Redirigiendo al acceso original de articulo en 20 segundos...
Inicio  /  Information  /  Vol: 14 Par: 11 (2023)  /  Artículo
ARTÍCULO
TITULO

Polarizing Topics on Twitter in the 2022 United States Elections

Josip Katalinic    
Ivan Dunder and Sanja Seljan    

Resumen

Politically polarizing issues are a growing concern around the world, creating divisions along ideological lines, which was also confirmed during the 2022 United States midterm elections. The purpose of this study was to explore the relationship between the results of the 2022 U.S. midterm elections and the topics that were covered during the campaign. A dataset consisting of 52,688 tweets in total was created by collecting tweets of senators, representatives and governors who participated in the elections one month before the start of the elections. Using unsupervised machine learning, topic modeling is built on the collected data and visualized to represent topics. Furthermore, supervised machine learning is used to classify tweets to the corresponding political party, whereas sentiment analysis is carried out in order to detect polarity and subjectivity. Tweets from participating politicians, U.S. states and involved parties were found to correlate with polarizing topics. This study hereby explored the relationship between the topics that were creating a divide between Democrats and Republicans during their campaign and the 2022 U.S. midterm election outcomes. This research found that polarizing topics permeated the Twitter (today known as X) campaign, and that all elections were classified as highly subjective. In the Senate and House elections, this classification analysis showed significant misclassification rates of 21.37% and 24.15%, respectively, indicating that Republican tweets often aligned with traditional Democratic narratives.

 Artículos similares

       
 
Lamia Bendebane, Zakaria Laboudi, Asma Saighi, Hassan Al-Tarawneh, Adel Ouannas and Giuseppe Grassi    
Social media occupies an important place in people?s daily lives where users share various contents and topics such as thoughts, experiences, events and feelings. The massive use of social media has led to the generation of huge volumes of data. These da... ver más
Revista: Algorithms

 
Nirmalya Thakur, Yuvraj Nihal Duggal and Zihui Liu    
In the last decade and a half, the world has experienced outbreaks of a range of viruses such as COVID-19, H1N1, flu, Ebola, Zika virus, Middle East Respiratory Syndrome (MERS), measles, and West Nile virus, just to name a few. During these virus outbrea... ver más
Revista: Computers

 
Aditya Singhal and Vijay Mago    
The use of Twitter by healthcare organizations is an effective means of disseminating medical information to the public. However, the content of tweets can be influenced by various factors, such as health emergencies and medical breakthroughs. In this st... ver más
Revista: Informatics

 
Yaseen Khan, Surendra Thakur, Obiseye Obiyemi and Emmanuel Adetiba    
Bots (social robots) are computer programs that replicate human behavior in online social networks. They are either fully automated or semi-automated, and their use makes online activism vulnerable to manipulation. This study examines the existence of so... ver más
Revista: Informatics

 
Julio Jerison E. Macrohon, Charlyn Nayve Villavicencio, X. Alphonse Inbaraj and Jyh-Horng Jeng    
With the increasing popularity of Twitter as both a social media platform and a data source for companies, decision makers, advertisers, and even researchers alike, data have been so massive that manual labeling is no longer feasible. This research uses ... ver más
Revista: Information