Curtailing fake news creation and dissemination in Nigeria: Twitter social network and sentiment analysis approaches

Abstract

Influencers create and facilitate dissemination of information in a network and can shape the attitudes and beliefs of members of a social network. Identifying the influencers and their relations, as well as the sentiment of tweets being disseminated in the network on some selected keywords can help curtail fake news creation and dissemination in the network. This study uses a sequential mixed-methods design with a quantitative method followed by qualitative methods. The quantitative data were collected using Mozdeh big data analysis software. Mozdeh software was used to collect tweets through Twitter’s Streaming application programming interface to build a corpus of tweets, collected from 1 January 2016 to 30 June 2021. The study found two major actors/influencers involved in the creation and dissemination of fake news on the tweeter social network studied. The study further found overall Av. Pos. − Av. Neg. was −0.9935. Data collected were on some specific trending keywords on a particular region in Nigeria. Identifying and monitoring the tweets of influencers in a network can aid in debunking fake news immediately after dissemination and discourage the use of offensive words in tweets. The results revealed major influencers responsible for creating and disseminating fake news on some trending issues in Nigeria.