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This article investigates the lengths of time that publications with different numbers of policy document mentions take to receive their first mention (the beginning stage), and then compares the lengths of time to receive two or more mentions after receiving the first mention (the accumulative stage) based on complete policy document dataset from Altmetric database. We find that in response time distribution, i.e., from zero to one policy document mention, highly and mediumly mentioned papers exhibit obviously different lengths of time compared with lowly mentioned papers. In accumulative time distribution, i.e., from one to N policy document mentions, highly mentioned papers begin to receive mentions much more rapidly than medium‐ and low‐mentioned papers. However, as N increases, the difference in receiving new mentions among high‐, medium‐, and low‐mentioned publications does not increase quite significantly. [ABSTRACT FROM AUTHOR]

The academic community may make research findings public by mentioning Chinese scholarly papers on WeChat. However, why and how Chinese research papers were cited in WeChat articles remains unknown. This work conducted a content analysis of the motivations, emotions, forms, and elements of WeChat mentions. Data was collected from CNKI and WeChat official accounts, resulting in a dataset of 7,970 core journal papers with 21,134 WeChat mentions. Key findings include that: (1) Most of the mentions in the WeChat articles present Chinese academic publications for sharing and introduction. These mentions account for about 64%. (2) Mention sentiments are mainly neutral (around 64%). Negative emotions are almost absent. (3) In the mention forms, most WeChat articles mentioning scholarly papers do not include reference lists. They mention the papers directly in the body of the WeChat articles with recognizable elements of academic papers. (4) Concerning the mentioned elements, academic papers consist of essential content parts. They include titles (78%), abstracts (12%), and full texts (9%), and that gets the most WeChat mentions. This would give a better base and reference for advancing altmetrics in China. And it would be helpful to know the cause and how the academic papers spread on Chinese social media. [ABSTRACT FROM AUTHOR]

ABSTRACT This study investigates the effect of diffusing scientific articles on Twitter on their citation impact. For a set of 1.3 million papers covered by the Web of Science and published in 2012, normalized citation rates are compared between tweeted and non-tweeted articles published in the same journal. The results indicate that tweeted papers, published in the same year and in the same journal received around 30% higher citation rates than papers which were not diffused on Twitter. This type of citation advantage appeared across disciplines and countries of authors, but varied in extent. [ABSTRACT FROM AUTHOR]

ABSTRACT There have been many studies on the factors influencing paper citation counts. A number of studies have focused on the citing papers, and corresponding methods were proposed to measure the prestige of citations based on the journal impact factors, the total citation counts and the PageRank algorithm values. However, there are drawbacks to these methods. In this paper, we propose a novel method to identify prestigious citations from the affiliation of the citing paper. Specifically, if the authors of the citing paper are affiliated with a prestigious university, the citing paper could be counted as a prestigious citation. As a pilot, we used the top 200 universities on the QS World University Rankings 2015 to identify the prestigious universities so that the prestigious citations, named as QS citations, were identified accordingly. Experimental results validated that QS citations have more important impact on the cited papers than other citations. Papers with QS citations have better performance across most disciplines not only in total citation counts, but also in altmetrics such as the Altmetric Attension Score and Mendeley reader counts. [ABSTRACT FROM AUTHOR]

The diversity of social media platforms, users and uses has long been a challenge for social media research. The difficulty of inferring meaning from social media acts is also, and perhaps more importantly, due to the fact the even identical acts that are in appearance identical and that occur on the same platforms and contexts can have diverse meanings. This paper proposes a model based on the concepts of social and topical distance that can help shed light on the possible meanings of a social media act. The model considers the social relationship between the content creator and the user, as well as the topical relationship between the content the user's main topics of interest. It is demonstrated by analyzing a set of papers published in JASIST that were tweeted by researchers. The results show that the model can help differentiate between different types of heterogeneous social media acts and users or be used to characterize the attention that a specific content has received on social media. [ABSTRACT FROM AUTHOR]

Taking international LIS journals as an example, combining 8 traditional citation indicators and 10 altmetrics indicators, we use the method of multi‐indicator fusion to construct a comprehensive evaluation model of journal impact based on traditional citation indicators and altmetrics indicators. Through normalization processing, correlation analysis, reliability analysis, validity analysis, factor analysis, the paper evaluates the academic impact (FA), societal impact (FS) of LIS journals respectively. We get the following conclusion: (1) We get the 2‐dimensional evaluation results and according to LIS journals impacts, we divide the roles into four categories: "Prestige journals", "Star journals", "Common journals" and "Expert journals". (2) It is found that 8 traditional citation indicators based on JCR, present strong positive correlations, and the indicators are highly consistent overall and internally. (3) There are moderate or high positive correlations among 10 altmetrics based on Altmetrics Explorer, and there are also significant consistency among the indicators as a whole and internally. (4) The correlation coefficient between FA and FS is 0.566, with a moderate positive correlation. It indicates that the evaluation of LIS journals' societal impact based on altmetrics indicators has a useful supplement to the evaluation of academic impact based on citation. [ABSTRACT FROM AUTHOR]

There is evidence that scholarly processes have bias and create barriers to inclusion; more openness in scholarly communication is needed. Progress towards a better scholarly ecosystem requires comparable, reliable measures of the desired attributes of a better system. This paper describes an initiative in progress to produce standardized indicators that describe the volume and types of open science output systematically over time, using existing open data sources. We describe a replicable to clean, integrate, code, and analyze these sources to enable continuous publication of indicators. And we report on early results from this initiative, demonstrating how these indicators can go beyond "overall impact" measures to advance the understanding of who is, and who is not, participating in open scholarship. [ABSTRACT FROM AUTHOR]

It has always been argued that social sciences and humanities (SSH) impact evaluation calls for a broader range of indicators than only bibliometric indicators. This study analyzes the performance of scientific SSH publications using 1,327,924 records from the Social Sciences Citation Index (SSCI) and the Arts & Humanities Citation Index (A&HCI), and 629,586 records from Altmetric.com. The research covers a period of 5 years (2013–2017); three publication types (articles, reviews, and proceedings papers); four selected subject fields; three citation indicators; and 13 altmetric indicators. The comparative analysis of SSH performance is studied in both citation and altmetric pattern, and an attempt is made to interpret the results in both the metric and discipline contexts. Major contributions of this study include the extension of analysis methods for the SSH, as well as the validation of altmetric indicators. [ABSTRACT FROM AUTHOR]

YouTube is a valuable source of user‐generated content on a wide range of topics, and it encourages user participation through the use of a comment system. Video content is increasingly addressing scientific topics, and there is evidence that both academics and consumers use video descriptions and video comments to refer to academic research and scientific publications. Because commenting is a discursive behavior, this study will provide insights on why individuals post links to research publications in comments. For this, a qualitative content analysis and iterative coding approach were applied. Furthermore, the reasons for mentioning academic publications in comments were contrasted with the reasons for citing in scholarly works and with reasons for commenting on YouTube. We discovered that the primary motives for sharing research links were (1) providing more insights into the topic and (2) challenging information offered by other commentators. [ABSTRACT FROM AUTHOR]

ABSTRACT In this poster, we describe a framework to measure the impact of R packages from an altmetrics perspective. This framework includes search statistics on Google, the number of downloads on CRAN (the official R package repository), the number of posts on Stack Overflow and the count of papers on the Public Library of Science (PLoS) journals mentioning or citing the packages. These measures are normalized into monthly units. Six visualization packages were selected to test the method. Results are presented and discussed, particularly in light of the levels of engagement represented by these measures. The next steps of this project are also explained at the end of this poster proposal. [ABSTRACT FROM AUTHOR]

ABSTRACT As the way of evaluating research outputs has gradually changed, and the dissemination of scholarly materials online has gotten easier, research studies investigating the awareness and usage of social media in academia have also been on the rise. The number of user surveys on the awareness and usage of altmetrics (emerging alternative metrics based on social media) has, however, remained low. This paper presents the findings of an online survey, which are the results of the first phase data collection of a user survey on the awareness and usage of altmetrics in academia. Our findings show that article views and downloads from online digital libraries or repositories are very well-known. The most used altmetrics are mentions and shares on social networks. Mentions in blog posts and topics in a forum are also popular altmetrics. Interestingly, this study reveals a tendency for non-faculty staff to be more aware of altmetrics. Furthermore, we also investigate how the usage of social media correlates with the usage of altmetrics. The findings show medium to large correlations between the usage of social media and the usage of altmetrics, which means academics who use social media often, also tend to use altmetrics often. [ABSTRACT FROM AUTHOR]

ABSTRACT Altmetrics is an emerging measure for academic impact and it is gaining in global importance. In this paper, we analyse the altmetric landscape of Singapore, a young nation with a fast growing international research sector. We aim to find out if the coverage of altmetrics across the different disciplines is increasing along with the fast increase in the amount of research publications in recent years. We also look into how altmetrics relate to traditional citation counts as a measure of research impact. From our results, we see that there is overall an 18% coverage of altmetrics of Singapore publications from 2009 to 2013. The number of publications with available altmetric data has also been increasing over the years for most disciplines. Correlation results between citation counts and altmetrics show medium to low correlations with distinct differences amongst the various disciplines. A high coverage of altmetrics however does not seem to lead to larger correlations with citation counts. Singapore thus remains an intriguing case study to watch in the coming years. [ABSTRACT FROM AUTHOR]

In this paper, we describe our preliminary findings of our multi‐site study on researchers' use of online scholarly tools. Using surveys and in‐depth interviews, our study will provide information professionals and scholars a 360‐degree panorama of the ways social media is impacting the dissemination and evaluation of scholarly research. At the visual presentation session, we will present the statistical results and analysis of our data, as well as individual case stories exemplifying the main findings. Additionally, we will have an activity where our audience can participate in the same card sorting exercise that study subjects did, and compare their results with the study participants, to better understand the value of various scholarly activities. [ABSTRACT FROM AUTHOR]

This panel will present views and critical reflections on peer review, bibliometrics and altmetrics against the background of the latest developments and critique of the scientific system (e.g., replication crisis, DORA, open science, data manipulation). Peer review is the oldest form of monitoring the scientific process and research outcomes and is sometimes considered as the gold standard for evaluating quality. However, it also has its drawbacks; therefore, new forms of peer review are being explored. Bibliometrics, comparative statistics based on publication and citation counts, was introduced as a more objective evaluation method, which is applicable on meso and macro levels of research producing units but is not without problems either. Citation counts as a proxy of quality; the impact factor and the h‐index are some of the most controversial subjects of research evaluation today. The newest addition to the evaluation toolbox are altmetrics, impact measures based mainly on social media activity. Altmetrics have pros and cons as well. None of the measuring devices is perfect, and rather than replacing they complement each other. By drawing on indicators from all three aspects of research evaluation, negative and adverse effects are limited. [ABSTRACT FROM AUTHOR]

ABSTRACT Metrics have become objective standards for evaluating research performance. Measurements such as citation counts and h-index are used for evaluating individual research performance as well as the ranking of research institutions and universities. This exploratory study aims to understand the implications of the increasing use of metrics on scholarly communication and practices. A pilot study was conducted in universities in Ireland. Preliminary findings show that researchers use Google Scholar and ResearchGate for self-monitoring and that they perceive bibliometric measures as indicators of achievements. The pilot study also shows that there are mixed feelings toward bibliometrics: while the participants emphasise that research interest is the most important criterion in choosing research topics and publication channels and that citation counts, h-index, and RG scores are coincidental of their research activities, they also perceive the quantitative measures as objective evaluation of research performance without knowing how the h-index or RG scores are calculated. [ABSTRACT FROM AUTHOR]

Using Article-Level-Metrics (ALMs) data from PLOS, we analyze the citations, views, saves, and shares of different types of articles. Using multiple statistical and visualization techniques, we explore scientists' behaviors associated with scholarly works, which could help us better understand their information needs, and provide clues about how different types of scholarly information are valued. We find that scholarly impact could be better interpreted when article types are taken into consideration. Moreover, the correlations between citations, views, saves, and shares also demonstrate the need to consider article types when assessing the validity of altmetrics. Since altmetrics usage data are associated with various information behaviors, we advocate that altmetrics, especially only the scores, should be used with caution. In summary, our approach provides a novel point of view to explore altmetrics and citation data. Future work will adopt quality approaches to look into more details of the current analyses, to get a better understanding of flavors of scholarly impact. [ABSTRACT FROM AUTHOR]

The panel explores the theoretical, practical, and policy aspects of self-presentation in academia given the rapidly changing world of knowledge creation, dissemination and consumption. It offers insights into both the potential and challenges of social media in academia and highlights future directions regarding scholarly communication. The goal of the panel is to start an interactive discussion based on a number of important themes related to social media use and appearance of various stakeholders in academia that will be of interest to scholarly communication researchers, information professionals, librarians and administrators. [ABSTRACT FROM AUTHOR]

The aim of this SIG/MET-sponsored panel is to discuss major informetric topics including the impact factor, the hindex, sources of citation data, the Eigenfactor, the making and use of base maps of science, application of informetrics (e.g., for retrieval purposes), altmetrics, and future perspectives on bibliometrics. The panel especially addresses attendees who want to expand their knowledge in this area or got in touch with it only recently. [ABSTRACT FROM AUTHOR]

We examined the correlations between an article's citation count (as an indicator of the article's quality) and different impact measures regarding the article's references (as indicators of the quality of the authors' information seeking while producing the article). Two research questions of interest were studied. First, do authors' information seeking and use affect the quality of their research output? Second, if yes, which metrics can better identify those references that may inspire researchers to produce high quality research work (so that we can recommend these references to others)? We found that the impact measures for the references have a slight or moderate correlation with article citations. Among these measures, references' article level impact measures calculated based on altmetrics data sources have a consistently stronger correlation with high quality research output, which may serve to identify helpful articles for researchers. [ABSTRACT FROM AUTHOR]

Scholars are increasingly incorporating social media tools like blogs, Twitter, and Mendeley into their professional communication. Altmetrics tracks usage of these and similar tools to measure scholarly influence on the social Web. Altmetrics researchers and practitioners have amassed a growing body of literature and working tools to gather and analyze altmetrics and there is growing interest in this emerging subfield of scientometrics. In this panel, sponsored by SIG/MET, we will present results demonstrating the utility of alternative metrics from a variety of stakeholders: researchers, librarians, publishers and those participating in academic social media sites. We will discuss and debate the value and validity of such metrics with strong degrees of participation from the audience encouraged. Metrics, for better or worse, have had a presence in the lives of scholars--we will discuss the challenges and opportunities of altmetrics for the future. [ABSTRACT FROM AUTHOR]

ABSTRACT There has been tremendous growth in the amount of scientific literature being published every year. Yet, very little of it receives press coverage. Mentions by news outlets often establish the relevance the research has to society in general. In the present study, we focus on better understanding the factors that contribute to a research article's newsworthiness. We have built three classifiers to predict the likelihood of a research article receiving online press coverage, based on features that quantify the attention it has received on various online platforms. The random forest classifier performed best with an accuracy rate of 0.92. [ABSTRACT FROM AUTHOR]