Research on the Driving Force of Civil Legal Aid Willingness Under the Discrimination of Big Data–Based on the Analysis of Economic Case Texts

DOI

10.2991/978-94-6463-030-5_125How to use a DOI?

Keywords

Big Data Discrimination; Willingness Economy Of Civil Legal Aid; Network Case; Text Analysis

Abstract

Individuals are subject to three types of big data discrimination: biased selection, false association, and malicious recommendation, and victims should be relieved through civil legal aid. This paper analyzes the text of network cases and constructs a regression model, and finds that there are two types of attitude words in the case text, explicit and implicit, which reflect the true attitude of the willingness to seek civil legal aid and have a significant impact. Through the texts of existing network cases, it has a good inspiration for the construction of a legal aid relief system for China’s big data discrimination cases.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xiu Ye
AU  - Huihui Dong
AU  - Pengxiang Jiang
AU  - Yanling Li
PY  - 2022
DA  - 2022/12/20
TI  - Research on the Driving Force of Civil Legal Aid Willingness Under the Discrimination of Big Data–Based on the Analysis of Economic Case Texts
BT  - Proceedings of the 2022 International Conference on Bigdata Blockchain and Economy Management (ICBBEM 2022)
PB  - Atlantis Press
SP  - 1261
EP  - 1269
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-030-5_125
DO  - 10.2991/978-94-6463-030-5_125
ID  - Ye2022
ER  -