Misclassification Bias in Computational Social Science: A Simulation Approach for Assessing the Impact of Classification Errors on Social Indicators Research-Reference-Cited by-同舟云学术

Misclassification Bias in Computational Social Science: A Simulation Approach for Assessing the Impact of Classification Errors on Social Indicators Research

Published:2022 Issue: Volume:10 Page:18886-18898
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Smetanin Sergey¹^ORCID,Komarov Mikhail¹^ORCID

Affiliation:

1. Department of Business Informatics, Graduate School of Business, National Research University Higher School of Economics, Moscow, Russia

Funder

HPC facilities at HSE University [59]

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09706439.pdf?arnumber=9706439

Reference62 articles.

1. Over-Fitting and Model Tuning

2. An Overview of Overfitting and its Solutions

3. A Review on Quantification Learning

4. A data‐driven supply‐side approach for estimating cross‐border Internet purchases within the European Union

5. Proportional Classification Revisited: Automatic Content Analysis of Political Manifestos Using Active Learning

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