International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 11 Issue: 04 | Apr 2024
p-ISSN: 2395-0072
www.irjet.net
Social Network Analysis for Understanding Online Information Diffusion Patterns Antara Dessai1, Prof. Siddhi Naik2 1Student, Department of Information Technology and Engineering, Goa College of Engineering, Farmagudi, Goa,
India
2Assistant Professor, Department of Information Technology and Engineering, Goa College of Engineering,
Farmagudi, Goa, India ---------------------------------------------------------------------***--------------------------------------------------------------------unveils the role of key influencers, mapping out the Abstract - Social Network Analysis (SNA) with a focus on
network elements that drive the diffusion process. Moreover, the exploration of network properties, such as density, centrality, and clustering, adds depth to the understanding of how information spreads. An illustration of Social Network is depicted in Figure 1.
unraveling the intricate patterns of online information diffusion. This study focuses on Social Network Analysis (SNA) techniques to gain insights into how information propagates through social network by means of data analysis of information shared on network by Visualizing the graph, measuring Degree Centrality, Betweenness Centrality, Closeness Centrality, Clustering Effects, Bridges, Assortativity, Network Communities and Plot Word Cloud, Bar Chart Representation for Sentiment Analysis. The study employs a multidisciplinary approach, combining elements data science, and social network to provide a comprehensive understanding of online information diffusion. Utilizing real-world datasets from prominent social media platforms, we analyze the interactions, connections, and behavioral patterns of users involved in the dissemination process.
Key Words:Social Network Analysis,Influence Maximization, Sentiment Analysis
1.INTRODUCTION Fig -1: Social Network
Social Network Analysis (SNA) is a powerful method used to study the relationships and interactions among individuals, groups, or organizations within a social system. It provides a valuable framework for understanding the structure, dynamics, and patterns of social networks.
By adopting an SNA perspective, It can offer valuable insights into the interplay between social connections and the dynamics of information diffusion in the digital landscape. This holistic understanding has far-reaching implications for academics, policymakers, and businesses, providing actionable knowledge for optimizing communication strategies, enhancing online engagement, and fostering informed decision-making in an increasingly interconnected world.
Social Network Analysis stands as a pivotal tool in unraveling the intricate dynamics of online information diffusion patterns, providing a nuanced lens through which researchers can comprehend the complexities inherent in the digital dissemination of information. In the realm of project reports, a comprehensive overview of SNA's application in understanding online information diffusion is imperative for unlocking key insights.
2. Related works While existing literature surveys predominantly focus on state-of-the-art methodologies within specific perspectives, our survey uniquely addresses the gap in social network analysis by incorporating privacy preservation. To the best of our knowledge, this marks the inaugural attempt to provide foundational insights into social network analysis issues, serving as an essential resource for emerging researchers in this field. Notably, our survey differs from previous ones in various aspects. For instance, Reference [10] primarily delves into information diffusion associated with community
SNA delves into the intricate web of relationships within social networks, enabling the identification of influential nodes and pathways that govern the flow of information. This analytical approach facilitates a granular examination of the factors influencing the speed, reach, and impact of information dissemination, shedding light on the underlying structures that shape online communication. Through the analysis of connections between nodes, SNA
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