JSAI2022

Presentation information

General Session

General Session » GS-2 Machine learning

[3E3-GS-2] Machine learning: market analysis

Thu. Jun 16, 2022 1:30 PM - 3:10 PM Room E (Room E)

座長:伊集院 幸輝(北陸先端科学技術大学院大学)[現地]

2:30 PM - 2:50 PM

[3E3-GS-2-04] On the number of samples needed for estimating opinions in social networks

Masato Shinoda1, 〇Yuko Sakurai2, Satoshi Oyama3 (1. Nara Women's University, 2. AIST, Kyushu University, 3. Hokkaido University)

Keywords:Opinion Estimation, Social Networks, PAC Learning

We use the PAC learning framework to evaluate the number of samples needed to estimate the overall proportion of opinions propagated in a social network. While existing studies have only considered binary opinions, this study uses the graph dimension and Natarajan dimension, which are generalizations of the VC dimension, to give upper and lower bounds on the number of samples when multiple values are considered.

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