Academic journal article Library Philosophy and Practice

Tweets of an Article and Its Citation: An Altmetric Study of Most Prolific Authors

Academic journal article Library Philosophy and Practice

Tweets of an Article and Its Citation: An Altmetric Study of Most Prolific Authors

Article excerpt

INTRODUCTION

With the advent of internet technologies, Web 2.0 is the current state of online technology which is characterized by greater user interactivity and collaboration. The elements of Web 2.0 like Wikipedia, Facebook, Twitter, and LinkedIn, in the virtual spaces, are called as Social Networking Sites (SNS). These elements had changed the communication and information transmission pattern by moving beyond traditional citation-based performance analysis into new citation databases that attempt to cover a large variety of the researcher's output, the impact of scholarly communication in social networks and public services. SNS had penetrated to all walks of life; these social media are not confined to the conventional communication. In the past, scholar communication is made only in scholarly journals but now blogs and other SNS had penetrated into that space. Till now the quality of a scholarly communication is measured by the number of citation, h-index and i-10 index. A new tool that tries to explain the reach of scholarly communication is Altmetric Scores which is calculated using various variables like News, Blogs, Tweets etc., ("How is the Altmetric Attention Score calculated?: Altmetric Support,2016). One important variable which contributes to the Altmetric Score is "Twitter". According to Priem et al. (2010), altmetrics is "the creation and study of new metrics based on the social web for analyzing and, informing scholarship." Altmetrics includes data about usage (e. g. pdf downloads); captures (e. g. Bookmarks); mentions (e. g. in Blogs); social media (e. g. shares on Twitter, Facebook) and citations (e. g. Scopus) (Cave, 2012). Altmetrics is proposed as an alternative to (and the extension of) the traditional bibliometric indicators (such as Journal Impact Factor or h-index). Altmetrics (Priem & Costello, 2010; Priem, Costello, & Dzuba, 2011) tracks the online mentions by pulling in data from social media, blog, traditional media and online reference managers. From an altmetrics point of view, the tweeting of research papers could be considered as an early proxy of article-level research impact (Eysenbach 2011; Priem et al. 2012; Shuai et al. 2012).Tweets can predict the citation count for a publication (Eysenbach, 2011), but this relationship cannot be considered for all kinds of data.

LITERATURE REVIEW

The first studies on Twitter came up shortly after starting the service and they were focused on describing the service and its impact on the social web communication (Java et al. 2007; Huberman et al. 2008). Earlier studies had tried to predict, how many citations an article could get in future in that case altmetric can be used as future prediction tool (Priem, Piwowar, & Hemminger, 2011). A publication from social sciences, humanities and medical and life sciences show the highest presence of altmetric score(R Costas, Zahedi & Wouters, 2015). But the presence of paper in this platform is very low (Haustein et al., 2015). Today, the quality of the scholarly article is quantified on the basis of citation. There are 33 different ways for increasing the citation count (Ebrahim, Saheli, & Embi, 2013). Some write a blog post highlighting the finding of their study to have a wide reach. Some are cited in the blog also, blog citation can be used as an alternative metric source (Patric D, 2015) (Shema, Bar-Ilan, & Thelwall, 2014). Facebook is another medium to get feedback on an article which may be likes and dislikes. The Facebook likes can also be used to predict the citations. This social media indicator can be potential early indicator of the impact of a scientific work in a particular domain of Knowledge (Ringelhan et al., 2015). From the related work it evident that various studies had been carried on altmetric and its components, but still there is no correct conclusion that each of its variables contributes to the citation.Eysenbach (2011) finding that tweets can predict highly cited articles within the first 3 days of publication. …

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