SILGDec 13, 2021

Survey of Generative Methods for Social Media Analysis

arXiv:2112.07041v18 citations
Originality Synthesis-oriented
AI Analysis

It fills a void for researchers by offering a broader and more current review than previous surveys, which is incremental in scope.

This survey provides a comprehensive overview of state-of-the-art generative methods for analyzing social media data, addressing gaps in existing literature by including dynamics and networks as key aspects.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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