis of Altmetric.com data from November 2015 and Scopus citation counts from October 2017 for articles in 30 narrow fields, only Mendeley reader counts are consistent predictors of future citation impact. Most other Altmetric.com scores can help predict future impact in some fields. Overall, the results confirm that early Altmetric.com scores can predict later citation counts, although less well than journal impact factors, and the optimal strategy is to consider both Altmetric.com scores and journal impact factors. Altmetric.com scores can also reflect dimensions of non-scholarly impact in some fields.     

Dimensions: A competitor to Scopus and the Web of Science?

Dimensions is a partly free scholarly database launched by Digital Science in January 2018. Dimensions includes journal articles and citation counts, making it a potential new source of impact data. This article explores the value of Dimensions from an impact assessment perspective with an examination of Food Science research 2008–2018 and a random sample of 10,000 Scopus articles from 2012. The results include high correlations between citation counts from Scopus and Dimensions (0.96 by narrow field in 2012) as well as similar average counts. Almost all Scopus articles with DOIs were found in Dimensions (97% in 2012). Thus, the scholarly database component of Dimensions seems to be a plausible alternative to Scopus and the Web of Science for general citation analyses and for citation data in support of some types of research evaluations.     

U.S. academic departmental Web-site interlinking in the United States Disciplinary differences

This article explores disciplinary differences in academic Web-site interlinking using the university departments of chemistry, psychology, and history. Research has suggested that Web-link counts are related to research productivity and geographic distance between source and target, but no previous Webometric studies have comparatively analyzed academic departments from different disciplines. This study shows large differences in Web use by discipline for both Web-site size and the extent of interlinking, with the history department making little use of the Web and the chemistry department the most. There are significant correlations between in-links and research impact for the psychology and chemistry departments, with a stronger association for the psychology department. There was little evidence, however, of a geographic trend in interlinking.     

Can Google Scholar and Mendeley help to assess the scholarly impacts of dissertations?

Dissertations can be the single most important scholarly outputs of junior researchers. Whilst sets of journal articles are often evaluated with the help of citation counts from the Web of Science or Scopus, these do not index dissertations and so their impact is hard to assess. In response, this article introduces a new multistage method to extract Google Scholar citation counts for large collections of dissertations from repositories indexed by Google. The method was used to extract Google Scholar citation counts for 77,884 American doctoral dissertations from 2013 to 2017 via ProQuest, with a precision of over 95%. Some ProQuest dissertations that were dual indexed with other repositories could not be retrieved with ProQuest-specific searches but could be found with Google Scholar searches of the other repositories. The Google Scholar citation counts were then compared with Mendeley reader counts, a known source of scholarly-like impact data. A fifth of the dissertations had at least one citation recorded in Google Scholar and slightly fewer had at least one Mendeley reader. Based on numerical comparisons, the Mendeley reader counts seem to be more useful for impact assessment purposes for dissertations that are less than two years old, whilst Google Scholar citations are more useful for older dissertations, especially in social sciences, arts and humanities. Google Scholar citation counts may reflect a more scholarly type of impact than that of Mendeley reader counts because dissertations attract a substantial minority of their citations from other dissertations. In summary, the new method now makes it possible for research funders, institutions and others to systematically evaluate the impact of dissertations, although additional Google Scholar queries for other online repositories are needed to ensure comprehensive coverage.     

Gender and research publishing in India: Uniformly high inequality?

Women’s access to academic careers has been historically limited by discrimination and cultural constraints. Comprehensive information about gender inequality within disciplines is needed to understand the problem and target remedial action. India is the fifth largest research producer but has a low international index of gender inequality and so is an important case. This study assesses gender inequalities in Indian journal article publishing in 2017 for 186 research fields. It also seeks overall gender differences in interests across academia by comparing the terms used in 27,710 articles with an Indian male or female first author. The data show that there are at least 1.5 male first authors per female first author in each of 26 broad fields and 2.8 male first authors per female first author overall. Compared to the USA, India has a much lower share of female first authors but smaller variations in gender differences between broad fields. Dentistry, Economics and Maths are all more female in India, but Veterinary is much less female than in the USA. There is a tendency for males to research thing-oriented topics and for females to research helping people and some life science topics. More initiatives to promote gender equality in science are needed to address the overall imbalance, but care should be taken to avoid creating the larger between-field gender differences found in the USA.     

Mathematical models for academic webs: Linear relationship or non-linear power law?

Previous studies of academic web interlinking have tended to hypothesise that the relationship between the research of a university and links to or from its web site should follow a linear trend, yet the typical distribution of web data, in general, seems to be a non-linear power law. This paper assesses whether a linear trend or a power law is the most appropriate method with which to model the relationship between research and web site size or outlinks. Following linear regression, analysis of the confidence intervals for the logarithmic graphs, and analysis of the outliers, the results suggest that a linear trend is more appropriate than a non-linear power law.     

Microsoft Academic automatic document searches: Accuracy for journal articles and suitability for citation analysis

Microsoft Academic is a free academic search engine and citation index that is similar to Google Scholar but can be automatically queried. Its data is potentially useful for bibliometric analysis if it is possible to search effectively for individual journal articles. This article compares different methods to find journal articles in its index by searching for a combination of title, authors, publication year and journal name and uses the results for the widest published correlation analysis of Microsoft Academic citation counts for journal articles so far. Based on 126,312 articles from 323 Scopus subfields in 2012, the optimal strategy to find articles with DOIs is to search for them by title and filter out those with incorrect DOIs. This finds 90% of journal articles. For articles without DOIs, the optimal strategy is to search for them by title and then filter out matches with dissimilar metadata. This finds 89% of journal articles, with an additional 1% incorrect matches. The remaining articles seem to be mainly not indexed by Microsoft Academic or indexed with a different language version of their title. From the matches, Scopus citation counts and Microsoft Academic counts have an average Spearman correlation of 0.95, with the lowest for any single field being 0.63. Thus, Microsoft Academic citation counts are almost universally equivalent to Scopus citation counts for articles that are not recent but there are national biases in the results.     

Can Microsoft Academic assess the early citation impact of in-press articles? A multi-discipline exploratory analysis

Many journals post accepted articles online before they are formally published in an issue. Early citation impact evidence for these articles could be helpful for timely research evaluation and to identify potentially important articles that quickly attract many citations. This article investigates whether Microsoft Academic can help with this task. For over 65,000 Scopus in-press articles from 2016 and 2017 across 26 fields, Microsoft Academic found 2–5 times as many citations as Scopus, depending on year and field. From manual checks of 1122 Microsoft Academic citations not found in Scopus, Microsoft Academic’s citation indexing was faster but not much wider than Scopus for journals. It achieved this by associating citations to preprints with their subsequent in-press versions and by extracting citations from in-press articles. In some fields its coverage of scholarly digital libraries, such as arXiv.org, was also an advantage. Thus, Microsoft Academic seems to be a more comprehensive automatic source of citation counts for in-press articles than Scopus.     

Who shares health and medical scholarly articles on Facebook?

Over a million journal articles had been shared on public Facebook pages by 2017, but little is known about who is sharing (posting links to) these papers and whether mention counts could be an impact indicator. This study classified users who had posted about 749 links on Facebook before October 2017 mentioning 500 medical and health‐related research articles, obtained using altmetric.com data. Most accounts (68%) belonged to groups, including online communities, journals, academic organizations, and societies. Of individual profiles, academics accounted for only 4%, but the largest group were health care professionals (16%). More than half (58%) of all Facebook accounts examined were not academic. The non‐academic dominance suggests that public Facebook posts linking to health‐related articles are mostly used to facilitate scientific knowledge flow between non‐academic professionals and the public. Therefore, Facebook mention counts may be a combined academic and non‐academic attention indicator in the health and medical domains.     

Finding and tracking subjects within an ongoing debate

This paper describes a new algorithm for finding and tracking different subjects within an ongoing debate. The algorithm finds blocks of co-occurring terms, representing subjects, including blocks for which the term co-occurrence pattern forms a ring topology. We used short online debate forum data and longer summary bulletins to assess the extent to which the algorithm could correctly detect subjects, according to the judgements of human evaluators. The results show that it could normally detect subject-shifting and track different subjects over time in online debate forums and with adjustments could find subjects in bulletins, but could not track the subjects in the bulletins because the interlinking between subjects was too dense in the longer documents.