Media Influence and Public Opinion in the 2023 Israel-Hamas Conflict
Session Number
Project ID: CMPS 18
Advisor(s)
Rohan Leekha, MIT Lincoln Laboratory
Courtland VanDam, MIT Lincoln Laboratory
Discipline
Computer Science
Start Date
17-4-2024 9:20 AM
End Date
17-4-2024 9:35 AM
Abstract
Following the Hamas invasion of Israel on October 7th, 2023, there has been a significant increase in media coverage of the Israel/Hamas conflict. Given the risk of extreme polarization and the inherent unpredictability of the internet, the aim of this research is to perform a detailed examination of how media influences public perception and reaction in the context of a recently intensified conflict. We utilize various Natural Language Processing (NLP) techniques, including topic modeling, sentiment analysis, and bias detection, to analyze news articles surrounding the conflict, as well as user comments on said news articles.
Our analysis reveals a difference in topic, sentiment, and bias of news media following the October 7th invasion of Israel. Results suggest a modest correlation between media content sentiment and public sentiment, particularly with negative emotions, suggesting a deeper psychological engagement with such content. We also find that media with a negative tone garners the most engagement from users, which further supports a potential negativity bias for individuals consuming media. Lastly, we find that media which discusses violent topics, such as terrorism/Hamas activities, evokes significantly more negative user responses as opposed to media discussing more civilized topics, such as foreign policy and protests.
Media Influence and Public Opinion in the 2023 Israel-Hamas Conflict
Following the Hamas invasion of Israel on October 7th, 2023, there has been a significant increase in media coverage of the Israel/Hamas conflict. Given the risk of extreme polarization and the inherent unpredictability of the internet, the aim of this research is to perform a detailed examination of how media influences public perception and reaction in the context of a recently intensified conflict. We utilize various Natural Language Processing (NLP) techniques, including topic modeling, sentiment analysis, and bias detection, to analyze news articles surrounding the conflict, as well as user comments on said news articles.
Our analysis reveals a difference in topic, sentiment, and bias of news media following the October 7th invasion of Israel. Results suggest a modest correlation between media content sentiment and public sentiment, particularly with negative emotions, suggesting a deeper psychological engagement with such content. We also find that media with a negative tone garners the most engagement from users, which further supports a potential negativity bias for individuals consuming media. Lastly, we find that media which discusses violent topics, such as terrorism/Hamas activities, evokes significantly more negative user responses as opposed to media discussing more civilized topics, such as foreign policy and protests.