Interdisciplinary Approach to Identify and Characterize COVID-19 Misinformation on Twitter: Mixed Methods Study.

ABSTRACT:

Background

Studying COVID-19 misinformation on Twitter presents methodological challenges. A computational approach can analyze large data sets, but it is limited when interpreting context. A qualitative approach allows for a deeper analysis of content, but it is labor-intensive and feasible only for smaller data sets.

Objective

We aimed to identify and characterize tweets containing COVID-19 misinformation.

Methods

Tweets geolocated to the Philippines (January 1 to March 21, 2020) containing the words coronavirus, covid, and ncov were mined using the GetOldTweets3 Python library. This primary corpus (N=12,631) was subjected to biterm topic modeling. Key informant interviews were conducted to elicit examples of COVID-19 misinformation and determine keywords. Using NVi

SUBMITTER: Isip Tan IT 

PROVIDER: S-EPMC10337476 | biostudies-literature | 2023 Jun

REPOSITORIES: biostudies-literature