Discourse Analysis of Covid-19 in Persian Twitter Social Networks Using Graph Mining and Natural Language Processing

by   Omid Shokrollahi, et al.

One of the new scientific ways of understanding discourse dynamics is analyzing the public data of social networks. This research's aim is Post-structuralist Discourse Analysis (PDA) of Covid-19 phenomenon (inspired by Laclau and Mouffe's Discourse Theory) by using Intelligent Data Mining for Persian Society. The examined big data is five million tweets from 160,000 users of the Persian Twitter network to compare two discourses. Besides analyzing the tweet texts individually, a social network graph database has been created based on retweets relationships. We use the VoteRank algorithm to introduce and rank people whose posts become word of mouth, provided that the total information spreading scope is maximized over the network. These users are also clustered according to their word usage pattern (the Gaussian Mixture Model is used). The constructed discourse of influential spreaders is compared to the most active users. This analysis is done based on Covid-related posts over eight episodes. Also, by relying on the statistical content analysis and polarity of tweet words, discourse analysis is done for the whole mentioned subpopulations, especially for the top individuals. The most important result of this research is that the Twitter subjects' discourse construction is government-based rather than community-based. The analyzed Iranian society does not consider itself responsible for the Covid-19 wicked problem, does not believe in participation, and expects the government to solve all problems. The most active and most influential users' similarity is that political, national, and critical discourse construction is the predominant one. In addition to the advantages of its research methodology, it is necessary to pay attention to the study's limitations. Suggestion for future encounters of Iranian society with similar crises is given.


page 1

page 2

page 3

page 4


A comparative study of Bot Detection techniques methods with an application related to Covid-19 discourse on Twitter

Bot Detection is an essential asset in a period where Online Social Netw...

The Drift of #MyBodyMyChoice Discourse on Twitter

#MyBodyMyChoice is a well-known hashtag originally created to advocate f...

Large-scale, Language-agnostic Discourse Classification of Tweets During COVID-19

Quantifying the characteristics of public attention is an essential prer...

Automated clustering of COVID-19 anti-vaccine discourse on Twitter

Attitudes about vaccination have become more polarized; it is common to ...

Identification of Twitter Bots based on an Explainable ML Framework: the US 2020 Elections Case Study

Twitter is one of the most popular social networks attracting millions o...

Identifying the Adoption or Rejection of Misinformation Targeting COVID-19 Vaccines in Twitter Discourse

Although billions of COVID-19 vaccines have been administered, too many ...

Please sign up or login with your details

Forgot password? Click here to reset