Sentiment Analysis

Navigating the First Year of the Ukrainian Battlefield: Machine Learning vs. Large Language Models

Abstract:

In an era marked by impressive technological developments, conflicts persist and are rooted in complex historical and socioeconomic dynamics, also manifesting through social media platforms. While the war in Ukraine garnered global attention and prompted humanitarian and strategic responses, more efforts are necessary to understand its dynamics and implications directly by analysing the discourses of Ukrainian people in raising unconventional social media platforms like Telegram and TikTok. Accordingly, this research deploys a Data Science approach for building a set of Machine Learning and Large Language Models for analysing discourses and sentiments of Ukrainian users in the first year of war.

Published In

Volume 23, Issue 2

Testing the Importance of Information Control: How Does Russia React When Pressured in the Information Environment?

Abstract:

Applying big data and sentiment analysis to TASS reporting and 15 years of Russian Foreign Ministry documents, this paper tests the importance Moscow places on information control. By comparing the Russian government’s responses to four categories of foreign policy tools— diplomatic, information, military, and economic (the DIME construct)—this research finds that Russia reacts far more negatively to information tools than to military, diplomatic, or economic tools. 

Published In

Volume 18, Issue 1

Written By

Scott Fisher

Understanding the Trolling Phenomenon: The Automated Detection of Bots and Cyborgs in the Social Media

Abstract:

Social media has become a place for discussion and debate on controversial topics and, thus, provides an opportunity to influence public opinion. This possibility has given rise to a specific  behaviour  known  as  trolling,  which  can  be  found  in  almost  every  discussion  that includes emotionally appealing topics. Trolling is a useful tool for any organisation willing to force a discussion off-track when one has no proper facts to back one’s arguments. Previous research has indicated that social media analytics tools can be utilised for automated detection of trolling. This paper provides tools for detecting message automation utilized in trolling.

Published In

Volume 15, Issue 4

Journal of Information Warfare

The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.

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APT

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The definitive publication for the best and latest research and analysis on information warfare, information operations, and cyber crime. Available in traditional hard copy or online.

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