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The new norm: Computer Science conferences respond to COVID-19.
Mubin, Omar; Alnajjar, Fady; Shamail, Abdullah; Shahid, Suleman; Simoff, Simeon.
  • Mubin O; Western Sydney University, Sydney, Australia.
  • Alnajjar F; College of IT, UAE University, Al Ain, United Arab Emirates.
  • Shamail A; Lahore University of Management Sciences, Lahore, Pakistan.
  • Shahid S; Lahore University of Management Sciences, Lahore, Pakistan.
  • Simoff S; Western Sydney University, Sydney, Australia.
Scientometrics ; 126(2): 1813-1827, 2021.
Article in English | MEDLINE | ID: covidwho-959329
ABSTRACT
The disruption from COVID-19 has been felt deeply across all walks of life. Similarly, academic conferences as one key pillar of dissemination and interaction around research and development have taken a hit. We analyse an interesting focal point as to how conferences in the area of Computer Science have reacted to this disruption with respect to their mode of offering and registration prices, and whether their response is contingent upon specific factors such as where the conference was to be hosted, its ranking, its publisher or its original scheduled date. To achieve this, we collected metadata associated with 170 conferences in the area of Computer Science and as a means of comparison; 25 Psychology conferences. We show that conferences in the area of Computer Science have demonstrated agility and resilience by progressing to an online mode due to COVID-19 (approximately 76% of Computer Science conferences moved to an online mode), many with no changes in their schedule, particularly those in North America and those with a higher ranking. Whilst registration fees have lowered by an average of 42% due to the onset of COVID-19, conferences still have to facilitate attendance on a large scale due to the logistics and costs involved. In conclusion, we discuss the implications of our findings and speculate what they mean for conferences, including those in Computer Science, in the post-COVID-19 world.
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Full text: Available Collection: International databases Database: MEDLINE Topics: Long Covid Language: English Journal: Scientometrics Year: 2021 Document Type: Article Affiliation country: S11192-020-03788-9

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Full text: Available Collection: International databases Database: MEDLINE Topics: Long Covid Language: English Journal: Scientometrics Year: 2021 Document Type: Article Affiliation country: S11192-020-03788-9