Introduction The idea for altmetrics originates from researchers’ need to find new ways to locate relevant and interesting scientific articles (i.e., filtering) from the ever-increasing amount of scientific publications (Priem et al. 2010). Yet altmetric events have primarily been researched from a research evaluation perspective, with some qualitative approaches to analyze the online mentions of research products recently having been introduced. Earlier research on altmetrics has focused on investigating how different altmetric counts are connected to citation counts (e.g., Thelwall, Haustein, Larivière & Sugimoto, 2013; Haustein, Lariviére, Thelwall, Amyot, & Peters, 2014; Haustein, Peters, Sugimoto, Thelwall & Larivière, 2014; Bornmann, 2015), in some cases finding evidence of a connection between the two metrics. Other studies have analysed the potential influence of various document characteristics (e.g., discipline, title length, number of references and level of collaboration) on future altmetric events that research outputs attract (e.g., Haustein, Costas & Larivière, 2015; Didegah, Bowman & Holmberg, 2016) or how citation and altmetric counts differ for different disciplines (e.g., Costas, Zahedi & Wouters 2015). The goal of many earlier studies has been to explain the meaning of altmetrics and to understand what the online attention some research receives could reveal about the research at an article level. This article continues this line of research and investigates effects at an institutional level by studying altmetric events of publications from Finnish universities. The first goal of this research is to identify if some institutional properties such as size of staff, amount of external funding, and number of international research visits have a connection to the level of online visibility the research publications receive on different online platforms. This line of investigation could reveal some new information about the mechanisms behind the creation of altmetrics and their possible connection to institutional properties of the organizations producing scientific outputs. We analyze the events aggregated by Altmetric.com and Mendeley associated with research articles from 10 universities in Finland between the years 2012 to 2014 from Wikipedia, Twitter, Facebook, mainstream news, blogs, and CiteULike, in combination with Mendeley readership counts retrieved from the Mendeley API. The second goal of this research is to investigate how the research profiles of the institutions (as measured by the distribution of Web of Science (WoS) indexed publications across different disciplines) correspond to the distribution of online attention (i.e. altmetric events) the same publications have received on different platforms. In other words, the second goal of this investigation can reveal some new insights into how well altmetrics can reflect the research profiles of universities. This article proceeds as follows: in Section 2, the literature on the subject is summarised; in Section 3, the data collection and methodology of the study are described. In Section 4, we present the results of the study (section 4.1 addresses the first research question and 4.2 addresses the second research question) and in Section 5 we discuss the results and conclude with our findings.

Data and methodology The data about Finnish research publications was retrieved from the national Juuli research publications database. Juuli is maintained by the National Library of Finland in collaboration with the Finnish Ministry of Education and Culture and CDC—IT Centre for Science. The data for the database is collected annually from Finnish research organisations. For this article, a total of 114,496 publications were collected from 14 Finnish universities ranging from the years 2012 through 2014. CrossRef was queried through their API in an effort to add any missing digital object identifiers (DOI) to the data, after which a DOI was identified for 38,819 publications. These DOIs were used to search the altmetric data provided by Altmetric.com. This data showed that a total of 12,438 Finnish research publications from 2012–2014 had at least one recorded altmetric event. For some publications it was discovered that researchers from more than one Finnish university had collaborated, and these publications were counted for each participating university in this analysis. After these steps, the final data compiled for the study contained a total of 13,031 Finnish research publications from 2012 through 2014 with at least one altmetric event captured by Altmetric.com. A summary of the amount of articles included in the study from different universities can be seen in Table 1. University Publications With assigned DOIs With at least one altmetrics event Percentage of publications with identified altmetrics events University of Helsinki 30,296 11,066 3,966 13.1 University of Turku 12,196 4,203 1,706 14.0 Aalto University 12,091 3,377 1,177 9.7 University of Eastern Finland 7,680 3,231 1,149 15.0 University of Jyväskylä 8,060 2,924 1,072 13.3 University of Oulu 6,618 3,156 1,058 16.0 University of Tampere 6,568 2,346 939 14.3 Tampere University of Technology 5,158 2,876 675 13.1 Åbo Akademi University 3,878 1,429 501 12.9 Lappeenranta University of Technology 2,557 1,162 314 12.3 University of Lapland 2,414 637 230 9.5 University of Vaasa 1,703 640 166 9.7 Hanken School of Economics 785 332 101 12.9 University of Arts 421 33 12 2.9 Total 100,425 37,412 13,066 13.0 The analysis consisted of both bibliometric and altmetric data about the research publications and descriptive data about the universities. The altmetric data contains mentions of the research publications in blog posts, news articles, Facebook posts, Twitter posts, CiteULike, Mendeley and Wikipedia articles. The descriptive data from universities consisted of the number of publications and citations in the same time period (retrieved from Web of Science), and the logarithmised amount of external funding the universities received, the proportion of foreign researchers, number of research visits, and the amount of research personnel. The latter data was retrieved from the Finnish Vipunen database, which is a national education statistics database maintained by the Ministry of Education and Culture and the Finnish National Agency for Education. In order to answer the first research question these factors were examined in relation to the altmetric events and citations. The approach of this article is similar to that of Alhoori et al. (2014), Didegah and Thelwall (2013), Thelwall, Haustein, Larivière and Sugimoto (2013), and Torres-Salinas, Robinson-Garcia and Jiménez-Contreras (2016), but examines different factors and university-level data with linear regressions instead of country-level data with correlations. This article attempts to approach the question by employing regression models. It should be noted that the data might contain some of the problems listed by Haustein (2016) as challenges of altmetrics. For example, the amount of level 4 staff (professors) or external funding in universities might very well be driving factors for total other research staff, i.e. influencing the number of other research staff. Table 2 lists some descriptive statistics for the universities in the sample. In order to answer the second research question, the universities’ research profiles—as measured by the normalized attention received from different altmetric events by the Organisation for Economic Co-operation and Development (OECD) main categories—were compared with the universities research profiles based on their research outputs as measured by Web of Science classification of the fields of publications. Due to a low number of publications in some areas, OECD categories were merged, which resulted in four main categories used for this study: Agricultural Sciences, Engineering and Technology Medical and Health Sciences Natural Sciences Social Sciences and Humanities. Median Mean Standard deviation (n) Level 4 staff 179.8 184.4 140.8 Total research staff 1121.9 1285.9 1065.4 International visits (from Finland) 209.5 292.2 188.5 International visits (to Finland) 158.8 211.9 160.6 Publications 1554.2 1750.2 1673.8 Outside funding (mn) 45.8 48.2 45.9

Results University-level factors’ influence on altmetric events The university level factors were chosen to represent different aspects of the universities’ activities: the size of the university, their internationality (to some degree), publishing activity and their level of success in securing external research funding. The following factors were tested: Level 4 staff (total working hours of professors per year) Other research staff (total working hours per year) International research visits from Finland (number of visits with a duration of at least two weeks) International research visits to Finland (number of visits with a duration of at least two weeks) Peer-reviewed published journal articles Amount of external research funding accrued from outside the university (in millions of euros) First, the effect of each potential factor was examined separately in order to avoid multicollinearity issues. The levels of significance were omitted from the tables with the ordinary least squares estimates as all variables were found to be individually statistically significant at the 1% level. It should be noted that the coefficients of the effect of the total share of foreign researchers should not be directly compared to other estimates, which are based on absolute value variables, because they define the effect of a change of 1% as opposed to a change in absolute values. The first test is defined as: (1) altmetric measur e i , t = β 1 facto r i , t + ϵ i , t M1 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ altmetric\ measure_{i,t} = {\beta _1}\,factor_{i,t} + {\epsilon_{i,t}} \] \end{document} where altmetric measure is the activity in altmetric events, factor i,t is the tested variable from the list above, for the universities i in year (t), and ∈ i,t is the error term which defines the difference between the estimated values against a linear effect. Table 3 presents the ordinary least squares estimates (standard errors in parentheses) for the chosen factors on different altmetric measures. The levels of significance were omitted from the table as all the factors were found to be strongly statistically significant as individual explanatory variables at the 1% level. The estimates explain how the change of a single unit affects the altmetric measures. For example, an increase of one full-time professor in a university increases Web of Science citations by 1.513, Wikipedia citations by 0.107 and tweets by 12.145. Web of Science CiteULike Wikipedia Blogs News Facebook Twitter Level 4 staff 1.51

(0.07) 0.76

(0.04) 0.11

(0.02) 0.41

(0.02) 0.77

(0.08) 1.11

(0.07) 12.15

(0.86) Other research staff 0.26

(0.01) 0.13

(0.01) 0.02

(0.00) 0.07

(0.00) 0.13

(0.01) 0.19

(0.01) 2.08

(0.16) International visits from Finland 1.02

(0.15) 0.51

(0.08) 0.09

(0.02) 0.28

(0.05) 0.50

(0.12) 0.78

(0.12) 8.34

(1.41) International visits to Finland 1.23

(0.17) 0.62

(0.09) 0.12

(0.02) 0.33

(0.06) 0.57

(0.14) 0.91

(0.14) 9.49

(1.69) A-type publications 0.15

(0.00) 0.07

(0.00) 0.01

(0.00) 0.04

(0.00) 0.08

(0.01) 0.11

(0.01) 1.18

(0.08) Outside funding 5.22

(0.36) 2.68

(0.21) 0.33

(0.08) 1.47

(0.13) 2.57

(0.43) 3.58

(0.42) 39.74

(4.84) Some conclusions that can be construed from the estimates in Table 3: Level 4 staff members are, on average, notably more efficient than other research staff in publishing research that is shared through the studied platforms. Whether this is due to these staff members publishing more or being more active in sharing their research through the studied channels is an open question. Foreign academic visitors to Finland have an influence on how much attention Finnish research receives online. They are, on average, somewhat more active in publishing research that is shared through the studied channels. Similarly academic visits from Finland also have a positive influence, so visiting a foreign university increases the altmetric visibility of research. Outside funding is a substantial factor in published research, although it can be argued that investing the same amount into permanent research staff could yield higher returns in research in the long run as investing a million euros for just a single year earns three to four times the effect of a single level 4 staff member, or about twenty times the same for a single other research staff member. Many of the studied factors are strongly connected to each other. For example, the amount of level 4 staff members has a strong effect on the amount of total staff. In statistical analysis this problem of two factors defining each other is called endogeneity. In order to further study the effects of the chosen factors on the altmetric measures with multiple regression models, this inherent problem has to be addressed. This can be attempted with instrumental variable methods. Based on the results of OLS-estimates in Table 3, both the level 4 staff members and outside funding appear to be strong, unrelated driving factors for all the altmetric measures. Other research staff and the amount of users for the studied altmetric source are used as instruments to eliminate some of the effects of differing amounts of users for an altmetric channel and variances in total amount of research staff in universities. The results in Table 3 give some evidence of the relationship between all the factor variables and the altmetric measures to be somewhat linear, thus the following two-stage least squares estimation is used for estimating.1 (2) altmetric measur e i , t = α + β 1 level 4 staf f i , t + β 2 outside fundin g i , t + ϵ i , t M2 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ altmetric\,measure_{i,t} = \alpha + {\beta _1}\,level\;4\;staff_{i,t} + {\beta _2}\,outside\;funding_{i,t} + {\epsilon_{i,t}} \] \end{document} where altmetric measure is the activity in altmetric events, level 4 staff and outside funding are the variables presented earlier from each university on an annual basis and (3) ϵ i , t = μ research staf f i , t + δ altmetric measure user s i , t + γ i , t M3 \documentclass[10pt]{article} \usepackage{wasysym} \usepackage[substack]{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage[mathscr]{eucal} \usepackage{mathrsfs} \usepackage{pmc} \usepackage[Euler]{upgreek} \pagestyle{empty} \oddsidemargin -1.0in \begin{document} \[ {\epsilon_{i,t}} = \mu \;research\;staff_{i,t} + \delta \;altmetric\;measure\;users_{i,t} + {\gamma _{i,t}} \] \end{document} where research staff i,t is the variable presented earlier, altmetric measure users is the number of users/sharers in the dataset and γ i,t is the error term. Table 4 presents the two-stage least squares estimates (standard errors in parentheses) for level 4 staff and outside funding when instrumented with users of the altmetric channel in question and non-professor research staff. The amount of professors is statistically significant at the 1% level for Web of Science, CiteULike, and Wikipedia citations, statistically significant at the 5% level for Facebook posts and Twitter posts, and at the 10% level for blog posts and news mentions.2 The amount of outside funding has a weak statistically significant, slightly negative effect on CiteULike readers, Wikipedia citations, and Facebook posts and a positive effect on Twitter posts. Web of Science CiteULike Wikipedia Blogs News Facebook Twitter Level 4 staff 3.412***

(1.010) 1.859***

(0.547) 0.417***

(0.149) 2.745*

(1.598) 6.119*

(3.157) 6.608**

(2.400) 86.2**

(40.4) Outside funding –4.410

(3.101) –3.093*

(1.680) –0.967**

(0.456) –6.639

(4.871) –14.73

(9.63) –15.80**

(7.31) 0.001*

(>0.001) (Constant) –143.4***

(51.8) –78.7***

(28.1) –17.5

(7.3) 120.4

(70.8) –251.8*

(142.6) –256.2*

(118.6) –3334.2*

(1864.7) Adjusted R2 0.85 0.79 0.51 0.36 0.39 0.45 0.36 N 10,757 5,171 760 2,730 5,333 7,846 86,163 Using the coefficients and adjusted R2 to directly compare the two-step least squares regressions to each other should not be done as the set of instruments change in each estimation. These measures can, however, provide some evidence for the fits of regressions. The amount of level 4 staff especially explains a portion of the changes in Web of Science citations counts CiteULike readers, and Wikipedia citations. For blogs, news posts, Facebook posts, and tweets, the model explains a smaller portion of the changes in altmetric activity when controlled with user/sharer counts and other research staff. University-level research profiles and altmetric profiles The research profiles of the universities (as measured by the distribution of published research articles across different research areas) were also examined to determine if the distribution of altmetric events across research areas would reflect the distribution of research outputs across the same research areas. Table 5 presents the distribution of published scientific articles by university and the distribution of the different altmetric events across the OECD categories. For instance, 47.4 percent of the WoS indexed publications from Aalto University are in Natural Sciences, 37.2 percent in Agricultural Sciences, Engineering, and Technology, 10.2 percent in Social Science and Humanities, and 5.2 percent in Medical and Health Sciences. Yet, the majority of publications from Aalto University that have received some attention on Twitter and Facebook (48.1% and 59.6% respectively) are in Medical and Health Sciences. WoS profile Wikipedia Twitter Facebook News Blog CiteULike Mendeley Citations (WoS) Aalto University Medical and health sciences 5.2 10.9 48.1 59.6 30.2 24.0 37.8 31.5 39.0 Natural sciences 47.4 50.9 27.0 22.1 28.1 51.4 34.6 36.1 38.4 Social sciences and humanities 10.2 5.5 8.8 5.2 3.7 1.9 6.5 12.0 3.5 Agricultural sciences, engineering and technology 37.2 32.7 16.1 13.1 38.1 22.6 21.1 20.4 19.2 University of Helsinki Medical and health sciences 36.8 24.4 47.7 44.8 33.7 28.9 39.9 31.0 34.0 Natural sciences 36.9 48.2 24.7 23.1 27.8 38.8 38.2 39.7 51.2 Social sciences and humanities 12.9 7.3 6.9 4.6 3.8 4.2 3.7 10.4 2.7 Agricultural sciences, engineering and technology 13.3 20.2 20.8 27.5 34.8 28.1 18.3 18.9 12.2 University of Eastern Finland Medical and health sciences 44.2 53.5 60.7 61.4 57.6 44.1 40.6 32.1 42.7 Natural sciences 30.3 27.9 19.0 16.4 17.1 33.9 40.4 44.2 42.3 Social sciences and humanities 7.6 0.0 5.8 4.1 3.5 3.8 5.3 7.5 2.3 Agricultural sciences, engineering and technology 17.8 18.6 14.4 18.2 21.9 18.3 13.7 16.2 12.8 University of Jyväskylä Medical and health sciences 17.3 16.1 34.6 28.6 23.7 17.5 31.3 24.8 20.9 Natural sciences 47.6 54.8 20.7 19.0 21.4 35.8 29.6 38.0 50.1 Social sciences and humanities 21.5 3.2 7.9 6.5 9.6 3.3 6.8 10.1 2.6 Agricultural sciences, engineering and technology 13.6 25.8 36.8 46.0 45.3 43.4 32.3 27.1 26.5 Lappeenranta University of Technology Medical and health sciences 0.7 19.0 56.2 78.8 70.7 44.0 42.7 30.9 40.7 Natural sciences 44.2 71.4 31.5 13.6 27.6 50.0 41.8 54.5 53.1 Social sciences and humanities 10.1 4.8 4.4 2.0 1.7 4.0 3.6 3.8 1.0 Agricultural sciences, engineering and technology 45.0 4.8 7.9 5.6 0.0 2.0 11.8 10.7 5.2 University of Oulu Medical and health sciences 27.9 27.7 51.3 44.6 33.6 21.5 40.0 29.7 35.7 Natural sciences 42.6 44.7 22.7 13.1 26.3 37.1 34.7 38.1 43.4 Social sciences and humanities 7.0 4.3 6.7 24.5 0.0 3.1 2.3 6.9 2.4 Agricultural sciences, engineering and technology 22.6 23.4 19.3 17.8 40.1 38.3 23.0 25.4 18.5 Tampere University of Technology Medical and health sciences 5.0 22.7 49.3 31.0 26.7 26.1 44.0 30.6 43.5 Natural sciences 47.3 50.0 25.3 24.1 41.9 46.7 31.1 40.5 40.8 Social sciences and humanities 5.1 4.5 10.5 6.0 4.3 6.5 4.9 12.2 2.7 Agricultural sciences, engineering and technology 42.6 22.7 14.8 38.8 27.1 20.7 20.0 16.7 13.0 University of Tampere Medical and health sciences 62.9 34.8 66.1 69.1 42.5 41.6 40.9 35.5 38.5 Natural sciences 16.6 54.3 18.1 16.2 40.7 37.1 39.4 35.9 44.8 Social sciences and humanities 13.7 6.5 4.8 5.3 4.7 2.0 5.8 12.0 3.9 Agricultural sciences, engineering and technology 6.7 4.3 11.0 9.3 12.1 19.3 13.9 16.6 12.8 University of Turku Medical and health sciences 40.4 15.5 52.9 62.9 42.4 24.0 37.6 30.1 23.1 Natural sciences 35.7 76.5 17.4 13.7 18.5 35.7 41.5 40.1 65.6 Social sciences and humanities 12.6 2.7 8.5 6.6 2.4 8.1 4.7 11.8 2.7 Agricultural sciences, engineering and technology 11.2 5.3 21.2 16.7 36.6 32.1 16.3 18.0 8.6 Åbo Akademi University Medical and health sciences 12.6 40.0 67.1 54.8 60.4 38.2 39.7 29.5 41.7 Natural sciences 44.7 40.0 17.1 22.1 21.1 34.0 35.0 40.5 38.8 Social sciences and humanities 13.0 0.0 3.1 4.3 0.3 4.9 2.3 8.9 3.5 Agricultural sciences, engineering and technology 29.7 20.0 12.8 18.7 18.2 22.9 22.9 21.1 16.0 In addition, the results show how the altmetric events from different sources are divided across the OECD categories for each university. While some universities are doing particularly well in Medical and Health Sciences on all altmetric sources (even when they do not necessarily have a medical school like Aalto University), other universities are doing especially well in Social Sciences on Facebook or Engineering and Technology in news sources. The results paint a picture of universities receiving online attention that may be different from their primary research profiles. Future research could focus on qualitative analysis of these reasons. The distributions of the events were compared between the OECD categories for all universities. The average distributions of events across different platforms (including WoS publications and citations) are presented in Figure 1. The results reflect the overall popularity of Medical and Health Sciences articles on platforms such as Twitter and Facebook, while articles in Natural Sciences receive much lower attention on Twitter and Facebook than the publishing activity in the field would suggest. The results also demonstrate an overall low attention across all platforms received by articles in Social Sciences and Humanities. The results reflect how different types of research receives more attention on different platforms. The platforms showing distributions closest to that of citations may be further evidence of the platforms closer connection or more important role in scholarly communication, however, further research is needed to confirm this. The results from the Spearman Rank correlation between the distributions (as shown in Table 6) indicate that on average the distribution of altmetric events for University of Helsinki and University of Eastern Finland across different research areas correspond very well with the distribution of their research output (0.641 and 0.742 respectively), while the altmetric events for Tampere University of Technology, University of Jyväskylä, and Aalto University do not correspond that well with their research output (–0.042, 0.001, and 0.121 respectively). The implications of these results are further discussed in the next section. Variables Aalto University University of Helsinki University of Eastern Finland University of Jyväskylä Lappeenranta University of Technology University of Oulu Tampere University of Technology University of Tampere University of Turku Åbo Akademi University Wikipedia: posts 0.80 1.00 1.00 0.20 –0.21 1.00 0.40 0.80 0.60 –0.20 Twitter: posts –0.20 0.80 1.00 –0.80 –0.40 0.80 –0.20 0.80 0.40 –0.20 Facebook: posts –0.20 0.40 0.80 –0.80 –0.40 –0.40 0.00 0.80 0.40 –0.20 News: posts 0.00 0.20 0.80 –0.80 –0.80 0.20 0.80 0.80 0.40 –0.20 Blogs: posts 0.40 1.00 1.00 –0.40 –0.40 0.40 0.40 0.80 0.00 –0.20 CiteULike: reader –0.20 0.80 1.00 –0.80 –0.40 0.80 –0.20 0.80 0.60 –0.20 Mendeley: readers 0.40 1.00 0.80 0.20 0.00 1.00 0.40 0.60 0.60 0.40 WoS: citations –0.20 1.00 1.00 0.20 0.00 1.00 –0.20 0.60 0.60 –0.20