Journal of Computational Social Science
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Incorporating machine learning in dispute resolution and settlement process for financial fraud
Journal of Computational Social Science - Tập 6 - Trang 515-539 - 2023
This paper aims to classify disciplinary hearings into two types (settlement and
contested). The objective is to employ binary machine learning classifier
algorithms to predict the hearing outcomes given a set of features representing
the victims, offenders, and enforcement. Data for this project came from the
Investment Industry Regulatory Industry of Canada’s (IIROC) tribunal hearing.
The data c...
Telegram channels covering Russia’s invasion of Ukraine: a comparative analysis of large multilingual corpora
Journal of Computational Social Science -
Simulating language knowledge across the EU: language regimes, language learning and consequences for linguistic disenfranchisement
Journal of Computational Social Science - - 2022
AbstractThe objective of this paper is to develop an simulation model able to
test different language education orientations and their consequences for the EU
population in terms of linguistic disenfranchisement, that is, the inability of
citizens to understand EU documents and parliamentary discussions should their
native language(s) no longer be official. I will focus on the impact of
linguistic...
Influencing overseas Chinese by tweets: text-images as the key tactic of Chinese propaganda
Journal of Computational Social Science - Tập 3 - Trang 469-486 - 2020
The literature on China’s social media foreign propaganda mostly focuses on
text-format contents in English, which may miss the real target and the tool for
analysis. In this article, we traced 1256 Twitter accounts echoing China
government’s #USAVirus propaganda before and after Twitter removed state-linked
operations on June 12, 2020. The 3567 tweets with #USAVirus we collected, albeit
many writ...
Integrating semantic directions with concept mover’s distance to measure binary concept engagement
Journal of Computational Social Science - Tập 4 - Trang 231-242 - 2020
In an earlier article published in this journal (“Concept Mover’s Distance”,
2019), we proposed a method for measuring concept engagement in texts that uses
word embeddings to find the minimum cost necessary for words in an observed
document to “travel” to words in a “pseudo-document” consisting only of words
denoting a concept of interest. One potential limitation we noted is that,
because words ...
Automation impacts on China’s polarized job market
Journal of Computational Social Science - Tập 5 Số 1 - Trang 517-535 - 2022
School dropout prediction and feature importance exploration in Malawi using household panel data: machine learning approach
Journal of Computational Social Science - Tập 6 - Trang 245-287 - 2022
Designing early warning systems through machine learning (ML) models to identify
students at risk of dropout can improve targeting mechanisms and lead to
efficient social policy interventions in education. School dropout is a
culmination of various factors that drive children to leave school, and timely
policy responses are most needed to address these underlying factors and improve
school retenti...
Flexible imitation suppresses epidemics through better vaccination
Journal of Computational Social Science - Tập 4 - Trang 709-720 - 2021
The decision of whether or not to vaccinate is a complex one. It involves the
contribution both to a social good—herd immunity—and to one’s own well-being. It
is informed by social influence, personal experience, education, and mass media.
In our work, we investigate a situation in which individuals make their choice
based on how social neighbourhood responded to previous epidemics. We do this by
...
Towards misinformation mitigation on social media: novel user activity representation for modeling societal acceptance
Journal of Computational Social Science - - 2024
Intervention-based mitigation methods have become a common way to fight
misinformation on Social Media (SM). However, these methods depend on how
information spreads are modeled in a diffusion model. Unfortunately, there are
no realistic diffusion models or enough diverse datasets to train diffusion
prediction functions. In particular, there is an urgent need for mitigation
methods and labeled dat...
An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms
Journal of Computational Social Science - - Trang 1-17 - 2023
Among text-mining studies, one of the most studied topics is the text
classification task applied in various domains, including medicine, social
media, and academia. As a sub-problem in text classification, sentiment analysis
has been widely investigated to classify often opinion-based textual elements.
Specifically, user reviews and experiential feedback for products or services
have been employe...
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