Understanding the Twitter Usage of Humanities and Social Sciences Academic Journals
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Presentation made for 2018 ASIS&T Annual Meeting https://www.asist.org/am18/ http://www.altmetrics.ntuchess.com/
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18
Background
• Social media has become a valuable marketing tool for publishers to
promote research articles
• Twitter is used prominently by both journals and conferences for
sharing research works
• Studies have even shown that journals with Twitter profiles, tend to
have higher academic metrics [1]
• Twitter usage has been studied in the context of researchers [2],
conferences [3,4] and journals from specific disciplines [5-7]](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Understanding the Twitter Usage of Humanities and Social Sciences Academic Journals
- 1. #ASIST 18 Understanding the Twitter Usage of Humanities and Social Sciences Academic Journals Aravind Sesagiri Raamkumar, Mojisola Erdt, Harsha Vijayakumar, Yin-Leng Theng Nanyang Technological University, Singapore Edie Rasmussen University of British Columbia, Canada
- 2. #ASIST 18 Background • Social media has become a valuable marketing tool for publishers to promote research articles • Twitter is used prominently by both journals and conferences for sharing research works • Studies have even shown that journals with Twitter profiles, tend to have higher academic metrics [1] • Twitter usage has been studied in the context of researchers [2], conferences [3,4] and journals from specific disciplines [5-7]
- 3. #ASIST 18 Research Agenda • There has been a distinct lack of studies focusing on the usage of Twitter by journals from a broader outlook i.e., journals from different disciplines • The overall objective of this study is to understand the usage dynamics of Humanities and Social Sciences (HSS) journals in Twitter from a broader perspective • RQ1: What types of actions on Twitter are prevalent among HSS journals? • RQ2: What is the nature of Twitter conversations among the HSS journals? • RQ3: What is the prevalent network structure in Twitter communication graphs of the HSS journals? • RQ4: Which Twitter accounts act as hubs and authorities in the communication graphs of the HSS journals?
- 4. #ASIST 18 Methodology 1. Selection of candidate HSS journals from Arts & Humanities Citation (AHCI) and Social Science Citation Index (SSCI) of Master Journals List (MJL) 2. Manual identification of Twitter profiles for the selected HSS journals 3. Extraction of tweets from Twitter profiles of HSS 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
- 5. #ASIST 18 Data • 408 out of 4,999 HSS journals were found to have Twitter profiles • 321,094 tweets were extracted for these journals • Note: Basic Twitter API allowed extraction of only 3000 tweets per Twitter profile • The percentage of HSS journals with Twitter accounts is quite low • Around 7% to 9% across the two indices Entity AHCI (n) SSCI (n) Journals [A] 1769 3230 Journals with Twitter Accounts [B] 159 (8.99% of A) 249 (7.71% of A) Extracted Tweets [C] 145419 175675
- 6. #ASIST 18 Results – RQ1 Entity AHCI (n) SSCI (n) Retweets (RTs) [E] 32002 (22.01%) 41096 (23.39%) Tweets containing URLs [F] 126172 (86.76% ) 157918 (89.89% ) Tweets containing Links to Articles [G] 7240 (4.98% ) 19370 (11.03%) • Journals from SSCI had the highest number of retweets (23.39%) closely followed by AHCI (22.01%) –> Retweeting is not a very frequent activity • SSCI journals had a higher number of tweets with URLs (89.89%) followed by AHCI (86.76%) –> URL sharing is a frequent activity • The percentage of tweets containing links to research articles is not substantial (less than 15% of total), with SSCI (11.03%) having a better percentage than AHCI (4.98%) –> Research articles URL sharing is infrequent among HSS journals
- 7. #ASIST 18 Results – RQ2 Entity AHCI (n) SSCI (n) Total conversations [A] 103181 121099 Unique journal accounts initiating conversations [B] 152 242 Unique mentions [C] 31040 32819 Conversations where mentions are AHCI journals [D] 13812 (13.39% of A) 70 (0.06% of A) Conversations where mentions are SSCI journals [E] 63 (0.06% of A) 16048 (13.25% of A) Unique AHCI journal mentions [F] 142 (93.42% of B) 18 Unique SSCI journal mentions [G] 18 230 (95.04% of B) Conversations where account and mention are same [H] 13015 (12.61% of A) 14398 (11.89% of A) • HSS journals do not seem to be interacting with other journals in Twitter to any great degree (about 13% of total conversations) • Interactions with journals from other index is even lower(<1%) • Self-mentioning (self-citing) of own Twitter profile in tweets is moderately low (about 12%)
- 8. #ASIST 18 Results – RQ3 (AHCI) Metric AHCI Number of Nodes 4,280 Number of Edges 12,194 Number of Communities 11 • 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
- 9. #ASIST 18 Results – RQ3 (SSCI) Metric AHCI Number of Nodes 4,656 Number of Edges 14,353 Number of Communities 13 • 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
- 10. #ASIST 18 Results – RQ4 (AHCI) Top 20 Nodes with Highest In-degree (AUTHORITIES) Top 20 Nodes with Highest Out-degree (HUBS) Twitter Account Account Type Twitter Account Journal Full Name Nytimes News VQR Virginia Quarterly Review Guardian News AiANews Art In America NewYorker Magazine Missouri_Review Missouri Review Parisreview Journal Wasafiri1 Wasafiri Nypl Library Artforum Artforum International Sharethis Social Bookmarking kenyonreview Kenyon Review LAReviewofBooks Magazine TheHudsonReview Hudson Review Metmuseum Museum ArchRecord Architectural Record Tate Art Gallery NERweb New England Review- Middlebury Series LRB Magazine LonJournal London Journal PoetryFound Magazine BurlingtonMag Burlington Magazine nybooks Magazine AD_books Architectural Design TheAtlantic Magazine nybooks New York Review Of Books ElectricLit Digital Library TheTLS Tls-The Times Literary Supplement MuseumModernArt Museum TheAmScho American Scholar OUPAcademic Publisher JCLJournal Journal Of Commonwealth Literature YouTube Video Sharing Apollo_magazine Apollo-The International Art Magazine gmailcom Email NOReview New Orleans Review PublishersWkly Magazine MassReview Massachusetts Review thelithub Not Active ARTnewsmag Artnews • Magazines (e.g., NewYorker) and News Portals (e.g.,Nytimes) are most frequently referenced as mentions in AHCI Twitter conversations • Libraries (e.g., nypl) and Museums (e.g., metmuseum) are also present as authoritative nodes in AHCI Twitter conversations • Only one journal (Parisreview) was identified as a authoritative node • The top 20 out-degree nodes (hubs) comprise of mostly literature and arts journals
- 11. #ASIST 18 Results – RQ4 (SSCI) • News Portals (e.g., Nytimes) are most frequently referenced as mentions in SSCI Twitter conversations • Magazines (e.g., TheEconomister) and Journals (e.g., TheSocReview) are also present as authoritative nodes in SSCI Twitter conversations • The journals in the top 20 nodes with highest out- degrees (hubs) are spread across different disciplines unlike AHCI • From the JIF quartiles data, it can be ascertained that only three journals (AmJNurs, AmEthno, ASQJournal) are from the first quartile • There are more second quartile (n=7), third quartile (n=6) and fourth quartile (n=4) journals in this list Top 20 Nodes with Highest In-degree (AUTHORITIES) Top 20 Nodes with Highest Out-degree (HUBS) Twitter Account Account Type Twitter Account Corresponding Journal Title Quartile nytimes News InternatlTheory International Theory 3 guardian News AFSJournal Australian Feminist Studies 3 washingtonpost News AmJNurs American Journal Of Nursing 1 TheEconomist Magazine EPSRjournal European Political Science Review 2 TheAtlantic Magazine po_qu Political Quarterly 4 WSJ News EvidencePolicy Evidence & Policy 2 raulpacheco Researcher BulletinAtomic Bulletin Of The Atomic Scientists 4 chronicle News terpolv Terrorism And Political Violence 2 sharethis Social Bookmarking BASeditors Business & Society 2 NPR Media Organization AmEthno American Ethnologist 1 NewYorker Magazine govandopp Government And Opposition 3 HuffingtonPost News ERSjournal Ethnic And Racial Studies 2 TheSocReview Journal psychmag Psychologist 4 SAGEsociology Journal CMPjournal Culture Medicine And Psychiatry 3 timeshighered Magazine LAPerspectives Latin American Perspectives 3 YouTube Video Sharing mgmt_learning Management Learning 2 TIME Magazine hhrjournal Health And Human Rights 3 Slate Magazine Editor_IES Irish Educational Studies 4 wordpressdotcom Content Management socprobsjournal Social Problems 2 ConversationUK News ASQJournal Administrative Science Quarterly 1
- 12. #ASIST 18 Limitations • By considering journals exclusively from MJL, we might be missing some other important journals which are indexed elsewhere • By the end of 2017, Twitter increased the character count in tweets to 280 from the earlier 140 characters • Twitter users can now post more descriptive content and tag more users in their tweets
- 13. #ASIST 18 Concluding Remarks • URL sharing was a major activity performed by HSS journals in tweets • Inter-journal communication seemed to be largely restricted to the journals within the same index • Tweets from public news portals and magazines were highly tweeted or retweeted by HSS journals • Non-academic sources were identified as the authoritative sources in the communication graphs formed with the tweet conversations of the the HSS journals • Findings are to be compared with tweets conversations of SCI journals in future work
- 14. #ASIST 18 Acknowledgements This research was supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Science of Research, Innovation and Enterprise programme (SRIE Award No. NRF2014-NRF-SRIE001-019) Grant Period: Feb 2015 – Mar 2018
- 15. #ASIST 18 Thank you! For any questions, email Aravind at aravind002@ntu.edu.sg
- 16. #ASIST 18 References • [1] Wong, K., Piraquive, J., & Levi, J. R. (2018). Social media presence of otolaryngology journals: The past, present, and future. The Laryngoscope, 128(2), 363–368. https://doi.org/10.1002/lary.26727 • [2] Holmberg, K., & Thelwall, M. (2014). Disciplinary differences in Twitter scholarly communication. Scientometrics, 101(2), 1027– 1042. https://doi.org/10.1007/s11192-014-1229-3 • [3] Lee, M. K., Yoon, H. Y., Smith, M., Park, H. J., & Park, H. W. (2017). Mapping a Twitter scholarly communication network: a case of the association of internet researchers’ conference. Scientometrics, 1–31. https://doi.org/10.1007/s11192-017-2413-z • [4] Parra, D., Trattner, C., Gómez, D., Hurtado, M., Wen, X., & Lin, Y.-R. (2016). Twitter in Academic Events: A Study of Temporal Usage, Communication, Sentimental and Topical Patterns in 16 Computer Science Conferences. Computer Communications, 73, 301–314. https://doi.org/10.1016/j.comcom.2015.07.001 • [5] Cosco, T. D. (2015). Medical journals, impact and social media: an ecological study of the Twittersphere. Canadian Medical Association Journal, 187(18), 1353–1357. https://doi.org/10.1503/cmaj.150976 • [6] Kelly, B. S., Redmond, C. E., Nason, G. J., Healy, G. M., Horgan, N. A., & Heffernan, E. J. (2016). The Use of Twitter by Radiology Journals: An Analysis of Twitter Activity and Impact Factor. Journal of the American College of Radiology, 13(11), 1391–1396. https://doi.org/10.1016/j.jacr.2016.06.041 • [7] Nason, G. J., O’Kelly, F., Kelly, M. E., Phelan, N., Manecksha, R. P., Lawrentschuk, N., & Murphy, D. G. (2015). The emerging use of Twitter by urological journals. BJU International, 115(3), 486–490. https://doi.org/10.1111/bju.12840
- 17. #ASIST 18
Notas del editor
- Point 1: Publishers use social media platforms for letting their audience know about the latest published papers and also to get timely feedback on the publishing process Point 2: Twitter is used more than Facebook, LinkedIn and other social media platforms as it is used by many researchers and academicians Point 3: Journals in the area of otolaryngology, which had Twitter profiles, were found to have higher SCImago Journal & Country Rank (SJR) and H-index Point 4: The usage of Twitter has been studies for different academia related usecases. They are (1) researchers’ usage, (2) usage by conference organizers (e.g., association of internet researchers’ conference and 16 other computer science conferences) and (3) Usage by journals in the areas of medicine, radiology and urology
- Point 1: Prior studies have not focussed on the Twitter usage of journals at a broad level (e.g. hard sciences, soft sciences) Point 2: In this study, we have focussed on Humanities and Social Sciences (HSS) journals. The aim is to do the same with Science Citation Index (SCI) journals and then compare the results Point 2.1: RQ1 looks at the percentage of HSS journals having Twitter accounts and also the percentages of retweets, tweets with URLs, tweets with links to research articles Point 2.2: RQ2 looks at HSS journals’ Twitter conversations statistics in depth. A Twitter conversation is one in which other twitter users are mentioned. Point 2.3: RQ3 tries to identify the type of network formed with the conversational tweets posted by HSS journals. This RQ involves usage of community detection algorithms in SNA Point 2.4: RQ4 makes use of the SNA graphs generated for RQ3 to identify top 20 hubs and authorities in the tweets posted by HSS journals
- The methodology of the study is explained in seven sequential steps Point 1:The Master Journals List (MJL) is a well-known directory of journals. MJL is split into three indices, of which AHCI and SSCI are relevant for this study. We extracted the AHCI and SSCI journal titles from MJL for this study Point 2: In this step, we hired some students to manually identify the Twitter presence of HSS journals Point 3: After identifying the HSS journals with Twitter accounts, the Twitter API was used to extract the tweets posted by these journals Point 4: From the extracted tweets, the tweets containing URLs were identified. Also, from this filtered list, further filtering was done to identity the tweets with URLS of research articles for differentiation purposes Point 5: In this step, the user-mentions data was extracted from the tweets. In the screenshot, the user @mikethelwall is an example of a user-mention. The “OIR journal” twitter account and @mikethelwall together are called as a Twitter conversation. Point 6: After the Twitter conversations data was extracted from the HSS journals tweets, directed graphs were generated using Gephi. The nodes of the graphs were sized based on the degree (sum of in-degree and out-degree) of the node. The ForceAtlas2 community detection algorithm was used to detect the communities in the generated graphs. The communities represent a set of nodes (Twitter accounts) which frequently interact with each other. Point 7: Data generated from the previous steps were analysed for addressing the research questions.
- For better clarity, the HSS journals’ findings are presented with the two HSS indices (AHCI and SSCI) separately. Point 1 and 3: Only a total of 408 (159 AHCI and 249 SSCI) journals were found to have Twitter accounts. This constitutes to 8.99% and 7.71% of AHCI and SSCI journals respectively. These percentages indicate that most HSS journals do not have a major presence in Twitter Point 2: Corresponding more tweets for extracted for SSCI (175, 675 tweets) than AHCI journals (145, 419 tweets)
- Point 1: The retweeting percentage was between 22% and 24% of the total tweets for HSS journals. This is a good indication that journals are trying to post more of their content instead of retweeting others tweets Point 2: Among all the tweets, around 86.8% to 89.9% of tweets contains URLs. This is quite common behavior among Twitter users as information sharing is one of the main purposes of using Twitter Point 3: Although lot of URLs are shared by HSS journals, strangely very few of them were research articles
- To re-iterate again, a Twitter conversation is between one Twitter account (HSS journal in this study’s context) and some other Twitter account which we call as a “mention” in Twitter terminology. For RQ2, we have analysed the Twitter conversations by looking at the type of mentions included in the tweets Point1: Even though many journals are included as mentions in the tweets, HSS journals don’t often involve other HSS journal(s) in Twitter conversations. Both AHCI and SSCI have similar percentage (13%) of tweets where they mention another journal from the same index. Point 2: However, the percentage is very low (0.06%) for conversations with journals from the other HSS index. Point 3: There are certain occasions where a Twitter account would mention itself in a conversation (for example: retweets, replying on top of own tweets). For this case, it was found that around 12% of tweets are self-references
- For addressing RQ3 and RQ4, communication graphs were built using Gephi. The Twitter conversations data was used for building these directed graphs where each source node is a HSS journal and the target node is any Twitter account which has been mentioned in the tweets. For the AHCI graphs, the number of nodes and edges were 4,280 and 12,194 respectively After generating the graph, the nodes were re-sized based on the degree value. A degree value of a node is the sum of both in-degree and out-degree. An in-degree represents an incoming connection while a out-degree represents an outgoing connection. Then, the communities in the graphs were identified by running the ForceAtlas2 algorithm in Gephi. In this AHCI graph, 11 communities were identified (represented with different colors in the screenshot). We went through nodes of each community to identify the parent research area/discipline. After this identification, we added a label beside each community to represent the dominant research area of the nodes in that particular community. Point 1: Since AHCI is about arts and humanities, the communities represented these disciplines with literature and history having bigger communities among others Point 2: The network type for AHCI graph was identified as a “community clusters” network type since there are different communities in this graph with minimal inter-community interactions.
- For the SSCI graphs, the number of nodes and edges were 4,656 and 14,353 respectively In this SSCI graph, 13 communities were identified (represented with different colors in the screenshot). Point 1: Since SSCI comprises of journals about different social science sub-disciplines, the communities represented a broad range of topics. Interestingly, some of the adjacent communities were related to each other (for e.g., politics and international security) Point 2: The network type for SSCI graph was identified as a “community clusters” network type since there are different communities in this graph with minimal inter-community interactions. This is the same as AHCI graph.
- For RQ4, the top 20 hubs and authorities were identified. Hubs are nodes with high in-degrees and authorities are nodes with high out-degrees. In the AHCI graph, the top 20 hubs was almost entirely occupied by non-journal Twitter accounts (with Paris Review journal as the only exception). Magazines and News Portals Twitter accounts were identified as the the top hub types. The presence of museums and libraries was also evident. The top 20 authorities will only comprise of HSS journals because the source node in the graph will always be a HSS journal. The top 20 authorities in AHCI graph were mostly comprises of journals dealing with literature and arts. So, it can be stated these journals of these two research areas, tweet frequently than others
- In the SSCI graph, the top 20 hubs were predominantly occupied by News Portals. Since SSCI journals deal with topics related to current affairs, SSCI journals might find initiating discussions on news articles in Twitter. Magazine related Twitter accounts were also present. Except for Times Higher Education, all the other magazines in this list are for general public reading. Only two journals (The Social Review and SAGE Sociology) were present in the top hubs list. These two journals are often mentioned in tweets so they might be popular in their respective research areas. Unlike AHCI journals, SSCI journals have journal impact factors (JIF) in the journals citation report (JCR), hence we were able to use the JIF quartiles of the journals for comparison purpose. The quartile of the journal is added as the final column in this table for top 20 authorities nodes. SSCI journals’ top 20 authorities were spread across journals from different disciplines with no dominant discipline, corroborating with the 13 equally sized communities in the SSCI communication graph. However, the JIF quartile doesn’t seem to have an impact on the popularity of SSCI journals in Twitter. Only three journals from this list were the first JIF quartile. Most of the SSCI journals in this list were from the second and third quartiles. It can ascertained that these journals are trying to reach as many people as possible to underline their presence outside the research community
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