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Measuring International Online Human Values with Word Embeddings

Authors:

Virgilio AlmeidaAuthors Info & Claims

ACM Transactions on the Web (TWEB), Volume 16, Issue 2

Article No.: 9, Pages 1 - 38

https://doi.org/10.1145/3501306

Published: 22 December 2021 Publication History

Abstract

As the Internet grows in number of users and in the diversity of services, it becomes more influential on peoples lives. It has the potential of constructing or modifying the opinion, the mental perception, and the values of individuals. What is being created and published online is a reflection of people’s values and beliefs. As a global platform, the Internet is a great source of information for researching the online culture of many different countries. In this work we develop a methodology for measuring data from textual online sources using word embedding models, to create a country-based online human values index that captures cultural traits and values worldwide. Our methodology is applied with a dataset of 1.7 billion tweets, and then we identify their location among 59 countries. We create a list of 22 Online Values Inquiries (OVI), each one capturing different questions from the World Values Survey, related to several values such as religion, science, and abortion. We observe that our methodology is indeed capable of capturing human values online for different counties and different topics. We also show that some online values are highly correlated (up to c = 0.69, p < 0.05) with the corresponding offline values, especially religion-related ones. Our method is generic, and we believe it is useful for social sciences specialists, such as demographers and sociologists, that can use their domain knowledge and expertise to create their own Online Values Inquiries, allowing them to analyze human values in the online environment.

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Measuring International Online Human Values with Word Embeddings

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cover image ACM Transactions on the Web

ACM Transactions on the Web Volume 16, Issue 2

May 2022

148 pages

ISSN:1559-1131

EISSN:1559-114X

DOI:10.1145/3506669

Editor:
Ryen White
Microsoft Research, USA

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Publication History

Published: 22 December 2021

Accepted: 01 November 2021

Revised: 01 October 2021

Received: 01 November 2020

Published in TWEB Volume 16, Issue 2

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Yasuo MMatsushita M(2024)Comparison of Vocabulary Features Among Multiple Data Sources for Constructing a Knowledge Base on Disaster InformationTechnologies and Applications of Artificial Intelligence10.1007/978-981-97-1711-8_10(139-150)Online publication date: 28-Mar-2024
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https://doi.org/10.3156/jsoft.35.2_645
Nevmerzhitsky ABelokonev S(2023)Studying the Political Values in the Digital: The Review of Russian and Foreign CasesRUDN Journal of Public Administration10.22363/2312-8313-2023-10-4-543-55110:4(543-551)Online publication date: 15-Dec-2023
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Ahmed ULin JSrivastava G(2023)Graph Attention Network for Text Classification and Detection of Mental DisorderACM Transactions on the Web10.1145/357240617:3(1-31)Online publication date: 22-May-2023
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