قاسم كرعاوي

In the fast-growing domain of Information and Telecommunication Technologies (ICT), the emergence and rapid growth of social network platforms have led to the formation of large and dynamic online communities this is thanks to the unprecedented development in the Management of Information and Communication Technology. Understanding the evolution of these communities and their underlying topics is crucial for effective social media marketing, targeted advertising, and online reputation management. In this research, we propose a novel framework for tracking the evolution of social network communities based on influencer of topic. Our approach involves the use of topic modeling techniques, network analysis algorithms, and machine learning methods to identify the main topics and community of influential users and track their evolution over time, in order to predict the temporal emergence of such communities. This prediction will help in identify the influencers and their intentions. We conducted a comprehensive review of the literature on social network analysis, community detection, and topic modeling to develop our theoretical framework. We also explored various data collection, processing, and analysis techniques, including web scraping, natural language processing, and data visualization tools. To eva‎luate the effectiveness of our approach, we applied it to a real-world social network dataset. Our experiments demonstrated the effectiveness of our framework in accurately tracking the evolution of community topics and identifying influential users. Overall, this thesis provides a valuable contribution to Information and Communication Technologies Management (ICT Management) to the field of social network analysis by proposing a new framework for community tracking that can be used for various applications in social media marketing, advertising, and online reputation management. In this research we take a real dataset from tweeter platform for 86 days and take many snapshot windows for studying.

شبكه رسانه هاي اجتماعي , گروه اجتماعي

social media network , social community

Ghasem Karaavi

Dr. Hassan Naderi