Inicio  /  Information  /  Vol: 14 Par: 9 (2023)  /  Artículo
ARTÍCULO
TITULO

Social Media Analytics on Russia?Ukraine Cyber War with Natural Language Processing: Perspectives and Challenges

Fahim Sufi    

Resumen

Utilizing social media data is imperative in comprehending critical insights on the Russia?Ukraine cyber conflict due to their unparalleled capacity to provide real-time information dissemination, thereby enabling the timely tracking and analysis of cyber incidents. The vast array of user-generated content on these platforms, ranging from eyewitness accounts to multimedia evidence, serves as invaluable resources for corroborating and contextualizing cyber attacks, facilitating the attribution of malicious actors. Furthermore, social media data afford unique access to public sentiment, the propagation of propaganda, and emerging narratives, offering profound insights into the effectiveness of information operations and shaping counter-messaging strategies. However, there have been hardly any studies reported on the Russia?Ukraine cyber war harnessing social media analytics. This paper presents a comprehensive analysis of the crucial role of social-media-based cyber intelligence in understanding Russia?s cyber threats during the ongoing Russo?Ukrainian conflict. This paper introduces an innovative multidimensional cyber intelligence framework and utilizes Twitter data to generate cyber intelligence reports. By leveraging advanced monitoring tools and NLP algorithms, like language detection, translation, sentiment analysis, term frequency?inverse document frequency (TF-IDF), latent Dirichlet allocation (LDA), Porter stemming, n-grams, and others, this study automatically generated cyber intelligence for Russia and Ukraine. Using 37,386 tweets originating from 30,706 users in 54 languages from 13 October 2022 to 6 April 2023, this paper reported the first detailed multilingual analysis on the Russia?Ukraine cyber crisis in four cyber dimensions (geopolitical and socioeconomic; targeted victim; psychological and societal; and national priority and concerns). It also highlights challenges faced in harnessing reliable social-media-based cyber intelligence.

 Artículos similares

       
 
Andrea Calvagna, Emiliano Tramontana and Gabriella Verga    
Social media networks provide an aggregation of news and content, allowing users to share and discuss topics of greatest interest to them. Users can enrich the news by providing context and opinions that are useful to other users. Understanding topics of... ver más
Revista: Information

 
David Hanny and Bernd Resch    
With the vast amount of social media posts available online, topic modeling and sentiment analysis have become central methods to better understand and analyze online behavior and opinion. However, semantic and sentiment analysis have rarely been combine... ver más
Revista: Information

 
Ana Pérez-Escoda, Andrés Barrios-Rubio, Luis Miguel Pedrero-Esteban and Carolina Ávalos    
Today?s public sphere is increasingly shaped by a dynamic, global, cross-cutting digital landscape, mostly ruled by social media and algorithms. Individuals are the raw material, the product, in this digital scenario, insofar as they generate and create ... ver más
Revista: Information

 
Ivan S. Maksymov and Ganna Pogrebna    
We propose a quantum-mechanical model that represents a human system of beliefs as the quantised energy levels of a physical system. This model represents a novel perspective on opinion dynamics, recreating a broad range of experimental and real-world da... ver más
Revista: Information

 
Retno Kusumaningrum, Selvi Fitria Khoerunnisa, Khadijah Khadijah and Muhammad Syafrudin    
The mangrove ecosystem is crucial for addressing climate change and supporting marine life. To preserve this ecosystem, understanding community awareness is essential. While latent Dirichlet allocation (LDA) is commonly used for this, it has drawbacks su... ver más
Revista: Information