The goal of this project is to understand the interactions around the #EXPO2020 on Twitter. I can extract from this analysis the prominent influencers, narratives around the topic selected, the volume of mentions, country, and language predominant in the discussion, among others.
The data was collected directly from Twitter API. Next, I preprocessed the tweets (raw data) to a usable format for the library Networkx in Python. Then, I computed the modularity and the degree of the nodes.
I represent the social network graph around the mentions in the left chart. I could extract main influencers, clusters, interactions behavior and understand how the diffusion of the information is carried out on Twitter.
In the chart below, I show the evolution of the mentions of #EXPO2020 during the analysis period. Note the spike on December 8th and the seasonality of the mentions every day.
Skills: API, Graph Theory, Python, Networkx, Pandas, D3.js.
Total Tweets analyzed are 15,118.
The hour of the query is 12/09/2021, 11:08:10.
The tweets were made from 11/30/2021 18:28:35 to 12/09/2021 11:04:13.