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Research has been extremely involved in improving in the art criticism area. These improvements are reflected in scientific articles. This article purposed to investigate the 214 articles in art criticism to explore their main characteristics. These articles published in the Web of Science database of the Institute of Scientific Information (ISI) from the period of 1980 till 20 December 2013. Types of articles were article and review which is included in the study. The three top cited (more than 10 times citations) articles in art criticism were published in 1993 and 1999. The 214 articles mean citation rate was 0.87 (SD 2.38) times. Among the various fields, art (58.87%), arts humanities other topics (28.03%), both art and arts humanities other topics (5.14%), both art and education and educational research (2.33%), both art and history (1.40%), art, arts humanities other topics and literature (1.40%), both art and cultural studies (0.93%), both art and philosophy (0.93%), both art and literature (0.46%), and both arts humanities other topics and cultural studies (0.46%) were the most popular fields of research. The results showed that researches were done in the United States had highest citation which was written in English language.
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Out of 20 Universities in Macedonia, only Ss Cyril and Methodius University of Skopje and University St Clement of Bitola are listed in SCImago Institutions Rankings (SIR) for 2013.
Very small number of Macedonian scholarly journals are included in WOS (1), PubMed (1), PubMed Central (1), SCOPUS (5), and Google Scholar metrics (6).
SCOPUS rank and SCOPUS H-index are different for the top 10 authors from Macedonia.
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http://www.rannis.is/bibliometrics/workshop-programme/
Does a Long Reference List Guarantee More Citations? Analysis of Malaysian Hi...Nader Ale Ebrahim
Earlier publications have shown that the number of references as well as the number of received citations are field-dependent. Consequently, a long reference list may lead to more citations. The purpose of this article is to study the concrete relationship between number of references and citation counts. This article tries to find an answer for the concrete case of Malaysian highly cited papers and Malaysian review papers. Malaysian paper is a paper with at least one Malaysian affiliation. A total of 2466 papers consisting of two sets, namely 1966 review papers and 500 highly-cited articles, are studied. The statistical analysis shows that an increase in the number of references leads to a slight increase in the number of citations. Yet, this increase is not statistically significant. Therefore, a researcher should not try to increase the number of received citations by artificially increasing the number of references.
Research has been extremely involved in improving in the art criticism area. These improvements are reflected in scientific articles. This article purposed to investigate the 214 articles in art criticism to explore their main characteristics. These articles published in the Web of Science database of the Institute of Scientific Information (ISI) from the period of 1980 till 20 December 2013. Types of articles were article and review which is included in the study. The three top cited (more than 10 times citations) articles in art criticism were published in 1993 and 1999. The 214 articles mean citation rate was 0.87 (SD 2.38) times. Among the various fields, art (58.87%), arts humanities other topics (28.03%), both art and arts humanities other topics (5.14%), both art and education and educational research (2.33%), both art and history (1.40%), art, arts humanities other topics and literature (1.40%), both art and cultural studies (0.93%), both art and philosophy (0.93%), both art and literature (0.46%), and both arts humanities other topics and cultural studies (0.46%) were the most popular fields of research. The results showed that researches were done in the United States had highest citation which was written in English language.
Scientific Impact of Institutions, Academic Journals and Researchers in the R...Mirko Spiroski
The rank of the Macedonia according the SCImago Journal & Country Rank (SJR) is 99th in the world and 18th in the Eastern Europe.
Out of 20 Universities in Macedonia, only Ss Cyril and Methodius University of Skopje and University St Clement of Bitola are listed in SCImago Institutions Rankings (SIR) for 2013.
Very small number of Macedonian scholarly journals are included in WOS (1), PubMed (1), PubMed Central (1), SCOPUS (5), and Google Scholar metrics (6).
SCOPUS rank and SCOPUS H-index are different for the top 10 authors from Macedonia.
Top twenty Macedonian authors published 72.4% of the total number of abstracts indexed in PubMed.
There is urgent need for organized improvement of the quality of researchers, scholarly journals, and institutions in Macedonia in order to achieve higher international standards.
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Stefanie Haustein, Kim Holmberg, Timothy D. Bowman, Andrew Tsou, Cassidy R. Sugimoto & Vincent Larivière (2014).
Automated arXiv feeds on Twitter: On the role of bots in scholarly communication
Presentation at 19th Nordic Workshop on Bibliometrics and Research Policy, Reykjavik, 25. September 2014
http://www.rannis.is/bibliometrics/workshop-programme/
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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
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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
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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
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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
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References
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Usage, Communication, Sentimental and Topical Patterns in 16 Computer Science Conferences. Computer Communications, 73,
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• [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
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of Twitter by urological journals. BJU International, 115(3), 486–490. https://doi.org/10.1111/bju.12840
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