Aslib Journal of Information Management · 2017 · 102 citations · 27 references
ManagementInformation SystemsImpact MeasurementSocial Media AnalyticsText AnalyticsBibliometric AnalysisCitation NetworksResearch Impact AssessmentSocial MediaSocial Network AnalysisCitation FrequencyPublication Impact AnalysisResearch Dissemination ImpactResearch Impact MetricsResearch JournalsResearch Output Citation ImpactScholarly InfluenceScientific Influence Metrics
This study is the first to examine how academic journals’ Twitter presence influences article dissemination and citation rates. The authors aim to analyze the relationship between journal Twitter activity and research impact measured by tweets and citations. They extracted 4,176 articles from 350 journals via Plum Analytics, classified journals into four Twitter account types, and applied t‑tests and regression to compare tweet and citation counts. Journals with their own Twitter account received 46 % more tweets and 34 % more citations, and follower count was the strongest predictor of both metrics, though the model explained only 46 % of tweet variance and 18 % of citation variance.
Purpose The purpose of this paper is to analyze the relationship between dissemination of research papers on Twitter and its influence on research impact. Design/methodology/approach Four types of journal Twitter accounts (journal, owner, publisher and no Twitter account) were defined to observe differences in the number of tweets and citations. In total, 4,176 articles from 350 journals were extracted from Plum Analytics. This altmetric provider tracks the number of tweets and citations for each paper. Student’s t -test for two-paired samples was used to detect significant differences between each group of journals. Regression analysis was performed to detect which variables may influence the getting of tweets and citations. Findings The results show that journals with their own Twitter account obtain more tweets (46 percent) and citations (34 percent) than journals without a Twitter account. Followers is the variable that attracts more tweets ( ß =0.47) and citations ( ß =0.28) but the effect is small and the fit is not good for tweets ( R 2 =0.46) and insignificant for citations ( R 2 =0.18). Originality/value This is the first study that tests the performance of research journals on Twitter according to their handles, observing how the dissemination of content in this microblogging network influences the citation of their papers.
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Akshay Java, Xiaodan Song, Tim Finin et al. · 2007 · 2.7K citations
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Mike Thelwall, Stefanie Haustein, Vincent Larivière et al. · PLoS ONE · 2013 · 913 citations · Full text