Project Overview
Influence is a project that represents a synthesis between the world of marketing and artificial intelligence. The core idea is to analyze user data to generate social media content that matches the interests and preferences of a specific audience.
The platform offers detailed audience analysis regarding public sentiment and popular themes, providing actionable insights for content creators and marketers.
Technical Implementation
The platform is powered by three key machine learning algorithms:
1. Text Mining
Text Mining techniques are used to extract meaningful information from written sources. This allows us to identify the topics preferred by the target audience and detect recurring keywords in social media comments and interactions.
2. Sentiment Analysis
Sentiment Analysis is a Natural Language Processing (NLP) technique that evaluates text to determine whether the expressed opinion is positive, negative, or neutral. This provides immediate feedback on the emotional responses of the audience to different types of content.
3. Social Network Analysis
Social Network Analysis examines the structure and dynamics of social networks to predict how appealing content will be and estimate its viral potential with measurable accuracy.
Project Genesis
I developed this concept after completing a Digital Transformation course in July 2020, offered by the University of Trieste in collaboration with the Friuli Venezia Giulia region. The course focused on user experience and online positioning strategies.
Following this, I participated in the Contamination LAB at the University of Trieste, where I created formal business models and plans for the project, eventually reaching the finals of the competition.
Key Takeaways
This project taught me the importance of bridging different disciplines — combining technical skills in AI and machine learning with practical knowledge of marketing and user behavior. The intersection of these fields creates powerful tools for understanding and engaging audiences.