The Language of Influence: Sentiment, Emotion, and Hate Speech in State Sponsored Influence Operations
Authors:
- Ashfaq Ali ShafinASAshfaq Ali Shafin
- Khandaker Mamun AhmedKAKhandaker Mamun Ahmed
Preprint
Abstract
State-sponsored influence operations (SIOs) on social media have become an instrumental tool for manipulating public opinion and spreading unverified information. This study analyzes the sentiment, emotion, and abusive speech in tweets circulated by influence campaigns originating from three distinct countries: China, Iran, and Russia. We examined 1.5 million tweets to uncover patterns in the content of the influence operations using the dataset provided by Twitter. Our findings reveal distinct patterns of sentiment, emotion, and abusive nature in different SIOs. Our experimental result shows that Russian influence operations predominantly employ negative sentiment and toxic language to polarize audiences, Iranian operations balance negative and positive tones to provoke hostility while fostering support, and Chinese campaigns focus on positive messaging to promote favorable narratives.Keywords
All Related Versions
This publication has 19 references indexed in Scilit:
- SoK: False Information, Bots and Malicious Campaigns: Demystifying Elements of Social Media Manipulations2024
- Donetsk don’t tell – ‘hybrid war’ in Ukraine and the limits of social media influence operationsJournal of Information Technology & Politics, 2023
- Exposure to the Russian Internet Research Agency foreign influence campaign on Twitter in the 2016 US election and its relationship to attitudes and voting behaviorNature Communications, 2023
- Amplifying influence through coordinated behaviour in social networksSocial Network Analysis and Mining, 2021
- The responsibility of social media in times of societal and political manipulationEuropean Journal of Operational Research, 2021
- Content-based features predict social media influence operationsScience Advances, 2020
- Spread of Hate Speech in Online Social Media2019
- Disinformation Warfare: Understanding State-Sponsored Trolls on Twitter and Their Influence on the Web2019
- Hate Speech on Twitter: A Pragmatic Approach to Collect Hateful and Offensive Expressions and Perform Hate Speech DetectionIEEE Access, 2018
- Deep Learning for Hate Speech Detection in Tweets2017