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AI synopsis
Discussions often include phrases like 'sharing our publication' and mention of the 'brilliant team,' indicating pride and recognition of the work’s importance. The tone conveys enthusiasm and curiosity, with comments highlighting the innovative use of machine learning models to analyze vaccine attitudes, reflecting a strong collective interest and engagement.
Most posts express support or positive acknowledgment towards the publication, reflecting agreement with its aims and findings.
Posts demonstrate high curiosity and enthusiasm, especially with mentions of the innovative methods and publications, indicating strong interest.
Many posts discuss the machine learning techniques, share links, and mention collaborations, showing deep involvement and detailed engagement.
The shared excitement and focus on potential applications suggest these discussions could influence public or academic perceptions about vaccine sentiment analysis.
Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccine_trust with this brilliant team led by Per & @DigitalCoeliac - great learning experience working with this innovative methodology
New JMIR MedInform: Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse https://t.co/LTOr9DW1CC https://t.co/S667zlYKek
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
Open Access UCL Research: Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse https://t.co/cytFG9QDJR
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
This study employs transformer-based machine learning models to analyze and categorize public sentiment towards maternal vaccination on Twitter, processing over 16,000 tweets to identify promotional, discouraging…
This study investigates transformer-based machine learning models to analyze and categorize public vaccine sentiment on Twitter, evaluating over 16,000 tweets into promotional, discouraging, ambiguous, and neutral…
Open Access UCL Research: Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse https://t.co/cytFG9QDJR
https://t.co/x0qPHisTSz ne cherchez pas dans quelle catégorie nous sommes mis, mes amis...
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse https://t.co/5pApYGvmR7
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
RT @dadasara3: Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccin…
Sharing our @jmirpub publication on using #MachineLearning to analyse #vaccine sentiment on #twitter from my time at @vaccine_trust with this brilliant team led by Per & @DigitalCoeliac - great learning experience working with this innovative methodology
#NLP "Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse" https://t.co/24OEu04NMR
RT @jmirpub: New JMIR MedInform: Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Va…
New JMIR MedInform: Categorizing Vaccine Confidence With a Transformer-Based Machine Learning Model: Analysis of Nuances of Vaccine Sentiment in Twitter Discourse https://t.co/LTOr9DW1CC https://t.co/S667zlYKek