Related papers: Beyond the Headlines: Understanding Sentiments and Morals Impacting Female Employment in Spain

Beyond the Headlines: Understanding Sentiments and Morals Impacting Female Employment in Spain

URL: http://arxiv.org/abs/2402.07339v1
Date: Mon, 12 Feb 2024 00:14:04 GMT
Title: Beyond the Headlines: Understanding Sentiments and Morals Impacting Female Employment in Spain
Authors: Oscar Araque, Luca Barbaglia, Francesco Berlingieri, Marco Colagrossi, Sergio Consoli, Lorenzo Gatti, Caterina Mauri, Kyriaki Kalimeri
Abstract summary: After decades of improvements in the employment conditions of females in Spain, this process came to a sudden stop with the Great Spanish Recession of 2008. We analyse a large longitudinal corpus of national and regional news outlets employing advanced Natural Language Processing techniques. We find that females are, in the majority of cases, concerned more than males when there is a deterioration in the overall labour market conditions.
Score: 2.8915939548366776
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Abstract: After decades of improvements in the employment conditions of females in Spain, this process came to a sudden stop with the Great Spanish Recession of 2008. In this contribution, we analyse a large longitudinal corpus of national and regional news outlets employing advanced Natural Language Processing techniques to capture the valence of mentions of gender inequality expressed in the Spanish press. The automatic analysis of the news articles does indeed capture the known hardships faced by females in the Spanish labour market. Our approach can be straightforwardly generalised to other topics of interest. Assessing the sentiment and moral values expressed in the articles, we notice that females are, in the majority of cases, concerned more than males when there is a deterioration in the overall labour market conditions, based on newspaper articles. This behaviour has been present in the entire period of study (2000--2022) and looked particularly pronounced during the economic crisis of 2008 and the recent COVID-19 pandemic. Most of the time, this phenomenon looks to be more pronounced at the regional level, perhaps caused by a significant focus on local labour markets rather than on aggregate statistics or because, in local contexts, females might suffer more from an isolation or discrimination condition. Our findings contribute to a deeper understanding of the gender inequalities in Spain using alternative data, informing policymakers and stakeholders.

Related papers

Beyond Binary Gender: Evaluating Gender-Inclusive Machine Translation with Ambiguous Attitude Words [85.48043537327258]
Existing machine translation gender bias evaluations are primarily focused on male and female genders. This study presents a benchmark AmbGIMT (Gender-Inclusive Machine Translation with Ambiguous attitude words) We propose a novel process to evaluate gender bias based on the Emotional Attitude Score (EAS), which is used to quantify ambiguous attitude words.
arXiv Detail & Related papers (2024-07-23T08:13:51Z)
Thinking beyond Bias: Analyzing Multifaceted Impacts and Implications of AI on Gendered Labour [1.5839621757142595]
This paper emphasizes the need to explore AIs broader impacts on gendered labor. We draw attention to how the AI industry as an integral component of the larger economic structure is transforming the nature of work.
arXiv Detail & Related papers (2024-06-23T20:09:53Z)
Monitoring Gender Gaps via LinkedIn Advertising Estimates: the case study of Italy [3.5493798890908104]
We evaluate the potential of the LinkedIn estimates to monitor the evolution of the gender gaps sustainably. Our findings show that the LinkedIn estimates accurately capture the gender disparities in Italy regarding sociodemographic attributes. At the same time, we assess data biases such as the digitalisation gap, which impacts the representativity of the workforce in an imbalanced manner.
arXiv Detail & Related papers (2023-03-10T11:32:45Z)
"STILL AROUND": Experiences and Survival Strategies of Veteran Women Software Developers [53.5211430148752]
We conducted 14 interviews to examine the experiences of people at the intersection of ageism and sexism. We identified 283 codes, which fell into three main categories: Strategies, Experiences, and Perception. Several strategies we identified, such as (Deliberately) Not Trying to Look Younger, were not previously described in the software engineering literature.
arXiv Detail & Related papers (2023-02-07T19:26:15Z)
Towards Understanding Gender-Seniority Compound Bias in Natural Language Generation [64.65911758042914]
We investigate how seniority impacts the degree of gender bias exhibited in pretrained neural generation models. Our results show that GPT-2 amplifies bias by considering women as junior and men as senior more often than the ground truth in both domains. These results suggest that NLP applications built using GPT-2 may harm women in professional capacities.
arXiv Detail & Related papers (2022-05-19T20:05:02Z)
Gender stereotypes in the mediated personalization of politics: Empirical evidence from a lexical, syntactic and sentiment analysis [2.7071541526963805]
We show that the political personalization in Italy is more detrimental for women than men. Women politicians are covered with a more negative tone than their men counterpart when personal details are reported. The major contribution to the observed gender differences comes from online news rather than print news.
arXiv Detail & Related papers (2022-02-07T11:40:44Z)
Towards Understanding and Mitigating Social Biases in Language Models [107.82654101403264]
Large-scale pretrained language models (LMs) can be potentially dangerous in manifesting undesirable representational biases. We propose steps towards mitigating social biases during text generation. Our empirical results and human evaluation demonstrate effectiveness in mitigating bias while retaining crucial contextual information.
arXiv Detail & Related papers (2021-06-24T17:52:43Z)
Quantifying the efficacy of childcare services on women employment [5.0481365475507225]
Using worldwide panel data and Chinese data at province level, this paper unfolds the quantitative relationship between childcare services and women employment. The attendance rate of childcare services is positively correlated with the relative employment rate of women to men.
arXiv Detail & Related papers (2021-03-25T02:42:05Z)
Gender bias in magazines oriented to men and women: a computational approach [58.720142291102135]
We compare the content of a women-oriented magazine with that of a men-oriented one, both produced by the same editorial group over a decade. With Topic Modelling techniques we identify the main themes discussed in the magazines and quantify how much the presence of these topics differs between magazines over time. Our results show that the frequency of appearance of the topics Family, Business and Women as sex objects, present an initial bias that tends to disappear over time.
arXiv Detail & Related papers (2020-11-24T14:02:49Z)
Young Adult Unemployment Through the Lens of Social Media: Italy as a case study [108.33144653708091]
We employ survey data together with social media data to analyse personality, moral values, but also cultural elements of the young unemployed population in Italy. Our findings show that there are small but significant differences in personality and moral values, with the unemployed males to be less agreeable. Unemployed have a more collectivist point of view, valuing more in-group loyalty, authority, and purity foundations.
arXiv Detail & Related papers (2020-10-09T10:56:04Z)

This list is automatically generated from the titles and abstracts of the papers in this site.