A Large-Scale Comparison Of Social Media Coverage And Mentions Captured By The Two Altmetric Aggregators- Altmetric.Com And PlumX

A large-scale comparison of social media coverage and mentions captured
by the two altmetric aggregators- Altmetric.com and PlumX
Mousumi Karmakara, Sumit Kumar Banshalb & Vivek Kumar Singha,1
1
Department of Computer Science, Banaras Hindu University, Varanasi-221005, India
2
Department of Computer Science, South AsianUniversity, New Delhi-110021, India.
Abstract: The increased social media attention to scholarly articles has resulted in efforts to
create platforms & services to track and measure the social media transactions around scholarly
articles in different social platforms (such as Twitter, Blog, Facebook) and academic social
networks (such as Mendeley, Academia and ResearchGate). Altmetric.com and PlumX are two
popular aggregators that track social media activity around scholarly articles from a variety of
social platforms and provide the coverage and transaction data to researchers for various
purposes. However, some previous studies have shown that the social media data captured by
the two aggregators have differences in terms of coverage and magnitude of mentions. This
paper aims to revisit the question by doing a large-scale analysis of social media mentions of a
data sample of 1,785,149 publication records (drawn from multiple disciplines, demographies,
publishers). Results obtained show that PlumX tracks more wide sources and more articles as
compared to Altmetric.com. However, the coverage and average mentions of the two
aggregators vary across different social media platforms, with Altmetric.com recording higher
mentions in Twitter and Blog, and PlumX recording higher mentions in Facebook and
Mendeley, for the same set of articles. The coverage and average mentions captured by the two
aggregators across different document types, disciplines and publishers is also analyzed.
Keywords: Academic Social Networks, Altmetrics, Altmetric aggregators, Altmetric.com,
PlumX, Social Media Platforms.
Introduction
The newer forms of social media metrics (aka altmetrics) about scholarly articles, collected
from different social media platforms and academic social networks, present useful insight
about the importance and impact of the articles. Altmetrics are now being collected and
analyzed for a variety of purposes ranging from early impact assessment to measure the
correlations between altmetrics and citations. Several studies have tried to propose that
altmetrics could be an alternative to citations for assessment of the impact of research (such as
Costas, Zahedi, & Wouters, 2015; Huang, Wang, & Wu, 2018; Thelwall & Nevil, 2018;
Thelwall, 2017, 2018; Haustein et al., 2014). Owing to the increased attention on social media
1
Corresponding Author. Email: vivek@bhu.ac.in

data around scholarly articles, there are now efforts to track and measure them. Relevant data
for scholarly articles from popular social platforms (such as Twitter, Blog, Facebook) and
academic social networks (such as Mendeley, Academia) are being captured and utilized in
different ways. Altmetric.com and PlumX are two popular aggregators that track social media
activity around scholarly articles from a variety of social platforms and provide the coverage
and transaction data to researchers for various purposes.
Some recent studies have tried to analyze the coverage and data quality of the two altmetric
aggregators for same set of papers. While some studies (such as Zahedi, Fenner, & Costas,
2015; Zahedi & Costas, 2018a, 2018b; Ortega, 2018a; Bar-Ilan, Halevi, & Milojević, 2019)
focused on analyzing the agreement/ disagreement as well as differences in values of the social
metric scores across different altmetric data providers; several others (such as Meschede &
Siebenlis, 2018; Ortega, 2018b, 2018c) tried to understand the correlations among metric
values from different aggregators. Two recent studies (Ortega 2019a, 2020b) tried to analyze
the altmetric biases with respect to country, language and subjects, while another study (Ortega,
2019b) focused on inconsistencies in data from different aggregators.
Most of the previous studies, however, analyzed smaller data samples, except the relatively
recent studies by Ortega (2019a, 2019b, 2020b) that used 100,000 Crossref DOIs for analysis.
This paper, attempts to revisits the question of coverage variation, magnitude differences and
correlations in counts provided by the two aggregators, for the same set of articles. We analyzed
a large sample of 1,785,149 publication records (17 times higher than the largest data sample
used earlier), which constitutes the complete publication record for the whole world indexed
in Web of Science for the year 2016. The data sample represents different geographies,
publication types, subjects, and publishers. Our study is thus aimed to be a comprehensive
large-scale comparison of coverage and mentions tracked by the two altmetric aggregators in
overall and also across different document types, disciplines and publishers.
Research Questions
This paper attempts to obtain a conclusive and comprehensive answer to following research
questions:
RQ1: Do the two altmetric aggregators differ significantly in their coverage of social media
events for the same set of articles?
RQ2: What is the quantum of difference in altmetric mentions captured from different social
media platforms by the two altmetric aggregators?
RQ3: Do the altmetric mentions in the two aggregators, across different social media platforms,
correlate with each other?
RQ4: Do the agreements/ disagreements in the altmetric counts captured by the two
aggregators differ by document types, disciplines and publishers?

A brief overview of the two altmetric aggregators
An altmetric aggregator is typically a platform which tracks and accumulates various types of
data from different social media platforms around scholarly articles, mainly for analysis and
reporting purposes. Altmetric.com and PlumX are the two most popular altmetric aggregators.
We present below a very brief overview of the two aggregators, emphasizing on their coverage
of sources and the data collection process.
Altmetric.com2
is the first popular altmetric aggregator platform, originating in 2011 through
the efforts of Euan Adie and support of Digital Science3
. It crawls over different social media,
news, and blog platforms to collect views, mentions, comments etc. around a scholarly article.
The Altmetric.com aggregator captures the various unique identifiers, like PubMedID, arXiv
ID, SSRN ID, RePEC ID, DOIs and ISBNs, URI for the scholarly articles. Altmetric.com
makes use of various scholarly identifiers like (URLs, DOIs, PMIDs, ArXiv ids etc.) and
employ different APIs and tools to track events around scholarly articles from various sources.
For example, it uses Mendeley API to capture Mendeley reads, Wikipedia API for Wikipedia
citations, Facebook (FB) Graph API for FB mentions, GNIP API for Twitter etc. Multiple
sources of information for the same scholarly articles are cross-checked and summed up into
single entry in the respective platforms. It also computes a weighted score based on mainly
three factors-volume, sources, and authors- and provide a measure called ‘Altmetric Attention
Score’. This score is represented as a colorful donut on the article details page4
. Altmetric.com
offers various services for institutions, funding agencies, researchers, and agencies involved in
research & development (R&D). It provides a free API with rate limit to researchers on
request5
. It also provides an environment to obtain data in different formats, like JSON, CSV
etc.
PlumX is a suite of products launched by Plum analytics in 2016, initially with limited
coverage6
. Over time, these metrics evolved significantly in several ways and now it is a quite
comprehensive altmetric aggregator. Plum Analytics considered as many as 67 different types
of outputs to be tracked, which are named as ‘artifacts’. These artifacts include scholarly
articles, books, book chapters, conference articles. In addition, it also includes speeches, visual
arts, images, figures etc. It covers a very wide variety of social platforms, such as Twitter,
Facebook, YouTube; online knowledge sharing mediums, such as StackExchange, Wikipedia,
Github; bibliographical data-based sites, such as Scopus, SciELO, RePEcetc. It organizes the
captured data in five different types of metrics- usages, captures, mentions, citations, and social
media7
. The data for artifacts is collected from multiple platforms using different methods and
tools. These include data provider APIs, third party APIs, FTP data transfers, OAI-PMH
2
https://www.Altmetric.com/, accessed on 10 January, 2020
3
https://www.digital-science.com/, accessed on 10 January, 2020
4
https://www.Altmetric.com/about-our-data/the-donut-and-score/, accessed on 10 January, 2020
5
https://www.Altmetric.com/research-access/, accessed on 10 January, 2020
6
https://plumanalytics.com/learn/resources/plum-analytics-metrics-audit-log/, accessed on 10 December, 2019
7
https://plumanalytics.com/learn/about-metrics/, accessed on 10 December, 2019

harvesting, Web crawlers, and RSS feeds8
. The data harvesting is updated on different time
periods, ranging from daily to monthly basis, based on the different licensing policies of the
harvested platforms. Plum Analytics refreshes PlumX in every 3-4 hours to keep it most
updated. The data can be accessed through end-user interfaces, widgets, and APIs of Plum
analytics.
Both the aggregators, Altmetric.com and PlumX provide metrics based on data collected from
various social media, bibliographic and policy document sources. Tables 1 and 2 list the social
media, bibliographic and other sources tracked by the two aggregators. The table 1 lists a total
of 33 social media sources tracked by the two aggregators. Out of these 33 sources, 14 sources
are captured in Altmetric.com, whereas PlumX tracks 28 sources. The platforms/ sources
tracked by Altmetric.com are Twitter, Facebook, Youtube, Reddit, F1000, Blog, Mendeley,
Stack Overflow, Wikipedia, News, CiteULike, LinkedIn, Google+, and Pinterest. Out of these
14 sources, PlumX tracks most except five sources- F1000, LinkedIn, Google+, Stack
Overflow, and Pinterest. PlumX additionally tracks 19 social media sources that are not tracked
by Altmetric.com. These sources are bit.ly, Figshare, Github, Slideshare, SoundCloud,
SourceForge, Vimeo, Stack Exchange, Goodreads, Amazon, Delicious, Dryad, Dspace, SSRN,
EBSCO, ePrints, AritiiRead eBooks, Ariti Library, WorldCat. The table 2 lists the
bibliographic and policy document sources tracked by the two aggregators. Here, PlumX has a
better coverage and also provides citation metrics. PlumX covers total 16 sources whereas
Altmetric.com tracks only 6 sources. Both aggregators have only one bibliographic source in
common, which is Policy document source.
Related Work
Several previous studies tried to analyze the data from different altmetric aggregators for
different purposes ranging from assessing their accuracy to finding how much they agree on
altmetric counts for same set of scholarly articles.
Zahedi, Fenner, & Costas (2015) explored the agreement/disagreement among metric scores
across three altmetric providers namely, Mendeley, Lagotto, and Altmetric.com. They
analyzed 30,000 DOIs for the year 2013 in five common sources and analyzed possible reasons
for the differences. They found that Altmetric.com reports more tweets as compared to Lagotto
and concluded that the data capture procedure of Altmetric.com, which includes tweets, public
retweets, and comments in real-time, could be a probable reason for such differences. In later
studies, Zahedi & Costas (2018a, 2018b) have analyzed 31,437PloSOne DOIs and explored
the differences in metrics provided by four aggregators Crossref Event Data (CED),
Altmetric.com, Lagotto, and Plum Analytics. They focused on the process of data collection
used by different aggregators and that how different aggregators define metrics from the data
collected. The results showed that Mendeley (r>0.8) and Twitter (0.5≤r≤0.9) have good
agreement across aggregators, whereas Facebook (0.1≤r≤0.3) and Wikipedia (0.2≤r≤0.8) have
the lowest agreement. They attributed this to the methods of tracking and processing data. For
8
https://plumanalytics.com/niso-altmetrics-working-group-on-data-quality/, accessed on 10 December, 2019

example, the effect of direct data collection or collection through third-party APIs, aggregation
of data based on different versions, identifiers, types, etc., and the impact of frequency of
update, etc. They recommended that one should not rely only on the aggregators showing a
higher count for the metric.
Meschede & Siebenlist (2018) explored about the relationship between the metrics across
(inter-correlation) two aggregators PlumX and Altmetric.com, as well as between the metrics
within the aggregator itself (intra-correlation). They analyzed sample of 5,000 journal articles
from six disciplines(‘Computer Science, Engineering and Mathematics’, ‘Natural Sciences’,
‘Multidisciplinary’, ‘Medicine and Health Sciences’, ‘Arts, Humanities and Social Sciences’
and ‘Life Sciences’) and analyzed them for the eight common sources (‘Facebook’, ‘Blogs’,
‘Google+’, ‘News’ , ‘Reddit’, ‘Twitter’, ‘Wikipedia’ and ‘Mendeley’)in both aggregators. The
study showed that PlumX (99%) has higher overall coverage of the data chosen for analysis as
compared to Altmetric.com (39%). The intra-correlation between the metrics within the same
platforms are weak. They further observed that PlumX and Altmetric.com are highly inter-
correlated in terms of Mendeley and Wikipedia (with correlation coefficient values 0.97 and
0.82 respectively) but weakly correlated for other sources- Facebook (0.29), Blogs (0.46),
Google+ (0.28), News (0.11), Twitter (0.49), and Reddit (0.41).
Ortega (2018a) analyzed the difference in altmetric indicator counts in Crossref event data,
Altmetric.com, and PlumX, using a sample 67,000 papers. For each platform, the difference in
metrics across aggregators was quantified in terms of counting differences. Counting difference
was computed by taking the sum of the differences in metrics provided by two aggregators at
the document level and dividing by the number of publications that have non zero altmetric
events and occur in both aggregators. They concluded that different aggregators should be used
for data from different platforms, such as PlumX for Mendeley reads and Altmetric.com for
tweets, news & blogs. In another study, Ortega (2018b) has grouped different altmetrics into
three groups: social media, usage, citations using principle component analysis (PCA). In this
study data from Altmetric.com, Scopus and PlumX for a set of 3,793 articles published in 2013,
was used. Considering that the earlier studies provided evidence that some specific aggregators
perform better for some specific data sources; they collected different indicators from different
aggregators. These included tweets, Facebook mentions, news, blogs etc. from Altmetric.com;
citations from Scopus; Wikipedia mentions from CED; and views & Mendeley reads from
PlumX. Results showed that instead of using a single metric, such as altmetric score, one should
consider the relatedness of metrics and their impact across different disciplines for evaluating
research.
Ortega (2018c) examined the emergence and evolution of five altmetrics (download, views,
tweets, readers, and blog mention) along with bibliometric citations from the publication date
of a document. The study also investigated the evolution of the relationships among these
metrics by analyzing 5,185 papers from PlumX on a month to month basis. The results showed
that in a document’s entire life cycle, altmetric mentions are fast appearing ones, whereas
citations appearance is slow. Based on the relationship analysis of metrics, the study suggested
that the reader counts influence citations.

A series of studies (Ortega, 2019a, 2019b, 2020b) analyzed coverage of news and blog sources
in three aggregators namely, Crossref event data, Altmetric.com, and PlumX, by taking
100,000 Crossref DOIs. The results showed that, the overlap of these sources across
aggregators are comparatively low in numbers (Ortega, 2019a). As for example, Altmetric.com
has a higher coverage for blog (37.8%) but only 7.8% of the publication set is commonly
covered in the three aggregators. The coverage in one aggregator might be high for the same
set of articles but the lower overlapping ratio shows that the sources covered in aggregators
vary widely. The main objective of the study in Ortega (2020b) was to explore altmetric biases
with respect to country, language and subjects with a dataset of 100,000 DOIs. Author has
retrieved the sources which covered the randomly selected publication set and categorized them
based on their regions, language and interest level. It shows that, Altmetric.com is the most
heterogeneous aggregator geographically and linguistically. However, PlumX has more
coverage towards local news events, particularly for USA. Their conclusion serves as evidence
that English is the most prevailing language. News and blog sources are mostly from general
interest, social science and humanities disciplines. From this same dataset, Ortega (2019b)
extracted the blog and news links to verify the validity, coverage, and presence of the tracked
blog mentions and news mentions of the scholarly articles. There were 51,000 news & blog
links found in this extraction process, which were explored for their existence and it was found
that almost one-third of the links are broken. This elaborate longitudinal study concluded that
these mentions should be audited periodically as the aggregators are dependent on third-party
providers.
Bar-Ilan, Halevi, & Milojević (2019) have analyzed altmetric data of 2,728 JASIST articles
and reviews, provided by Mendeley, Altmetric.com and PlumX in two different points of time
2017 and 2018. They observed increase in overlap in coverage of documents with Mendeley
reader across the three sources over time. There were 874 papers commonly covered in all
sources in 2017, which increased to 1,021 papers in 2018. Further an increase in Mendeley
reader counts and citations was also observed. They suggested using more than one aggregator
to obtain altmetric indicators and to compare them in order to get reliable altmetrics.
Ortega (2020a) has performed a meta-analysis over a set of 107 altmetric articles related to five
altmetric aggregators, namely, Altmetric.com, Mendeley, PlumX, Lagotto, and ImpactStory,
published during 2012-2019. The dataset consisted of papers that had either computed or
published data useful in the computation of three metrics: coverage, platform wise coverage,
and average mentions. The usage percentage of all the aggregators was explored. Almetric.com
(54%) was found to be the most prevalent provider, followed by Mendeley (18%) and PlumX
(17%). The analysis showed that Altmetric.com tracks more events for Twitter, News, and
Blogs whereas PlumX performs well in FB and Mendeley platforms. The results exhibited
gradual increase in tweet capture by PlumX.

Data
Since the focus of the work is comparing the coverage of research publications and altmetrics
provided in two popular social media aggregators- Altmetric.com and PlumX, we analyzed the
variation in coverage for the whole world’s research output for the year 2016. The complete
set of research publications indexed in Web of Science (WoS) for the year 2016 are
downloaded. The download was performed in the month of Sep. 2019. Since WoS does not
allow downloading data above 100,000 records, therefore the data is collected based on Web
of Science Categories (WC). The WC based data collection has an inherent problem of
duplicity since in WoS a paper is generally tagged under many WCs. Due to this duplicity
initially, a total of 3,545,720 records are obtained for all WCs taken together, comprising of
the standard 67 fields- including TI (title), PY (publication year), DI (DOI), DT (document
type), SO (publication name), DE (author keywords), AB (abstract). After the removal of
duplicate entries and some erroneous records, we were left with 1,785,149 publication records.
The altmetric data for the publication records found in the two aggregators- Altmetric.com and
PlumX- was obtained thereafter. In order to obtain altmetric data from Altmetric.com, a DOI
look up was performed for all the DOIs in the WoS data. Out of 1,785,149 publication records,
a total of 902,990 records are found to be covered by Altmetric.com, which is about 50.58%
of the total data. The data obtained from Altmetric.com had 46 fields, including DOI, Title,
Twitter mentions, Facebook mentions, News mentions, Altmetric Attention Score, OA Status,
Subjects (FoR), Publication Date, URI, etc. The data from Altmetric.com was downloaded in
the month of Sep. 2019.Since we did not have an API access for PlumX, we contacted PlumX
team to provide us with access to PlumX data for the 1,785,149 publication records we had.
They agreed to provide us with data and created a dashboard access for us for the concerned
publication records. Out of the 1,785,149 publication records, a total of 1,661,477 publication
records were found covered in PlumX, which constitutes about 93.07% of the whole data.
PlumX provides metrics in five categories, from a wide range of source platforms. The PlumX
data was downloaded in the month of Nov. 2019. This data included fields like DOI, Title,
Year, Repo URL, Researcher Name(s), Captures:Readers:Mendeley, Social
Media:Tweets:Twitter, Social Media:Shares, Likes &Comments:Facebook etc. This data also
has a field named Plum stable url which redirects to the page from where one can get the actual
tweets, blogs etc. For our analysis we have analyzed data for four platforms- Twitter, Facebook,
Mendeley, and Blog platforms- as covered in both the aggregators.
Methodology
In this exploratory analysis, the data obtained from three different data sources have been
analyzed on six aspects, for the two aggregators: variation in coverage, difference in magnitude
of mentions, correlations in mention values, variation across document types, variation by
discipline and variation across publishers.
First of all, the coverage of scholarly articles in different social media platforms by the two
aggregators was compared. The altmetric data for the articles in consideration was obtained

from the two aggregators corresponding to the four social media platforms: Twitter, Facebook,
Blogs and Mendeley. The percentage of articles covered in the four social media platforms as
per the data from the two aggregators was identified.
Secondly, the magnitude of mentions in the four social media platforms for the articles was
analyzed and the difference in magnitude of mentions in the data drawn from the two
aggregators was computed. Statistical measures (mean and median) were computed for the
differences in values from each of these platforms.
Thirdly, the correlation between mention values for different social media platforms, as drawn
from the two aggregators, was computed. For computing correlations, the options were to
compute Pearson Correlation or Spearman Rank Correlation. However, as it has been observed
in previous studies (such as Thelwall & Nevill, 2018) that the altmetric data are highly skewed,
therefore, we have used Spearman Rank Correlation, which is more suitable for such skewed
data. The Spearman Rank Correlation Coefficient (SRCC) was computed between the different
types of mentions available from the two aggregators. The built-in function ‘corr’ available in
pandas module of python programming language was used for this purpose, value ‘spearman’
passed as parameter to the function. The value of SRCC lies between -1 to +1, with positive
values indicating positive correlation, value of 0 indicating no correlation, and negative value
indicates negative correlation.
Fourthly, the difference in coverage and mentions captured by the two aggregators for the five
social media platforms was analyzed across different document types. The document type of
articles was taken from the ‘DT’ tag in the WoS record file. The values for ‘DT’ include journal
articles, proceedings paper, book chapters, reviews, book reviews, editorial material etc. The
variation in coverage levels and magnitude of mentions for different social media platforms
was thus obtained for these document types.
Fifthly, the difference in coverage and mentions across different disciplines was computed by
grouping the publication records into different disciplines. Each publication record was
grouped into one of the fourteen major disciplinary categories as per the scheme proposed in
(Rupika et al., 2016). The Web of Science Category (WC) field information for each
publication record is seen and based on its value the publication record is assigned to one of
the fourteen broad disciplinary categories. These fourteen broad disciplinary categories are as
follows: Agriculture (AGR), Art & Humanities (AH), Biology (BIO), Chemistry (CHE),
Engineering (ENG), Environment Science (ENV), Geology (GEO), Information Sciences
(INF), Material Science (MAR), Mathematics (MAT), Medical Science (MED),
Multidisciplinary (MUL), Physics (PHY) and Social Science (SS). This disciplinary grouping
into 14 broad categories instead of more than 255 categories of Web of Science, made the
analysis more manageable and easier to understand. The variations in coverage and magnitude
of mentions were thus computed for publication records in each of the fourteen disciplinary
groups.
Finally, difference in journal coverage and mentions was computed for 16 most frequent and
well-known publishers namely ‘Springer’, ‘Nature’, ‘PLoS’, ‘Elsevier’, ‘IEEE’, ‘Wiley’,
‘Taylor & Francis’, ‘ACM’, ‘IOP’, ‘Oxford University Press’, ‘Sage’, ‘Hindawi’, ‘Cell Press’,

‘MDPI’, ‘Cambridge University Press’, and ‘Emerald’ across two aggregators. The publisher
information was obtained from the ‘PU’ tag of WoS records. In the PU field same publishers
are present in different forms. For e.g. Elsevier have variants such as Elsevier Science Ltd,
Elsevier Masson, and Elsevier Science Bv. All such variants represent same parent publisher
Elsevier. To capture all such variants of any publisher we employed partial string matches in
the PU field. This way all publication records for different publishers are obtained and
differences in their coverage and in mention counts are computed across the two aggregators.
Results
The altmetric data captured by the two aggregators for the large sample of articles was analysed
to identify differences in coverage and magnitude of mentions across different platforms. The
differences in mentions captured by the two aggregators was also analysed across different
disciplines, document types and publishers.
Difference in coverage of the two aggregators
First of all, the difference in coverage of the two altmetric aggregators was identified. It was
observed that out of the total set of 1,785,149 publication records, a total of 902,990 records
are found to be covered by Altmetric.com (which is about 50.58% of the total data), and a total
of 1,661,477 publication records were found covered in PlumX (which constitutes about
93.07% of the whole data). Figure 1 shows the overlap of coverage of the two aggregators. It
can be seen that a total of 879,981 articles are commonly covered by the two aggregators.
About 97.5% of articles covered by Altmetric.com are also covered by PlumX, whereas
Altmetric.com covers only 53% of articles tracked by PlumX. The PlumX aggregator has 47%
of articles uniquely covered. Thus, it is observed that PlumX has a higher overall coverage of
articles (including uniquely covered articles) as compared to Altmetric.com.
We have tried to find out whether the difference in coverage of the two aggregators is similar
across different platforms. Figure 2 shows a bar chart of article coverage of the two aggregators
for four different platforms- Twitter, Facebook, Mendeley and Blog. It can be observed that
PlumX has a better coverage for Mendeley platform, whereas Altmetric.com has an edge over
PlumX in coverage in the Twitter and Blog platforms. The coverage for Facebook platform of
the two aggregators is almost similar. The magnitude of coverage difference between the two
aggregators is highest for Mendeley and lowest for Facebook. Thus, while PlumX has an
overall higher coverage of articles, Altmetric.com has better coverage in two of the four
platforms analysed.
Difference in magnitude of mentions
The mean and median values of number of mentions for the four platforms as tracked by the
two aggregators was computed. Table 3 shows the number of articles tracked by the two
aggregators across the different platforms, along with the mean and median values of mentions.

It can be observed that the mean value of mentions for Twitter and Blog platforms is higher in
Altmetric.com, whereas the mean value of mentions for Facebook and Mendeley is higher in
PlumX. In case of Facebook platform, PlumX platform has significantly higher value of mean
and median of mentions as compared to Altmetric.com. It may, however, be noted that these
values are for different number of articles tracked by the two aggregators.
A more useful comparison of the value of mentions would require comparing the mentions for
the commonly covered set of articles by the two aggregators. Therefore, we have compared the
values of mentions captured by the two aggregators across different platforms for the same set
of commonly covered articles. The difference in mention value for the papers in Altmetric.com
and PlumX is computed. Figure 3 shows the mean of differences in mentions in the four
platforms as tracked by the two aggregators. It is observed that in case of Twitter and Blog
platforms, the mean value of differences is positive indicating that Altmetric.com captures
higher number of mentions as compared to PlumX in these platforms. In the Facebook and
Mendeley platforms, PlumX appears to have higher number of mentions tracked as compared
to Altmetric.com.
In order to gain further insight into the difference in magnitude of mentions, we have also
plotted the frequency of differences in mentions across different platforms by the two
aggregators. Figure 4 (a) – (d) present the frequency values of differences in mentions in the
two aggregators for the Twitter, Facebook, Mendeley and Blog, respectively. Figure 4(a)
shows the histogram for the differences in Twitter platform. These differences are for 565,445
commonly covered articles for Twitter platform, with at least one tweet captured in both the
aggregators. It can be seen that a good percentage (approximately 50%) of papers has tweet
difference equal to zero, indicating that both platforms record same number of tweets for these
papers. However, the slope is inclined towards the positive side, indicating that Altmetric.com
captures more tweets for a good number of the articles as compared to PlumX. We looked at
some examples to verify this and found this valid. One example paper titled “When the Great
Power Gets a Vote: The Effects of Great Power Electoral Interventions on Election Results”
has 24,318 tweets captured by Altmetric.com, whereas PlumX captured only 493 tweets for
this paper.
Figure 4(b) shows the histogram of article level differences in Facebook platform. Here the
plot is created for 71,437 commonly covered articles in Facebook platform, that have non-zero
FB mentions in both aggregators. It is observed that in approximately 16% of the articles, the
difference in mentions is zero. However, the slope is clearly inclined towards the negative side,
indicating that PlumX captures more mentions per article as compared to Altmetric.com for
majority of the articles. One example article to mention would be the article titled “CRISPR
gene-editing tested in a person for the first time”, which has 62,290 mentions captured by
PlumX but only 341 mentions captured by Altmetric.com.
The histogram for the differences in mentions in the Mendeley platform is shown in Figure
4(c). Here, the plot is made for a total of 830,520 commonly covered articles in Mendeley
platforms, that have at least one read recorded in both the aggregators. In this case too, it is
seen that pattern is inclined more towards the negative side, indicating that PlumX captures

more reads per article than Altmetric.com for majority of the articles. About 25% of articles
have the same number of mentions recorded by the two aggregators. One example article would
be article titled “Mastering the game of Go with deep neural networks and tree search” that has
39,621 records captured by PlumX but only 7,900 reads captured by Altmetric.com.
Figure 4(d) plots the histogram of the differences in Blog mentions for the 14,387 commonly
covered articles in Blog platform, with non-zero mentions captured by both the aggregators. In
this case, it is observed that more than 40 % articles have this difference equal to zero. The
pattern, however, is inclined towards the positive side, indicating that Altmetric.com captures
more mentions as compared to PlumX for a good number of articles. One example article to
mention would be an article titled “Planet Hunters IX. KICÂ 8462852 Â– where's the flux?”
that has 95 mentions captured by Altmetric.com but only 12 mentions captured by PlumX.
Thus, a perusal of the figures 4 (a) to (d) indicate that Altmetric.com captures more mentions
per article in case of Twitter and Blog platform, whereas PlumX captures more mentions per
article for the Mendeley and Facebook platforms.
Correlations in mentions
We have also computed correlation between the mention values for different platforms across
the two aggregators. The Spearman Rank Correlation Coefficient (SRCC) between mentions
is computed for the articles commonly covered by the two aggregators. Table 4 shows the
SRCC values in the article-mentions across the two aggregators. It can be observed that the
correlation values for Twitter and Mendeley platforms are 0.823 and 0.95, respectively,
indicating strong correlation. In case of Facebook and Blog platforms, these values are 0.272
and 0.424, respectively, indicating lower correlation. Thus, it can be said that there is more
agreement in mention-based ranks of articles in Twitter and Mendeley platforms, between the
two aggregators. The mention values differ in more random manner in the other two platforms.
The intra-platform correlations across the two aggregators are also shown, each of which are
less than 0.5, indicating weak positive rank correlations across the platforms in the two
aggregators.
Variations across document types
It would be interesting to check whether the coverage and mentions in different platforms as
captured by the two aggregators vary across different document types. We have, therefore,
analysed the coverage and mentions for the articles of different document types. These
document types correspond to Article, Book, Book Chapter, proceedings paper and Review, as
defined by the Web of Science. Table 5 shows the coverage and average mentions for Twitter,
Facebook, Mendeley and Blog platforms of the different document types. It is observed that
Altmetric.com has better coverage in Twitter and Blog platforms for almost all document types.
In case of average mention values too, Altmetric.com has higher values across almost all
document types in Twitter and Blog platforms. The PlumX platform is found to have better
coverage and average mention values across almost all document types in the Facebook and

Mendeley platforms. Thus, looking at the results across document types, it is seen that the
overall trend of better coverage of Altmetric.com for Twitter and Blog and of PlumX for
Facebook and Mendeley appear to be hold valid across different document types.
Variations across disciplines
The variations in coverage and mentions between the two aggregators is also analysed across
different disciplines. We have used the data grouping into fourteen broad disciplines. Table 6
presents the coverage and avg mention values in the four platforms. It is observed that in the
Twitter platform, Altmetric.com has better coverage and higher mention values than PlumX
for almost all disciplines. In case of Facebook platform, PlumX has higher mention values for
almost all disciplines. The coverage, however, is not higher for PlumX in Facebook for all
disciplines as disciplines like MED, AH, SS, BIO, and AGR has higher coverage by
Altmetric.com. In Mendeley platform, PlumX has higher coverage in all disciplines, but in
terms of reads, PlumX captures higher reads only for MED, SS, BIO, GEO, and MUL
disciplines. In case of Blog platform, Altmetric.com has better coverage than PlumX across
almost all disciplines and the average mention values of Altmetric.com are higher except for
PHY, ENV, MAT and ENG disciplines. Thus, the analysis of data across different disciplines
shows an overall trend of better coverage of Altmetric.com of Twitter and Blog and PlumX of
Facebook and Mendeley, except in case of some disciplines where slightly different patterns
are observed.
Variations across Publishers
We have also tried to see if the patterns of variations in coverage and mentions in the two
aggregators change across different publishers. In order to analyse this, articles for the 16 most
frequent publishers in the data are identified and analysed. Table 7 present the coverage and
average mention values for data for these publishers in the four platforms for the two
aggregators. In terms of number of journals for which data is covered, the PlumX aggregator
has an edge over Altmetric.com. For example, PlumX covers 76 more journals of Springer than
Altmetric.com, 34 more journals of Elsevier and 31 more journals of Taylor & Francis. It can
be further observed that PlumX covers more than 90% of publication records for all Publishers
except for Cambridge Univ Press (84.1%), whereas coverage of Altmetric.com varies
significantly between 25% to 86%. Altmetric.com has minimum coverage of about 25% for
IEEE and highest coverage of 86.88% for PLoS publications. In terms of coverage and
mentions for the four platforms, it is found that Altmetric.com has higher coverage in Twitter
for almost all publishers. In Facebook platform, Altmetric.com shows higher coverage for all
publishers except PLoS, Hindawi, and MDPI. In Mendeley platform, the coverage and average
reads captured by PlumX are higher for all publishers except Springer, IEEE, Taylor & Francis,
ACM and Hindawi. In case of Blog platform, Altmetric.com has in general better coverage and
average mention values than PlumX, though for IEEE, IOP, Hindawi, and Emerald publishers
the PlumX aggregators capture more mentions. Thus, in general it is observed that
Altmetric.com has better coverage of Twitter and PlumX has better coverage of Facebook,

irrespective of the publisher. However, in case of Mendeley and Blog platforms, the coverage
and mention values of the two aggregators do not show same patterns for all the publishers.
Discussion
The article tried to present a comparative analysis of two well-known altmetric aggregators,
namely, Altmetric.com and PlumX for four platforms- Twitter, Facebook, Mendeley and Blog.
The variations in coverage and mention values captured by the two aggregators for different
platforms is analyzed across different document types, disciplines and publishers as well.
The results show that PlumX has an overall higher and wider coverage than Altmetric.com,
with PlumX tracking about 93% articles as compared to Altmetric.com tracking about 50%
articles. Some previous studies (Meschede & Siebenlist, 2018; Ortega, 2018b; 2019a; Zahedi
& Costas, 2018b) have also found that PlumX has higher coverage of articles, with close to
95% articles tracked.
However, the coverage differentiation is not same across all the four platforms. In case of
Twitter and Blog platforms, Altmetric.com has better coverage than PlumX. Ortega (2018a)
found similar pattern for Twitter, with Altmetric.com having better tracking of Twitter platform
than PlumX. In case of Blog platform, Ortega (2020b) noted that Altmetric.com has better
coverage than PlumX. In case of Mendeley platform, PlumX has higher coverage than
Altmetric.com. One possible reason for this may be that PlumX and Mendeley are from the
same parent company and hence better integration of data capture process. The coverage level
of Facebook platform by the two aggregators is found to be quite similar, with PlumX having
an edge over Altmetric.com. One possible reason for Altmetric.com recording slightly lesser
Facebook mentions is that it has a policy of recording posts only from public pages9
. Ortega
(2020a) has found that in collecting mentions from Facebook and Mendeley, Altmetric.com
has performed poorly as compared to PlumX. It was found in previous studies (Zahedi &
Costas, 2018b; Ortega, 2018a) that in general, Altmetric.com captures more mentions per
article in case of Twitter and Blog platform, whereas PlumX captures more mentions per article
for the Mendeley and Facebook platforms.
In terms of correlations between the two aggregators, for mentions in the same platform,
Twitter and Mendeley achieve higher correlation values indicating similar magnitude of
mentions captured by the two aggregators for the commonly covered set of articles. The
correlation values are in the lower range in case of Facebook and Blog platform, indicating
higher differences in mentions captured by the two aggregators in these platforms. These
findings for Mendeley shows agreement with previous studies where this platform was noted
to have the highest inter-correlations across the aggregators (Zahedi & Costas, 2018b).
However, for Twitter platform, it contradicts with finding of Meschede & Siebenlist (2018),
9
https://help.altmetric.com/support/solutions/articles/6000060968-what-outputs-and-sources-does-
altmetric-track-, accessed on 16 November, 2020.

where it was found to be in the lower similarity group along with other platforms like Facebook,
Blog etc.
The variations of coverage and mention values of the two aggregators in the four platforms
across different document types, disciplines and publishers show interesting patterns. Out of
these three aspects, only discipline has been explored earlier by Ortega (2020b) for Blog and
News mentions. The variations by publisher and document types have not been explored
earlier. The results show that, in general Altmetric.com has better coverage and higher mention
values than PlumX for Twitter platform across different document types, disciplines and
publishers. Similarly, PlumX platform is seen to have better coverage and higher mention
values than Altmetric.com in case of Facebook, irrespective of the document type, discipline
and publisher. However, in case of Mendeley and Blog platforms, the coverage and average
mention values of the two aggregators do not show a consistent pattern across all the document
types, disciplines and publishers. In some cases, PlumX has better coverage and higher
mentions than Altmetric.com while in several other cases Altmetric.com has better coverage
and higher mentions. Thus, the variations in coverage and mentions across document types,
discipline and publishers are more clearly seen in case of Mendeley and Blog platforms.
The present study, thus, presents a comprehensive account of variations in coverage and
mention values captured by the two aggregators- Altmetric.com and PlumX- across four
different platforms. Further, the study also is perhaps the first effort to have analysed the
variations across different document types and publishers. The analytical results are interesting
and useful, with some contradicting whereas several others agreeing to findings of the previous
studies, as illustrated above. The results have practical implications in terms of suggestion for
use of a specific aggregator for data from different platforms.
Conclusion
The article presents following useful results and conclusions. Firstly, PlumX has an overall
higher coverage than Altmetric.com and tracks a wider number of platforms. Secondly,
Altmetric.com captures more mentions per article in case of Twitter and Blog platform,
whereas PlumX captures more mentions per article in case of Mendeley and Facebook
platforms. Thirdly, Altmetric.com and PlumX agree more in their mention values for Twitter
and Mendeley platforms but mention values differ more in case of Facebook and Blog
platforms, as observed by the correlation values. Fourthly, Altmetric.com is found to have
better coverage of Twitter whereas PlumX has better coverage of Facebook, across different
document types, disciplines and publishers. In case of Mendeley and Blog platforms, variations
in patterns of coverage and magnitude of mentions are observed across different document
types, disciplines and publishers. Overall, the analytical results present a comprehensive
account of the variations in coverage and mentions of the two aggregators across four different
platforms.

Acknowledgement
The authors would like to acknowledge support of Stacy Konkiel, Director of Research
Relations at Digital Science for providing access to Altmetric.com and Stephanie Faulkner
Director of Product Management and Operations at Elsevier Research Metrics for providing
dashboard access to PlumX data for our research work.
References
Bar-Ilan, J., Halevi, G. and Milojević, S., 2019. Differences between Altmetric Data Sources
– A Case Study. Journal of Altmetrics, 2(1), p.1. DOI: http://doi.org/10.29024/joa.
Costas, R., Zahedi, Z., &Wouters, P. (2015). Do “altmetrics” correlate with citations?
Extensive comparison of altmetric indicators with citations from a multidisciplinary
perspective. Journal of the Association for Information Science and Technology, 66(10), 2003-
2019.
Haustein, S., Peters, I., Bar-Ilan, J., Priem, J., Shema, H., & Jens, T. (2014). Coverage and
adoption of altmetrics sources in the bibliometric community. Scientometrics, 101(2), 1145–
1163.
Huang, W., Wang, P., & Wu, Q. (2018). A correlation comparison between Altmetric Attention
Scores and citations for six PLOS journals. PloS one, 13(4), e0194962.
Meschede, C., & Siebenlist, T. (2018). Cross-metric compatibility and inconsistencies of
altmetrics. Scientometrics, 115(1), 283-297.
Ortega, J. L. (2018a). Reliability and accuracy of altmetric providers: a comparison among
Altmetric. com, PlumX and Crossref Event Data. Scientometrics, 116(3), 2123-2138.
Ortega, J. L. (2018b). Disciplinary differences of the impact of altmetric. FEMS microbiology
letters, 365(7), fny049.
Ortega, J. L. (2018c). The life cycle of altmetric impact: A longitudinal study of six metrics
from PlumX. Journal of Informetrics, 12(3), 579-589.
Ortega, J. L. (2019a). The coverage of blogs and news in the three major altmetric data
providers. In 17th International conference of the international society for scientometrics and
informetrics, Rome, Italy.
Ortega, J.L., (2019b). Availability and Audit of Links in Altmetric Data Providers: Link
Checking of Blogs and News in Altmetric.com, Crossref Event Data and PlumX. Journal of
Altmetrics, 2(1), p.4. DOI: http://doi.org/10.29024/joa.
Ortega, J. L. (2020a). Altmetrics data providers: A meta-analysis review of the coverage of
metrics and publication. El profesional de la información (EPI), 29(1).

Ortega, J. L. (2020b). Blogs and news sources coverage in altmetrics data providers: a
comparative analysis by country, language, and subject. Scientometrics, 122(1), 555-572.
Rupika, Uddin, A. & Singh, V. K. (2016). Measuring the university–industry–government
collaboration in Indian research output. Current Science, 1904-1909.
Thelwall, M. (2017). Are Mendeley reader counts high enough for research evaluations when
articles are published? Aslib Journal of Information Management, 69(2), 174–183.
https://doi.org/10.1108/AJIM-01-2017-0028
Thelwall, M. (2018). Early Mendeley readers correlate with later citation counts.
Scientometrics, 115(3), 1231–1240. https://doi.org/10.1007/s11192-018-2715-9
Thelwall, M., & Nevill, T. (2018). Could scientists use Altmetric.com scores to predict longer
term citation counts? Journal of Informetrics, 12(1), 237–248.
Zahedi, Z., & Costas, R. (2018a). Challenges in the quality of social media data across altmetric
data aggregators. Proceedings of 23rd International Conference on Science and Technology
Indicators.
Zahedi, Z., & Costas, R. (2018b). General discussion of data quality challenges in social media
metrics: Extensive comparison of four major altmetric data aggregators. PloS one, 13(5),
e0197326.
Zahedi, Z., Fenner, M., & Costas, R. (2015). Consistency among altmetrics data
provider/aggregators: What are the challenges? Proceedings of Altmetrics workshop, 9 October
2015, Amsterdam Science Park, Amsterdam.

TABLES
Table 1: Social Media Sources Tracked by the two aggregators
Source(s) Altmetric.com PlumX
Twitter x x
Facebook x x
YouTube x x
Reddit x x
F1000 x
bit.ly x
Blog x x
Figshare x
GitHub x
Mendeley x x
Slideshare x
SoundCloud x
SourceForge x
Vimeo x
Stack Exchange x
Stack Overflow x
Wikipedia x x
News x x
Goodreads x
Amazon x
Delicious (historical only) x
CiteULike (historical only) x x
Dryad x
DSpace x
SSRN x
EBSCO x
ePrints x
AiritiiRead eBooks x
Airiti Library x
WorldCat x
LinkedIn x
Google+ x
Pinterest x
Table 2: Bibliographic Impact & Policy Implementation Sources tracked by the two
aggregators
Source(s) Altmetric.com PlumX
Dynamed Plus Topics x
Ariti Academic CitationIndex x
National Institute for Health and Care
Excellence (NICE)
x
OJS Journals x
Open Syllabus x
Patent Citations x

Peer Reviews x
PLOS x
Policy document source x x
PubMed Central Europe x
PubMed Clinical Guidelines x
PubMedCentral (for PLOS articles only) x
RePEc x
SciELO x
Scopus x
USPTO x
Web of Science x
CrossRef x
Bepress x
CABI x
Dimensions x
Table 3: Statistics of mentions for different platforms in the two aggregators (only mentions >0)
Platforms Altmetric.com (902,990) PlumX (1,661,477)
No. of
Articles
Mean Median No. of
Articles
Mean Median
Twitter 700,985 9.56 2.0 600,051 7.46 2.0
FB 185,243 2.38 1.0 182,556 47.57 5.0
Mendeley 877,685 34.37 20.0 1,540,214 35.08 16.0
Blog 70,387 1.92 0.0 23,052 1.64 1.0
Table 4: Spearman Rank Correlation between mention counts in the two aggregators
PlumX
Altmetric.com Twitter FB Mendeley Blog
Twitter 0.823 0.330 0.353 0.261
FB 0.236 0.272 0.135 0.195
Mendeley 0.321 0.182 0.950 0.176
Blog 0.348 0.303 0.213 0.424
Table 5: Document type wise distribution of mentions in the two aggregators
Document
Type
Aggregator #Twitter Avg.
Tweets
#FB Avg. FB
Mentions
#
Mendeley
Avg
Reads
#Blogs Avg Blog
Mentions
Article
Altmetric.com 545,842 8.286 140,542 2.217 691,290 33.073 55,730 1.951
PlumX 468,520 6.377 142,275 37.497 1,225,475 34.218 16,910 1.646
Book
Altmetric.com 6,055 5.801 1,184 1.671 6,502 28.305 331 1.344
PlumX 4,174 6.692 715 23.793 12,759 23.719 148 1.405
Book
Chapter
Altmetric.com 2,001 5.978 307 1.651 3,259 48.541 191 1.435
PlumX 2,043 5.38 516 13.791 3,714 62.155 104 1.413
Proceedings
Paper
Altmetric.com 7,089 5.784 1,796 1.744 10,832 28.63 486 1.523
PlumX 5,763 4.61 1,785 22.769 28,649 24.647 182 1.434
Review
Altmetric.com 58,628 12.067 17,925 2.831 67,511 68.622 5,631 1.703
PlumX 52,497 9.417 17,799 42.82 94,469 81.303 2,790 1.565

Table 6: Discipline wise distribution of mentions in the two aggregators
Discipline Aggregator #Twitter Avg.
Tweets
#FB Avg. FB
Mentions
#
Mendeley
Avg
Reads
#Blogs Avg Blog
Mentions
MED
Altmetric.com 301,704 10.505 96,605 2.587 361,663 33.583 23,116 1.946
PlumX 266,853 7.748 78,164 49.002 516,696 40.221 9,405 1.527
PHY
Altmetric.com 72,979 3.842 11,623 1.466 93,002 21.201 9,053 1.488
PlumX 53,269 3.292 14,049 30.972 204,802 19.522 1,143 1.85
CHE
Altmetric.com 55,197 3.628 9,020 1.401 72,337 31.303 3,575 1.45
PlumX 45,810 3.081 12,155 22.095 161,466 27.715 934 1.226
ENV
Altmetric.com 40,432 6.476 9,010 1.844 53,018 38.809 4,808 1.719
PlumX 35,354 5.585 10,501 28.799 99,051 37.798 1,476 1.732
AH
Altmetric.com 10,194 5.999 2,816 1.571 12,081 12.248 814 1.478
PlumX 6,963 5.221 1,898 30.347 25,738 11.274 287 1.307
SS
Altmetric.com 114,537 9.84 36,918 1.961 136,109 42.023 12,726 1.84
PlumX 95,173 8.11 28,557 28.906 192,979 49.824 4,988 1.603
INF
Altmetric.com 10,854 6.278 1,658 1.486 20,271 36.987 621 1.588
PlumX 7,423 5.735 3,202 18.685 65,892 28.539 221 1.534
BIO
Altmetric.com 109,393 8.239 27,229 2.056 130,175 38.03 11,260 1.783
PlumX 102,863 6.201 26,304 33.449 181,715 41.593 3,314 1.438
MAR
Altmetric.com 30,368 3.573 4,800 1.503 45,706 31.258 1,662 1.812
PlumX 23,781 3.009 6,854 25.608 136,295 26.78 536 1.278
MAT
Altmetric.com 10,772 6.138 1,227 1.516 15,289 24.91 611 1.624
PlumX 8,433 4.769 2,251 27.961 38,415 19.445 158 1.741
GEO
Altmetric.com 55,972 5.952 10,348 1.884 79,222 29.949 4,713 1.64
PlumX 48,856 4.806 12,651 26.889 143,839 31.889 1,421 1.53
ENG
Altmetric.com 18,616 3.336 2,904 1.476 40,115 33.537 888 1.568
PlumX 13,705 3.044 6,128 25.164 151,743 26.519 405 1.696
MUL
Altmetric.com 56,535 25.09 19,163 3.775 64,478 48.764 9,856 2.886
PlumX 51,136 18.882 26,362 99.871 84,051 60.863 3,634 2.117
AGR
Altmetric.com 29,005 4.707 7,986 1.934 38,359 33.279 2,360 1.427
PlumX 25,774 3.85 7,467 24.109 78,858 31.689 819 1.319
Table 7: Publisher wise summary of values of Altmetric.com and PlumX
Publisher Aggregator #Journals Coverage
%
Twitter Facebook Mendeley Blog
(%) Mean (%) Mean (%) Mean (%) Mean
Springer
Altmetric.com 1,512 44.47 73.5 4.98 16.4 1.66 97.5 26.24 5.1 1.45
PlumX 1,588 93.01 28.7 3.97 10.4 28.98 94.1 24.18 0.7 1.41
Nature
Altmetric.com 125 79.44 86.9 31.83 29.7 4.41 98.6 64.37 18.2 2.98
PlumX 126 97.74 63 23.55 25.2 144.87 95.5 81.84 5.1 2.22
PLoS
Altmetric.com 8 86.88 88 12.28 22.3 2.3 98.6 36.47 10.2 2.1
PlumX 8 98.46 72 8.96 43.1 47 96.4 48.08 3 1.57
Elsevier
Altmetric.com 1,836 43.10 72.3 6.67 16.5 2.01 97.7 39.85 4.9 1.67
PlumX 1,867 94.46 31.3 5.57 12.5 27.07 94.1 40.08 0.9 1.43
IEEE
Altmetric.com 163 24.98 37.7 3.31 5 1.69 96.7 32.02 1.6 1.68
PlumX 167 91.36 3.7 2.34 1 17.62 97.9 24.78 0.2 4.78
Wiley
Altmetric.com 1,317 64.28 79.8 7.10 24.4 1.88 97.8 31.77 6.8 1.62
PlumX 1,322 93.16 49.8 6.64 5 31.11 93.7 36.15 1.9 1.53
Taylor &
Franics
Altmetric.com 1,353 45.83 73.9 6.29 15.8 1.88 96.2 25.22 4.3 1.51
PlumX 1,374 91.42 31.5 5.3 3.2 14.35 92.9 23.88 0.9 1.29
ACM
Altmetric.com 31 54.78 75.8 5.12 19.3 1.25 94.7 23.85 8.7 1.29
PlumX 32 94.52 23 4.35 6.7 14.59 92.2 23.22 0.7 1
IOP
Altmetric.com 69 54.13 79 6.13 13 1.67 97.3 18.03 24 1.63
PlumX 71 90.22 29.1 6.8 8.1 28.69 92.2 19.16 1.1 1.86
Oxford
Univ Press
Altmetric.com 325 68.66 86.4 10.29 21.9 2.03 96.3 33.87 14.1 1.54
PlumX 327 92.17 45 5.73 10.5 23.49 88.7 41.15 1.7 1.38
SAGE
Altmetric.com 660 61.05 81.1 8.81 20.3 2.02 97.2 32.70 8.7 1.81
PlumX 663 94.73 41.2 8.31 3.5 25.91 92.4 36.3 2.3 1.58
Hindawi
Altmetric.com 87 35.21 68.6 3.1 13.3 2.27 98.3 27.22 3.1 1.15
PlumX 97 93.17 26.9 2.76 13.8 20.09 95.7 23.85 0.6 1.19
Cell
Altmetric.com 38 70.01 90.7 22.23 32.5 2.93 96.2 91.59 20.5 2.65
PlumX 38 94.9 64.6 14.84 24.6 54.76 80.1 120.58 4.5 1.54
MDPI
Altmetric.com 55 69.34 74.3 5.45 10.3 2.49 99.3 32.30 3.2 1.44
PlumX 55 97.35 44.1 4.84 22.2 32.9 98 34.51 1.5 1.32

Cambridge
Univ Press
Altmetric.com 305 46.50 75.1 7.01 22.8 1.70 91.4 25.61 8.3 1.55
PlumX 311 84.1 25.8 4.65 7.5 40.68 83 26.71 0.7 1.29
Emerald
Altmetric.com 89 30.49 48.3 3.42 8.1 1.61 97.8 51.13 1.7 1.31
PlumX 91 92.52 15.5 2.94 0.6 1 98.5 58.48 0.4 4.37

FIGURES
Altmetric.com PlumX Overlap
902,990 1,661,477 879,981
Figure 1: Number of Records found in PlumX and Altmetric.com
Figure 2: Coverage Percentages for various platforms in the two aggregators

Figure 3: Mean of differences of mentions (Altmetric.com -- PlumX) for different platforms
(a) Twitter (b) Facebook

(c) Mendeley (d) Blog
Figure 4: Frequency of distribution of differences in mentions (Altmetric.com -- PlumX)
for the four platforms.

A Large-Scale Comparison Of Social Media Coverage And Mentions Captured By The Two Altmetric Aggregators- Altmetric.Com And PlumX

More Related Content

Similar to A Large-Scale Comparison Of Social Media Coverage And Mentions Captured By The Two Altmetric Aggregators- Altmetric.Com And PlumX (20)

More from Dustin Pytko (20)

Recently uploaded (20)

A Large-Scale Comparison Of Social Media Coverage And Mentions Captured By The Two Altmetric Aggregators- Altmetric.Com And PlumX