What Twitter Can Tell Us about #IDWeek2020

Richard J. Medford; Sameh N. Saleh

doi:10.1093/ofid/ofaa621

What Twitter Can Tell Us about #IDWeek2020

Richard J. Medford, Sameh N. Saleh

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

We used topic modeling, subjectivity analysis, and social graph theory to analyze 11 944 tweets relating to IDWeek 2020. Twitter is a rich medium that can successfully disseminate knowledge and allow users to engage in social networks during a medical conference, despite a virtual format.

Original language	English (US)
Article number	ofaa621
Journal	Open Forum Infectious Diseases
Volume	8
Issue number	5
DOIs	https://doi.org/10.1093/ofid/ofaa621
State	Published - May 1 2021

Keywords

IDWeek 2020
Twitter
machine learning
natural language processing
social media
social network analysis
topic modeling

ASJC Scopus subject areas

Oncology
Clinical Neurology

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10.1093/ofid/ofaa621

Cite this

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title = "What Twitter Can Tell Us about #IDWeek2020",

abstract = "We used topic modeling, subjectivity analysis, and social graph theory to analyze 11 944 tweets relating to IDWeek 2020. Twitter is a rich medium that can successfully disseminate knowledge and allow users to engage in social networks during a medical conference, despite a virtual format.",

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note = "Publisher Copyright: {\textcopyright} 2020 The Author(s) 2020. Published by Oxford University Press on behalf of Infectious Diseases Society of America.",

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What Twitter Can Tell Us about #IDWeek2020

Abstract

Keywords

ASJC Scopus subject areas

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