Survey of Generative Methods for Social Media Analysis

TL;DR

This survey provides a comprehensive overview of the latest generative methods used in social media analysis, emphasizing dynamics and networks to understand influence, relationships, and social patterns.

Contribution

It offers a broad, updated review of generative techniques in social media analysis, integrating dynamics and networks often overlooked in prior surveys.

Findings

Highlights the importance of dynamics and networks in social media analysis

Identifies gaps and future directions in generative social media research

Provides a panoramic view of state-of-the-art methods

Abstract

This survey draws a broad-stroke, panoramic picture of the State of the Art (SoTA) of the research in generative methods for the analysis of social media data. It fills a void, as the existing survey articles are either much narrower in their scope or are dated. We included two important aspects that currently gain importance in mining and modeling social media: dynamics and networks. Social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, the productivity of teams, etc. Networks, on the other hand, may capture various complex relationships providing additional insight and identifying important patterns that would otherwise go unnoticed.