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Machine learning framework for country image analysis
In this work, we compare the performance of a machine learning framework based on a support vector machine (SVM) with fastText embeddings, and a Deep...
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Network toxicity analysis: an information-theoretic approach to studying the social dynamics of online toxicity
The rise of social media has corresponded with an increase in the prevalence and severity of online toxicity. While much work has gone into...
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Identifying early help referrals for local authorities with machine learning and bias analysis
Local authorities in England, such as Leicestershire County Council (LCC), provide Early Help services that can be offered at any point in a young...
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Regional contagion in health behaviors: evidence from COVID-19 vaccination modeling in England with social network theorem
Social contagion is a key mechanism that shapes health behaviors, but few studies have applied this approach at the regional level to examine how...
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Intra-family links in the analysis of marital networks
Marriage networks, which represent the matrimonial connections between different families in a given historical and geographical milieu, rarely take...
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Polysemy and the sociolinguistics of policy ideas: resilience, sustainability and wellbeing 2000–2020
In policy studies, there is a concern with understanding how new ideas affect policymaking. Central to this is the issue of how ideas become...
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Telegram channels covering Russia’s invasion of Ukraine: a comparative analysis of large multilingual corpora
Telegram channels are essential in covering Russia’s war in Ukraine. The article compares the war coverage by voenkory, military bloggers in Ukraine...
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Impact of income inequality on health and education in Africa: the long-run role of public spending with short-run dynamics
In this paper, we empirically investigate the long-run impact of income inequality on the pattern of major developmental indicators such as health...
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An empirical study of sentiment analysis utilizing machine learning and deep learning algorithms
Among text-mining studies, one of the most studied topics is the text classification task applied in various domains, including medicine, social...
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The risk co-de model: detecting psychosocial processes of risk perception in natural language through machine learning
This paper presents a classification system (risk Co-De model) based on a theoretical model that combines psychosocial processes of risk perception,...
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Exploring statistical approaches for predicting student dropout in education: a systematic review and meta-analysis
Student dropout is non-attendance from school or college for an extended period for no apparent cause. Tending to this issue necessitates a careful...
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Automated measures of sentiment via transformer- and lexicon-based sentiment analysis (TLSA)
The last decade witnessed the proliferation of automated content analysis in communication research. However, existing computational tools have been...
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A fuzzy set extension of Schelling’s spatial segregation model
This study explores a possible segregation mechanism assuming fuzzy group membership. We construct a fuzzy set extension of Schelling’s spatial...
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Integrating the gender dimension to disclose the degree of businesses’ articulation of innovation
In this contribution, we examine the relationship between the presence of women in companies’ Boards and innovation communication claims: we propose...
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A study of the effect of influential spreaders on the different sectors of Indian market and a few foreign markets: a complex networks perspective
Market competition has a role that is directly or indirectly associated with the influential effects of individual sectors on other sectors of the...
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Predictive insights: leveraging Twitter sentiments and machine learning for environmental, social and governance controversy prediction
This research introduces an innovative approach that utilizes machine learning to forecast Environmental, Social, and Governance (ESG) controversies...
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The variant of efforts avoiding strain: successful correction of a scientific discourse related to COVID-19
This study focuses on how scientifically accurate information is disseminated through social media, and how misinformation can be corrected. We have...
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A high-dimensional approach to measuring online polarization
Polarization, ideological and psychological distancing between groups, can cause dire societal fragmentation. Of chief concern is the role of social...
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Transfer learning for hate speech detection in social media
Today, the internet is an integral part of our daily lives, enabling people to be more connected than ever before. However, this greater connectivity...
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Modeling economic migration on a global scale
We introduce a global-scale migration model centered on neoclassical economic migration theory and leveraging Python and Jupyter as the base modeling...
