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Understanding the Twitter Usage of Science Citation Index (SCI) Journals
1. Understanding the Twitter
Usage of Science Citation
Index (SCI) Journals
Aravind Sesagiri Raamkumar, Mojisola Erdt, Harsha
Vijayakumar, Aarthy Nagarajan, and Yin-Leng Theng
ICADL 2019
Nov 5th, 2019
2. Background
• Twitter is used by researchers, conferences, scientific bodies,
journals
• Academic journals use Twitter to enable discussions about
research papers, research topics and engage with public
• Journals with social media accounts (e.g., Twitter) have been
found to have higher research metrics
• Twitter usage seems to vary based on the discipline
• 28% for medical journals
• 28% for radiology journals
• 25% for urological journal
• 50% of plastic surgery journals
• 14% of dermatology journals
3. Background
• Our previous study focused on the Twitter usage of HSS
Journals (AHCI and SSCI)
• HSS Journals Presence in Twitter
• Twitter Conversation Statistics
• Network Structure
• Top Hubs and Authorities
• This paper focuses on similar research objectives with SCI
journals Twitter activity and also provides the comparison
with HSS journals
4. Research Objectives
RQ1: Does the communication between journals in
Twitter conversations of SCI journals differ from HSS
(AHCI & SSCI) journals?
RQ2: Which network structure best represents the SCI
journals Twitter communication graph?
RQ3: What type of Twitter accounts are top
authorities in the communication graph of SCI
journals?
RQ4: What disciplines do the top SCI journals in the
communication graph represent and does their
Twitter popularity reflect their ranking in the Journal
Citation Report (JCR)?
Source: Neo4J
5. Methodology
1. Selection of candidate SCI journals from Science Citation Index Extended (SCIE) of
Master Journals List (MJL)
2. Manual identification of Twitter profiles for the selected SCI journals
3. Extraction of tweets from Twitter profiles of SCI journals
4. Identification of tweets which contain URL(s)
5. Extraction of user-mentions data from tweets
6. Building communication graphs using Gephi with user-mentions data
7. Analysis of tweets and communications graphs
6. Data
• 857 out of 8,827 SCI journals were found to have Twitter
profiles
• 953,253 tweets were extracted for these journals
• The percentage of SCI journals with Twitter accounts is
slightly better than HSS journals
Entity SCI (n) AHCI (n) SSCI (n)
Journals [A] 8827 1769 3230
Journals with Twitter
Accounts [B]
857 (9.71% of A) 159 (8.99% of A) 249 (7.71% of A)
Extracted Tweets [C] 953253 145419 175675
Retweets (RTs) 190510 (19.99% of C) 32002 (22.01% of C) 41096 (23.39% of C)
Tweets containing URLs 860474 (90.27% of C) 126172 (86.76% of C) 157918 (89.89% of C)
7. RQ1 – Twitter Conversation Statistics
Entity n
Conversations [A] 509,062
Unique journal accounts [B] 768
Unique user-mentions [C] 88,021
Conversations where user-mentions are SCI journals 92,421 (18.16% of A)
Conversations where user-mentions are AHCI journals 88
Conversations where user-mentions are SSCI journals 592
• The number of conversations in SCI journals was high
(n=509,062) – almost five times more than HSS journals
• SCI journals had the highest percentage of conversations
at an intra-index level (18.16%) as against HSS
journals(13.39% for AHCI, 13.25% for SSCI)
8. RQ2 – Twitter Communication Graph
• SCI graph is represented by communities mainly representing
Chemistry, Bioscience, Ecology and Surgery
• SCI graph can be classified as a Tight Crowd graph with the
central presence of Nature journals across many communities
9. RQ2 – Comparison with HSS Journals (AHCI)
• AHCI graph is represented by multiple communities including
Philosophy, History, Arts, Architecture, Film and Literature
• AHCI graph can be classified as a Community Clusters graph since
there are multiple communities with minimal interspersed nodes
10. RQ2 – Comparison with HSS Journals (SSCI)
• SSCI graph is represented by more number of communities including
Law, Anthropology, Women Studies, Politics and International
Security to name a few
• Similar to AHCI, SSCI graph can be classified as a Community Clusters
graph
12. RQ3 – Top Authorities in SCI Graph
Twitter Handle Account Name Account Type
In
Degree
NatureNews Nature News & Comment News 209
guardian The Guardian News 172
sciencemagazine Science Magazine Journal 165
nytimes The New York Times News 159
sciam Scientific American Magazine 157
WHO World Health Organization Specialized Agency 142
newscientist New Scientist Magazine 130
nature Nature Journal 127
altmetric Altmetric Scientific Organization 123
NIH NIH Government Agency 122
YouTube YouTube Video Sharing 114
wellcometrust Wellcome Trust Scientific Organization 112
MayoClinic Mayo Clinic Scientific Organization 109
NEJM NEJM Journal 104
physorg_com Phys.org News 102
UniofOxford Oxford University Scientific Organization 102
guardianscience Guardian Science News 102
royalsociety The Royal Society Scientific Organization 101
CDCgov CDC Government Agency 100
TheLancet The Lancet Journal 96
• News Portals (n=5)
and Scientific
Organizations (n=5)
are most frequently
referenced
• Four journals were
identified as
authoritative nodes
• Agencies (WHO, NIH &
CDC) were also found
as a popular authority
type (n=3)
• Very marginal
presence of Magazines
(n=2)
13. RQ4 – Top Hubs in SCI Graph
Twitter Handle Journal Name
Out
Degree
JIF
Quartile
BiolJLinnSoc Biological Journal of the Linnean Society 835 3
BMCMedicine BMC Medicine 769 1
ChemMater Chemistry of Materials 731 1
acsnano ACS Nano 716 1
BiochemJ Biochemical Journal 714 2
clin_sci Clinical Science 682 1
ChemCatChem Chemcatchem 661 1
PLOSPathogens PLOS Pathogens 642 1
NatureChemistry Nature Chemistry 636 1
FunEcology Functional Ecology 626 1
PLOSMedicine PLOS Medicine 605 1
NaturePlants Nature Plants 603 4
JExpMed Journal of Experimental Medicine 576 1
eLife eLife 574 1
ASIHCopeia Copeia 543 2
NatureGenet Nature Genetics 526 1
GenomeBiology Genome Biology 510 1
BiosciReports Bioscience Reports 506 3
cenmag Chemical & Engineering News 485 4
TheLancetInfDis Lancet Infectious Diseases 485 1
• Journals from the disciplines of
medicine (n=3), biology (n=4) and
chemistry (n=4) were prominent
• 14 journals for 1st JIF quartile were
found in this list
• Nature Publishing Group (NPG),
American Chemical Society (ACS) and
Portland Press were the most
popular publishers with three
journals each
• Five fully Open Access (OA) journals
in this list, whereas the other journals
follow the hybrid publishing model
14. Conclusions
• SCI journals were found to have a marginally better presence
than HSS journals on Twitter
• Conversation statistics revealed certain differences between
the journals from SCI and HSS
• The network structure of SCI communication graph (“tight
crowd”) was different from HSS journals (“community
cluster”)
• News portals, scientific organizations, journals, government
agencies and magazines were found to be top authorities in
SCI journal tweets
• Top hubs in Twitter were also top journals in the citation
network (represented by JCR rankings)
15. Directions for Future Research
• Validate the findings with recently posted “longer” tweets
(280 characters vs 140 characters)
• Include journals from other indices for future studies
• Build multi-dimensional graphs by considering mentions of
policies and clinical trials in Twitter conversations
16. References
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