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Understanding the Twitter Usage of Science Citation Index (SCI) Journals

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Conference paper presented on Nov 5th 2019

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Understanding the Twitter Usage of Science Citation Index (SCI) Journals

  1. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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
  11. 11. RQ3 and RQ4 - Hubs and Authorities
  12. 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. 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. 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. 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. 16. References 1. Mohammadi, E., Thelwall, M., Kwasny, M., Holmes, K.L.: Academic information on Twitter: A user survey. PLoS One. 13, e0197265 (2018). 2. Gardhouse, A.I., Budd, L., Yang, S.Y.C., Wong, C.L.: #GeriMedJC: The Twitter Complement to the Traditional-Format Geriatric Medicine Journal Club. J. Am. Geriatr. Soc. 65, 1347–1351 (2017). 3. Leung, E., Siassakos, D., Khan, K.: Journal Club via social media: authors take note of the impact of #BlueJC. BJOG An Int. J. Obstet. Gynaecol. 122, 1042–1044 (2015). 4. Chan, T.M., Thoma, B., Radecki, R., Topf, J., Woo, H.H., Kao, L.S., Cochran, A., Hiremath, S., Lin, M.: Ten Steps for Setting Up an Online Journal Club. J. Contin. Educ. Health Prof. 35, 148–154 (2015). 5. Wong, K., Piraquive, J., Levi, J.R.: Social media presence of otolaryngology journals: The past, present, and future. Laryngoscope. 128, 363–368 (2018). 6. Zheng, H., Aung, H.H., Erdt, M., Peng, T.-Q., Sesagiri Raamkumar, A., Theng, Y.-L.: Social media presence of scholarly journals. J. Assoc. Inf. Sci. Technol. (2018). 7. Raamkumar, A.S., Erdt, M., Vijayakumar, H., Rasmussen, E., Theng, Y.-L.: Understanding the Twitter usage of humanities and social sciences academic journals. Proc. Assoc. Inf. Sci. Technol. 55, 430–439 (2018). 8. Bastian, M., Heymann, S., Jacomy, M.: Gephi : An Open Source Software for Exploring and Manipulating Networks. In: ICWSM 8. pp. 361–362 (2009). 9. Smith, M.A., Rainie, L., Shneiderman, B., Himelboim, I.: Mapping Twitter Topic Networks: From Polarized Crowds to Community Clusters. (2014). 10. Lee, M.K., Yoon, H.Y., Smith, M., Park, H.J., Park, H.W.: Mapping a Twitter scholarly communication network: a case of the association of internet researchers’ conference. Scientometrics. 1–31 (2017). 11. Thomson Reuters: Journal Citation Reports (JCR), https://jcr.incites.thomsonreuters.com/.
  17. 17. Thank You For any enquiries, please mail me at ephsra@nus.edu.sg

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