Sygocki, WitoldRychlik, Małgorzata2021-03-152021-03-152020EAHIL Conference, Łódź, 16-18.11.2020https://hdl.handle.net/10593/26189Traditional metrics are recognized indicators of impact. However, web communication channels provide scientific community with various new indicators. The main aim of this study is to define the existence of a relationship between citation counts and altmetric mentions in the group of open access scholarly papers. The study was divided into two stages. The first stage was to query the Web of Science Core Collection (WoS CC) for open access articles in the field of occupational safety and health (N=866). Citation counts were collected for all papers. The second stage of the study involved the use of the Altmetric Explorer. The tool provided altmetric indicators for the papers that were assigned a DOI (N=833). The fact that it collects data using digital identifiers of the documents, makes Altmetric Explorer transparent. Altmetric Explorer collects data from different sources: news mentios, blogs, policy websites, Twitter, patent mentions, peer review mentions, Weibo mentions, Facebook mentions, Wikipedia mentions, Google+ mentions, LinkedIn mentions, Reddit mentions, Pinterest mentions, F1000 mentions, Q&A mentions, video mentions, syllabi mentions, Mendeley readers. The chronological scope of the study covered the years 2013-2019. The data were analyzed using linear regression models. The data were collected on 3th of November, 2019. Analyzed articles collected 3,365 citation counts and 20,273 altmetric indicators. The highest number of indicators was provided by Mendeley – 15,454 and Twitter 4,110. The number of citation counts of OA articles on occupational safety and health was highly dependent on both Mendeley readers and Twitter mentions. Highly significant relationships were as follows: linear regression of Mendeley readers and citations counts: R2 = 24,28%, p < 0,0001, y = 2.080 + 0.1038x, n = 833; linear regression of Twitter mentions and citation counts: R2 = 1,25%, p < 0,0012, y = 3.725 + 0.0460x, n = 832). Conducted analysis revealed that citation counts of open access papers on occupational safety and health are dependent both on Twitter mentions as well as Mendeley readers.enginfo:eu-repo/semantics/openAccessbibliometricsopen accessaltmetricslinear regressioncitaion countsTwitterInne