Women and news: A long and winding road

By K. Ross, C. Carter. 2011

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In Social Sciences & Humanities

Citations in the corpus

Exposing and Correcting the Gender Bias in Image Captioning Datasets and Models (2019, background): “Popular resources like Wikipedia [Wagner et al., 2015], news articles [Ross and Carter, 2011], Twitter [Barbieri and Camacho-Collados, 2018] possess gender bias in one or the other form.”
Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016, background): “While gender bias of any kind is concerning, stereotypes are often easier to study due to their consistent nature.”
Men Also Like Shopping: Reducing Gender Bias Amplification using Corpus-level Constraints (2017, background): “, 2017), online news (Ross and Carter, 2011), web search (Kay et al.”
Gender Bias in Coreference Resolution: Evaluation and Debiasing Methods (2018, background): “, 2017), online news (Ross and Carter, 2011), web search (Kay et al.”
Gender Bias in Contextualized Word Embeddings (2019, background): “Gender bias has been shown to affect several realworld applications relying on automatic language analysis, including online news (Ross and Carter, 2011), advertisements (Sweeney, 2013), abusive language detection (Park et al.”
Women through the glass ceiling: gender asymmetries in Wikipedia (2016, background): “Analysis of longitudinal data from the Global Media Monitoring Project (GMMP) spanning over 15 years indicates that the role of women as producers and subjects of news has seen a steady improvement, but the relative visibility of women compared to men has been stuck at 1:3 [27].”
Balanced Datasets Are Not Enough: Estimating and Mitigating Gender Bias in Deep Image Representations (2018, background): “Concerns have been raised for applications such as recommender systems [35], credit score prediction [9], online news [24], and others [11] and in response various approaches have been proposed to mitigate bias [1, 10].”
Mitigating Gender Bias in Captioning Systems (2020, background): “It has been reported that many popular language data resources contain gender bias [31, 36, 40, 41].”
Measuring Gender Bias in News Images (2015, background): “Traditionally, both text and image analysis have been performed by hand [3, 14, 18], but in recent times the detection of gender bias in text has been automated [1, 6], making it possible to analyse hundreds of thousands of news articles, from hundreds of different news outlets, over a period of mon”
Adversarial Removal of Gender from Deep Image Representations (2018, unknown): “Concerns have been raised for applications such as recommender systems [25], credit score prediction [12], online news [20], and many others [15] and in response various approaches have been proposed to mitigate bias [1, 13].”