scholarly journals Multiplex network analysis of the UK over‐the‐counter derivatives market

2019 ◽  
Vol 24 (4) ◽  
pp. 1520-1544
Author(s):  
Marco Bardoscia ◽  
Ginestra Bianconi ◽  
Gerardo Ferrara
Keyword(s):  
Network Analysis ◽  
Over The Counter ◽  
Multiplex Network ◽  
The Uk

scholarly journals Multiplex Network Analysis of the UK OTC Derivatives Market

2018 ◽  
Author(s):  
Marco Bardoscia ◽  
Ginestra Bianconi ◽  
Gerardo Ferrara
Keyword(s):  
Network Analysis ◽  
Otc Derivatives ◽  
Multiplex Network ◽  
The Uk

What Makes a Tweet Fly? Analysis of Twitter Messaging at Four Infection Control Conferences

2017 ◽  
Vol 38 (11) ◽  
pp. 1271-1276 ◽  
Author(s):  
Brett G. Mitchell ◽  
Philip L. Russo ◽  
Jonathan A. Otter ◽  
Martin A. Kiernan ◽  
Landon Aveling
Keyword(s):  
Network Analysis ◽  
Infection Control ◽  
Infection Prevention ◽  
Binary Logistic Regression ◽  
Cross Sectional Study ◽  
Infection Prevention And Control ◽  
Binary Logistic Regression Model ◽  
Cross Sectional ◽  
Activity Networks ◽  
The Uk

OBJECTIVETo examine tweeting activity, networks, and common topics mentioned on Twitter at 4 international infection control and infectious disease conferences.DESIGNA cross-sectional study.METHODSAn independent company was commissioned to undertake a Twitter ‘trawl’ each month between July 1, 2016, and November 31, 2016. The trawl identified any tweets that contained the official hashtags of the conferences for (1) the UK Infection Prevention Society, (2) IDWeek 2016, (3) the Federation of Infectious Society/Hospital Infection Society, and (4) the Australasian College for Infection Prevention and Control. Topics from each tweet were identified, and an examination of the frequency and timing of tweets was performed. A social network analysis was performed to illustrate connections between users. A multivariate binary logistic regression model was developed to explore the predictors of ‘retweets.’RESULTSIn total, 23,718 tweets were identified as using 1 of the 2 hashtags of interest. The results demonstrated that the most tweets were posted during the conferences. Network analysis demonstrated a diversity of twitter networks. A link to a web address was a significant predictor of whether a tweet would be retweeted (odds ratio [OR], 2.0; 95% confidence interval [CI], 1.9–2.1). Other significant factors predicting a retweet included tweeting on topics such as Clostridium difficile (OR, 2.0; 95% CI, 1.7–2.4) and the media (OR, 1.8; 95% CI, 1.6–2.0). Tweets that contained a picture were significantly less likely to be retweeted (OR, 0.06; 95% CI, 0.05–0.08).CONCLUSIONTwitter is a useful tool for information sharing and networking at infection control conferences.Infect Control Hosp Epidemiol 2017;38:1271–1276

Sign in / Sign up

Export Citation Format

Share Document