Citations Gone #Social: Examining the Effect of Altmetrics on Citations and Readership in Communication Research

Abstract

Altmetrics are a relatively new phenomenon in research. These metrics measure the attention that research articles receive from nontraditional venues such as social media and the Internet. This study examined how these metrics affect both the readership and citation of articles in communication research. The study examined citation data alongside altmetrics data from academic social networking sites ResearchGate and Mendeley, as well as mentions on Facebook, Twitter, and Google+. Results indicated that all altmetrics positively correlated with citation. Posting articles on sites such as ResearchGate and Mendeley not only impacted readership, it increased the likelihood of citation. Other variables that improved readership and citation were social media mentions, downloadable articles, coauthorship, and an active online presence among scholars.

Integrating Computer Prediction Methods in Social Science: A Comment on Hofman et al. (2021)

“…Although SSCR publications are not yet integrative, explanatory approaches published in SSCR could be imagined as integrative models. For example, Wasike (2021) tested whether posting research papers in online repositories or discussing them on social media impacts citation counts among 150 of the most cited papers in communications journals using manual data collection and altmetric data. This study’s data collection and analysis could be given to a machine to predict what papers get cited more in general to check if the explanatory model maybe missed some important other factors that lead to higher or lower citation counts (i.e., could improve the causal theory of citation counts).…”

Can promotion on WeChat official accounts improve scholarly journals' academic impact? A micro‐level correlation comparison study

“…AAS complements traditional citation‐based academic impact indicators by measuring activities on social media. Despite its unclear algorithm, it has become the most popular tool to measure academic influence in social media (Priem & Hemminger, 2010), and scholarly publishers can obtain a reflection of the overall performance of the academic content across social networks by using AAS (Bornmann, 2014; Chang et al, 2019; Huang et al, 2018; Smith et al, 2019; Thelwall et al, 2013; Wasike, 2021). However, since the AAS score is not transparent it is hard to determine a clear relationship between it and final citations (Cheung, 2013; Williams, 2017).…”

Twitter como objeto de investigación en comunicación de la ciencia

“…Numerosos trabajos se centran el uso de Twitter entre académicos para la diseminación de la información científica de alto nivel (Sugimoto, Work, Larivière y Haustein, 2017; Thelwall, Haustein, Larivière y Sugimoto, 2013; Torres-Salinas, Cabezas-Clavijo y Jiménez-Contreras, 2013), llegando a estimarse que el 21% de los artículos científicos se diseminan, como mínimo, a través de un tuit (Haustein, Costas y Larivière, 2015). Es por ello que las métricas basadas en Twitter se están proponiendo cada vez más como potencial indicador de impacto de las publicaciones científicas (Priem, Groth y Taraborelli, 2012), e incluso para el propio desempeño de la ciencia por el efecto que puede causar en el número de citas y visitas web a los artículos científicos referenciados en los tuits (Wasike, 2019).…”