Challenges of capturing engagement on Facebook for Altmetrics

Previous research shows that, despite its popularity, Facebook is less frequently used to share academic content. In order to investigate this discrepancy we set out to explore engagement numbers through their Graph API by querying the Facebook API with multiple URLs for a random set of 103,539 articles from the Web of Science. We identified two major challenge areas: mapping articles to URLs and the mapping URLs to objects inside Facebook. We then explored three problem cases within our dataset: (1) identifying a landing page for any given URL, (2) instances where equivalent URLs are mapped to different Facebook objects, and (3) instances of different articles being mapped onto the same Facebook object. We found that the engagement numbers for 11.8% of all articles that have been shared on Facebook at least once are not reliable because of these problems. Moreover, we were unable to identify the URL for 11.6% of the articles in our data. Taken together, the three problem cases constitute 12.3% of the 103,539 tested articles for which engagement numbers cannot be relied upon. Given that we only tested a small number of problem cases and URL variants, our results point to large challenges facing those wishing to collect Facebook metrics programatically through the available API.Comment: To be presented at the 23rd International Conference on Science and Technology Indicators (STI 2018

A folyóiratcikkek súlya a különféle tudományterületek szakirodalmában: az elmúlt két évtized trendjei

Absztrakt Vizsgálatunk során a folyóiratcikkek arányát hasonlítottuk össze néhány természettudományi, valamint társadalom- és bölcsészettudományi szakterület összefoglaló (review) cikkeinek irodalomjegyzékében. Megállapítottuk, hogy az 1995–2014 időszakban a folyóiratcikkek aránya mindegyik vizsgált területen növekedett. A legintenzívebb növekedés a társadalomtudományi területen volt tapasztalható. Orv. Hetil., 2015, 156(24), 985–987

A Systematic Identification and Analysis of Scientists on Twitter

Metrics derived from Twitter and other social media---often referred to as altmetrics---are increasingly used to estimate the broader social impacts of scholarship. Such efforts, however, may produce highly misleading results, as the entities that participate in conversations about science on these platforms are largely unknown. For instance, if altmetric activities are generated mainly by scientists, does it really capture broader social impacts of science? Here we present a systematic approach to identifying and analyzing scientists on Twitter. Our method can identify scientists across many disciplines, without relying on external bibliographic data, and be easily adapted to identify other stakeholder groups in science. We investigate the demographics, sharing behaviors, and interconnectivity of the identified scientists. We find that Twitter has been employed by scholars across the disciplinary spectrum, with an over-representation of social and computer and information scientists; under-representation of mathematical, physical, and life scientists; and a better representation of women compared to scholarly publishing. Analysis of the sharing of URLs reveals a distinct imprint of scholarly sites, yet only a small fraction of shared URLs are science-related. We find an assortative mixing with respect to disciplines in the networks between scientists, suggesting the maintenance of disciplinary walls in social media. Our work contributes to the literature both methodologically and conceptually---we provide new methods for disambiguating and identifying particular actors on social media and describing the behaviors of scientists, thus providing foundational information for the construction and use of indicators on the basis of social media metrics

Making the Mission Visible: Altmetrics and Nontraditional Publishing

Whereas traditional book and journal publishing remain the gold standard for many post-secondary institutions, nontraditional publishing is just as prolific at the flagship university in Maine. The university has strong land and sea grant missions that drive a broad research agenda, with an emphasis on community outreach and engagement. However, the impact of researchers’ contributions outside of academe is unlikely to be accurately reflected in promotion, tenure or review processes. Thus, the authors designed a series of altmetrics workshops aimed at seeding conversations around novel ways to track the impact of researchers’ diverse scholarly and creative outputs. This paper presents a case study of the instructional approach taken at the University of Maine library to facilitate discussions of alternative impact assessments that reach beyond traditional publications

Preprint w humanistyce – fikcja czy realna możliwość?

Even though the use of open preprint databases for scholarly publications is commonplace in several disciplines, their possibilities remain largely unexplored in the humanities. This article examines the emergence and the dynamics of academic preprint and evaluates the possibilities for introducing preprint for the humanities.Pomimo że korzystanie z otwartych baz preprintów publikacji naukowych jest powszechne w wielu dyscyplinach, możliwości takich baz preprintów pozostają w dużej mierze niewykorzystane w naukach humanistycznych. Artykuł omawia powstawanie i dynamikę preprintu akademickiego oraz ocenia możliwości wprowadzenia preprintów w naukach humanistycznych

Do Mendeley reader counts indicate the value of arts and humanities research?

This is an accepted manuscript of an article published by Sage in Journal of Librarianship and Information Science on 19/09/2017, available online: https://doi.org/10.1177/0961000617732381 The accepted version of the publication may differ from the final published version.Mendeley reader counts are a good source of early impact evidence for the life and natural sciences articles because they are abundant, appear before citations, and correlate moderately or strongly with citations in the long term. Early studies have found less promising results for the humanities and this article assesses whether the situation has now changed. Using Mendeley reader counts for articles in twelve arts and humanities Scopus subcategories, the results show that Mendeley reader counts reflect Scopus citation counts in most arts and humanities as strongly as in other areas of scholarship. Thus, Mendeley can be used as an early citation impact indicator in the arts and humanities, although it is unclear whether reader or citation counts reflect the underlying value of arts and humanities research

TWEETS OF AN ARTICLE AND ITS CITATION: AN ALTMETRIC STUDY OF MOST PROLIFIC AUTHORS

The present study was carried to find out the association between twitter and citation pattern for scholarly articles. This study was carried out with the most prolific authors of 2014 from the four subject domain “Clinical medicine, Microbiology, Molecular Biology, and Neuroscience” and 4886 papers were identified to studied their tweets and citation counts. From the study, it was found that the articles of the most prolific authors have a strong correlation with the citation and its value ρ =.518**. The linear relationship for individual subjects was between .386** to .559**, significant at .01 level

Altmetrics: State of the Art and a Look into the Future

The development of alternative indicators (altmetrics) can be traced back to a discussion a few years ago where the central question was: does the focus on classical bibliometric indicators still adequately reflect the scientific and social significance of scientific work in the Internet age? In the course of this discussion, the term “altmetrics” was introduced as a collective term for all those indicators that contain previously unnoticed information from the Internet—especially concerning social media. Altmetrics shed light on the reception of scientific publications in news websites as well as in scientific blogs, policy papers, and other web-based content. This chapter deals with the current state of the art of altmetrics, focusing on the present discussion about the informative value of altmetrics. Furthermore, we investigate to what extent altmetrics can be used in scientific evaluations. We conclude our chapter with an outlook on the potential prospects for success of altmetrics in different fields of application

Investigating the Social Media Presence of Articles in Altmetrics Field Indexed in Scopus Database: An Altmetrics study

Introduction: Altmetrics is one of the novel measures of citation in social media which can be used to investigate scientific and research output. The current study was carried out in order to determine the presence of articles in Altmetrics field in social media, determining superior articles in this field based on Altmetrics criteria and determining the relation between Altmetrics measure and citation performance of these articles. Method: This is a descriptive study with scientometrics approach using altmetrics method. The study population consisted of 337 articles in the altmetrics field indexed in Scopus database. Among these articles, 53 lacked Digital Object Identifier (DOI) which were eliminated from the study. The citation score of each article was determined by entering each article in Google Scholar database. SPSS16 software was used for data analysis. Descriptive statistics (average and standard deviation) was used to determine the average presence of articles in social media while Pearson correlation coefficient was used to determine the correlation between citation performance of articles and their total altmetrics score. Findings: Mendeley was the most important social media used by researchers in the field of altmetrics with average score of 45.34 which was followed by Twitter with average score of 19. U-like website with average score of 0.77 and Facebook with average of 0.47 were at the next ranks. The average altmetrics score for articles in the altmetrics field was 20.77 and average citation score was 19.046 and showed that the presence of altmetrics articles in social media and citation databases (Google Scholar) is almost identical. Conclusion: The results of the current study showed that social media greatly affect the amount of citations to scientific works. Researchers in the field of altmetrics share their articles and research results using social media almost as much as they share them over citation databases. Improving the awareness and educating researchers about social media and their altmetrics scores can improve the sharing of articles and research results in social media