Thematische Bibliographien / Text-based biases

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Auswahl der wissenschaftlichen Literatur zum Thema „Text-based biases“

Autor: Grafiati

Veröffentlicht am 7. Juni 2025

Zuletzt aktualisiert am 2. August 2025

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Zeitschriftenartikel zum Thema "Text-based biases"

Jethro, Jake C. Sampang, Albert R. Dela Rosa John, R. Pecson Ryan, G. Reyes Jeniel, R. Marticio Benjun, and Q. Quinto Ronald. "Challenges in Identifying Text-Based Biases in Ethnicity and Inclusivity in Learning Materials: Insights from Teacher Module-Writers." Social Science and Human Research Bulletin 02, no. 03 (2025): 64–68. https://doi.org/10.5281/zenodo.15031457.

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Abstract Purpose: Learning materials are tools to promote inclusivity and cultural awareness. The present study examines the challenges public school teacher module-writers encountered in identifying text-based biases in the textbooks and other learning materials they used, focusing on biases in ethnicity and inclusivity. Patients and methods: The study employs the descriptive survey design of quantitative research, wherein the needed data are gathered through a questionnaire to thirty (30) public school teachers who are module-writers and are purposively selected. The data collected are analy

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Souza Filho, Breno Augusto Bormann de, Érika Fernandes Tritany, and Cláudio José Struchiner. "VIÉS DE TEMPO, PESSOA E LUGAR: Ampliando o olhar através da Teoria dos Pressupostos da Qualidade Científica." Psicologia e Saúde em Debate 10, no. 1 (2024): 899–907. http://dx.doi.org/10.22289/2446-922x.v10n1a54.

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The literature presents several classifications for methodological biases, however little is discussed about the possible biases related to the theoretical foundation adopted in the research. Based on the Theory of Assumptions of Scientific Quality, we present reflections and conceptual expansions related to theoretical-methodological biases in research. A critical-reflective text supported by a narrative review, whose material collection process was carried out in a non-systematic way, chosen exclusively and based on the line of argument and reflection that the authors intend to submit to app

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Jaiswal, Siddharth. "Uncovering Gender Biases in Human-AI Platforms." Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society 7, no. 2 (2025): 21–22. https://doi.org/10.1609/aies.v7i2.31898.

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As part of my PhD studies, I am focusing on the broad problem of gender related biases in Human-AI systems, making a three-fold contribution to every part of the Responsible AI pipeline-- (i) Adversarial Audits in different human-AI platforms to identify biases against binary & non-binary gender groups, (ii) Novel gender-inclusive datasets and (iii) Low-resource bias mitigation algorithms. The Human-AI systems that I am studying as part of my PhD thesis are-- (a) Face Recognition Systems (FRSs), (b) e-commerce platforms, (c) text-based gender analyzers and (d) Vision Language Models (VLMs)

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Yang, Shuo, Bardh Prenkaj, and Gjergji Kasneci. "RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 24 (2025): 25633–41. https://doi.org/10.1609/aaai.v39i24.34754.

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Despite the widespread use of LLMs due to their superior performance in various tasks, their high computational costs often lead potential users to opt for the pretraining-finetuning pipeline. However, biases prevalent in manually constructed datasets can introduce spurious correlations between tokens and labels, creating so-called shortcuts and hindering the generalizability of fine-tuned models. Existing debiasing methods often rely on prior knowledge of specific dataset biases, which is challenging to acquire a priori. We propose RAZOR (Rewriting And Zero-bias Optimization Refinement), a no

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El Khazri, Abdelghafour. "Impacts of Cultural Biases on the International Advertising Translation." Journal of Languages and Translation 1, no. 2 (2024): 84–96. http://dx.doi.org/10.70204/jlt.v1i2.206.

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The translator's role is, by definition, to transfer the linguistic and iconic meanings of the text from one language to another, but during the translation process the translator's attitudes, judgments, prejudices... come into play. These are cultural biases linked to the socio-cultural context in which he was raised. Therefore, we can say that the translator's cultural biases largely affect, on the one hand, the production of the text; and on the other hand, the process of the receiver’s involvement in the construction of the meaning of the message. Thus, the translator is given a great deal

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Schick, Timo, Sahana Udupa, and Hinrich Schütze. "Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLP." Transactions of the Association for Computational Linguistics 9 (2021): 1408–24. http://dx.doi.org/10.1162/tacl_a_00434.

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Abstract ⚠ This paper contains prompts and model outputs that are offensive in nature. When trained on large, unfiltered crawls from the Internet, language models pick up and reproduce all kinds of undesirable biases that can be found in the data: They often generate racist, sexist, violent, or otherwise toxic language. As large models require millions of training examples to achieve good performance, it is difficult to completely prevent them from being exposed to such content. In this paper, we first demonstrate a surprising finding: Pretrained language models recognize, to a considerable de

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Kim, Chanbin. "Reading Looking for Alaska Through Critical Literacy(CL) Centering on Superiority of the White and Racism." Korean Society for Teaching English Literature 26, no. 3 (2022): 71–92. http://dx.doi.org/10.19068/jtel.2022.26.3.03.

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This study aims at reading Looking for Alaska with critical literacy to find hidden biases in the text generated from racism or superiority of the white. In texts, there must be concrete intentions of an author in order to influence a reader. In Looking for Alaska, in spite of its popularity in American-reading education, the text reveals both superiority of the white and racism indirectly through allowing Eastern men or foreigners to be marginalized. In other words, the text contains several concealed hazardous elements which present racial discriminations against those who are not the white.

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Fitzsimmons, Lane, Maya Dewan, and Judith W. Dexheimer. "Diversity in Machine Learning: A Systematic Review of Text-Based Diagnostic Applications." Applied Clinical Informatics 13, no. 03 (2022): 569–82. http://dx.doi.org/10.1055/s-0042-1749119.

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Abstract Objective As the storage of clinical data has transitioned into electronic formats, medical informatics has become increasingly relevant in providing diagnostic aid. The purpose of this review is to evaluate machine learning models that use text data for diagnosis and to assess the diversity of the included study populations. Methods We conducted a systematic literature review on three public databases. Two authors reviewed every abstract for inclusion. Articles were included if they used or developed machine learning algorithms to aid in diagnosis. Articles focusing on imaging inform

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Li, Jia, Lijie Hu, Jingfeng Zhang, Tianhang Zheng, Hua Zhang, and Di Wang. "Fair Text-to-Image Diffusion via Fair Mapping." Proceedings of the AAAI Conference on Artificial Intelligence 39, no. 25 (2025): 26256–64. https://doi.org/10.1609/aaai.v39i25.34823.

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In this paper, we address the limitations of existing text-to-image diffusion models in generating demographically fair results when given human-related descriptions. These models often struggle to disentangle the target language context from sociocultural biases, resulting in biased image generation. To overcome this challenge, we propose Fair Mapping, a flexible, model-agnostic, and lightweight approach that modifies a pre-trained text-to-image diffusion model by controlling the prompt to achieve fair image generation. One key advantage of our approach is its high efficiency. It only require

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Voutyrakou, Dialekti Athina, Gianna Katsiampoura, and Constantine Skordoulis. "Are AI tools biased storytellers? Examining gender-bias in AI-generated narratives." Edelweiss Applied Science and Technology 9, no. 4 (2025): 1032–49. https://doi.org/10.55214/25768484.v9i4.6169.

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With millions of people relying on Artificial Intelligence (AI) tools such as Copilot, Gemini, and ChatGPT in their daily lives, evaluating the fairness of these systems and investigating their potential biases is crucial. The purpose of this research is to examine whether AI tools associate certain professions and hobbies with specific genders during storytelling, potentially perpetuating gender stereotypes. The study employs a dual approach: text-based and image-based storytelling are analyzed through controlled experiments. In the text analysis, patterns in gender-occupation pairings are id

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Dissertationen zum Thema "Text-based biases"

Doey, Laura. "Miscommunication Among Children Through Text-Based Media and Its Relation to Social Anxiety." Thesis, Université d'Ottawa / University of Ottawa, 2017. http://hdl.handle.net/10393/35766.

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This study examined how social anxiety, gender, and mode of presentation influenced miscommunication and perception of negativity in children’s interpretation of computer-mediated messages. The initial phase of the research involved developing and validating the stimuli for emotion recognition via presentation of various emotionally toned messages. Following preparation of the stimuli, the 98 participants (aged 8-12 years) in the main study were randomly assigned to one of three conditions: audio-visual, audio-only, and text message. The same emotionally toned messages were presented in each o

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Li, Meng. "Développement de l'expression orale du français chez les apprenants chinois par le biais de l'échange écrit instantané en ligne." Thesis, Limoges, 2020. http://aurore.unilim.fr/theses/nxfile/default/e30e642f-7e77-4c68-a010-2f57edcde34d/blobholder:0/2020LIMO0058.pdf.

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Notre étude s’inscrit dans le domaine de la didactique du français langue étrangère. Elle porte exclusivement sur le développement de la compétence d’expression orale en français par le biais de l’échange écrit instantané en ligne. Nous sommes partis du constat selon lequel l’expression orale constituait un grand handicap chez les étudiants chinois et que les pratiques d’enseignement en classe présentielle étaient insuffisantes pour y remédier. Dans ce contexte, nous avons pensé aux TICE et posé la question : les TICE peuvent-elles aider à créer un dispositif d’enseignement/apprentissage qui b

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Costa, Ana Rebello de Andrade da. "A text-mining based model to detect unethical biases in online reviews: a case-study of Amazon.com." Master's thesis, 2017. http://hdl.handle.net/10071/15297.

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The rapid growth of social media in the last decades led e-commerce into a new era of value co-creation between the seller and the consumer. Since there is no contact with the product, people have to rely on the description of the seller, knowing that sometimes it may be biased and not entirely truth. Therefore, reviewing systems emerged in order to provide more trustworthy sources of information, since customer opinions may be less biased. The problem was, once sellers realized the importance of reviews and their direct impact on sales, the need to control this key factor arose. One of the m

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Bücher zum Thema "Text-based biases"

Dunbar, Edward W., ed. Indoctrination to Hate. ABC-CLIO, LLC, 2022. http://dx.doi.org/10.5040/9798400669798.

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This collection spotlights the impact of hate violence on individuals and communities as well as how people form biases and are indoctrinated into hate groups, why they participate in violent hate crimes, and how hate may become extreme. This book details the solicitation and indoctrination of members into extremist hate groups. Using theoretical, empirical, and field studies, experts explain the psychological processes of bias formation, hate identity, and the stages of extremism, and detail first-person accounts of hate group membership and critical incidents of hate violence. Contributors d

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Spevak, Christopher J. Ethical Issues in Treating Pain and Addiction (DRAFT). Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190265366.003.0006.

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In addressing the ethical issues that arise in treating both pain and addiction, the author of this chapter has organized his presentation around: the history of medical ethics; theories and definitions; and the ethical challenges to providing clinical care. The theoretical underpinnings to ethical decision-making are important to providing the best possible outcome, and their evolution is described, from the Hippocratic Oath to current human subjects’ protection rules for clinical trials. The tension between patient autonomy and the physician’s obligation to protect is as high as that seen in

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Dobson, James E. Critical Digital Humanities. University of Illinois Press, 2019. http://dx.doi.org/10.5622/illinois/9780252042270.001.0001.

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This book seeks to develop an answer to the major question arising from the adoption of sophisticated data-science approaches within humanities research: are existing humanities methods compatible with computational thinking? Data-based and algorithmically powered methods present both new opportunities and new complications for humanists. This book takes as its founding assumption that the exploration and investigation of texts and data with sophisticated computational tools can serve the interpretative goals of humanists. At the same time, it assumes that these approaches cannot and will not

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Karim Bangura, Abdul, ed. United States Presidential Election of 2020. Lexington Books, 2023. https://doi.org/10.5040/9781978734142.

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This edited volume is the first comprehensive text to provide an evidence-based (i.e. emphasizing the practical application of the findings of the best available current research) and nonpartisan (i.e. not biased, especially toward any particular political group) analyses of the United States Presidential Election of 2020. The contributors to this volume present evidence pertaining to polling and improbabilities, the modernization of United States elections administration and the voting process, voting strategy and legal wrangling, the Black view, and challenges to democracy. The collection en

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Hilton, Denis. Social Attribution and Explanation. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.33.

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Attribution processes appear to be an integral part of human visual perception, as low-level inferences of causality and intentionality appear to be automatic and are supported by specific brain systems. However, higher-order attribution processes use information held in memory or made present at the time of judgment. While attribution processes about social objects are sometimes biased, there is scope for partial correction. This chapter reviews work on the generation, communication, and interpretation of complex explanations, with reference to explanation-based models of text understanding t

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Kinney, M. Killian. Gender Identity and Expression. Bloomsbury Publishing Inc, 2025. https://doi.org/10.5040/9798216172727.

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This book answers young readers' questions about gender – what it is, what it isn't, and how it impacts our experiences and our interactions with others. Gender is an essential part of all our lives, whether we recognize it as such or not and regardless of how we identify and express that identity. Gender informs how we feel about ourselves, the clothes we wear, how we engage with others, and much more. This volume’s 48 questions cover concepts such as gender roles and norms, the binary gender system and cisnormativity, gendered language, and gender discrimination and bias. Readers will also d

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Márquez-Peláez, Sergio, Juan Antonio Blasco-Amaro, and Mª José Aguado-Romeo. Incompatible living-donor kidney transplantation (an update). AETSA Área de Evaluación de Tecnologías Sanitarias de Andalucía, Fundación Progreso y salud. Consejería de Salud y Familias. Junta de Andalucía, 2022. http://dx.doi.org/10.52766/kpnf6027.

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Background This report responds to a need to update the available information about incompatible living-donor kidney transplantation (LDKT) previously published in 2014 which, based on 14 case series and 1 cohort study, concluded that this type of transplants could be a therapeutic option with survival, graft and patient outcomes, adequate and similar to a compatible living-donor kidney transplant, however, these report only included ABO-incompatible information. Objective The purpose of the report is to provide updated evidence on effectiveness and safety in terms of graft survival and surviv

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Buchteile zum Thema "Text-based biases"

Hendriks, Jennifer. "Investigating change from a perspective of continuity." In Investigating West Germanic Languages. John Benjamins Publishing Company, 2024. http://dx.doi.org/10.1075/sigl.8.10hen.

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Word order variation in Dutch two-verb clusters continues to attract the attention of linguists from a variety of perspectives. Most accounts have a contemporary focus and diachronic developments therefore remain poorly understood. Rather than simply marshalling more evidence from more historical sources, I argue for an approach which considers biases in the historical record and how common methodological practices of text selection and data aggregation exacerbate them. Van Coetsem’s (1988; 2000) psycholinguistic model of contact offers a principled way to establish whether the linguistic data

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Gurumurthy, Anita. "Towards Feminist Futures in the Platform Economy: Four Stories from India." In Epistemic Rights in the Era of Digital Disruption. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-45976-4_8.

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AbstractThis chapter focuses on how gender relations are orchestrated in the platform economy and its platform-mediated structures of social power. While digital platforms have been seen as opportunities for women to enter the labour market, there is little evidence that platform work is challenging existing structural biases. The totalising control of algorithms in platform-mediated work exposes platform workers to exploitative conditions, raising important questions about platform workers’ epistemic rights. Based on primary research in India, and building on the research undertaken with coll

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Nayak, Gopa, and Navreet Kaur Rana. "7. ‘Aboutness’ and semantic knowledge." In Digital Humanities in the India Rim. Open Book Publishers, 2024. http://dx.doi.org/10.11647/obp.0423.07.

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This essay establishes the use of computational methods to study the semantics of a historical corpus compiled from the ancient Indian text of Yajnavalkya Smriti. Although the use of corpora has been extended to the study of computational semantics, in addition to grammar usage and patterns of language, they have mostly been limited to word-sense disambiguation, structural disambiguation or analysing a semantic space in terms of calculating semantic distances and determining relations between words within a corpus. This study adopts the use of computational semantics on ‘aboutness’ and ‘knowle

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Gassara, Olfa, Belkacem Chikhaoui, Rostom Mabrouk, and Shengrui Wang. "Deriving Physiological Information from PET Images Using Machine Learning." In Digital Health Transformation, Smart Ageing, and Managing Disability. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-43950-6_3.

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AbstractMachine learning (ML) algorithms have become popular in recent years and have found increasing utility in the field of medical imaging, specifically in positron emission tomography (PET) imaging. The interest in ML in PET imaging for the study of neurodegenerative diseases stems from the potential of these techniques to analyze and predict the physiological parameters of biomarkers such as the total volume of distribution (V$$_{\text {t}}$$ t ) in the organ or a structure of the organ to be explored. In this paper, we investigated whether the V$$_{\text {t}}$$ t of [$$^{18}$$ 18 F]-FEP

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Viola, Lorella. "The Opposite of Unsupervised." In The Humanities in the Digital: Beyond Critical Digital Humanities. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-16950-2_3.

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AbstractOne widespread way to enhance access to digital material is through a method called ’content enrichment’. Enrichment consists of several techniques such as entity annotation (e.g., named entity recognition—NER), entity linking (e.g., entity disambiguation), text classification and linguistic annotation (e.g., parts-of-speech tagging—POS). In this chapter, I present the enrichment of ChroniclItaly 3.0 as an example of how the post-authentic framework can be used as the applied theory for the curation of digital material. ChroniclItaly 3.0 has been enriched for NER, geocoding and sentime

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Topolska, Ewelina. "Entre la licentia poetica y la psicopatología. ¿Qué haré yo con esta espada? (Aproximación a la Ley y al problema de la Belleza) de Angélica Liddell en diálogo con Erich Fromm." In Studi di letterature moderne e comparate. Firenze University Press, USiena Press, 2023. http://dx.doi.org/10.36253/979-12-215-0278-7.11.

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This article is an attempt to analyse the text ¿Qué haré yo con esta espada? (Aproximación a la Ley y al problema de la Belleza) by Angélica Liddell from the perspective of Erich Fromm's psychoanalysis, with particular focus on his concept of necrophilic orientation. The German psychoanalyst diagnosed this orientation in people fascinated by death, decay, disease, decomposition, who put material goods before human well-being and treated their fellow human beings in an instrumental, sadistic and destructive manner, being incapable of creating truly deep bonds based on Love. Liddell's works not

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Romano, Maurizio, Francesco Mola, and Claudio Conversano. "Decomposing tourists’ sentiment from raw NL text to assess customer satisfaction." In Proceedings e report. Firenze University Press, 2021. http://dx.doi.org/10.36253/978-88-5518-304-8.29.

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The importance of the Word of Mouth is growing day by day in many topics. This phenomenon is evident in everyday life, e.g., the rise of influencers and social media managers. If more people positively debate specific products, then even more people are encouraged to buy them and vice versa. This effect is directly affected by the relationship between the potential customer and the reviewer. Moreover, considering the negative reporting bias is evident in how the Word of Mouth analysis is of absolute interest in many fields. We propose an algorithm to extract the sentiment from a natural langua

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Cheney, Debora. "Big Data, Text Mining, and News Content." In Advances in Media, Entertainment, and the Arts. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8580-2.ch008.

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Mining the natural language text of news content has great potential for academic researchers seeking to understand and visualize patterns and relationships buried within everyday news coverage and content. Mining news can help researchers across many disciplines understand the impact of news, biases in news coverage, and language usage. It can also help them detect unknown patterns in news coverage. However, researchers must understand the challenges of using news text for text-mining-based research. Many challenges are inherent in the news form, including the complexity of the news environme

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Nag, Bodhibrata. "Navigating Ethical Dilemmas in Generative AI." In Advances in Computational Intelligence and Robotics. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-9173-0.ch007.

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Generative AI, based on neural networks, is transforming the creation of content like text, images, music, and interactive digital experiences. However, it raises ethical and practical questions about the authenticity of AI-generated works, intellectual property rights, and the role of creators. AI is also transforming journalism by integrating algorithms and automation, but raises ethical concerns about potential biases and transparency. To address these issues, the sector should set clear standards, promote diversity, and encourage cooperation among technologists, artists, ethicists, and pol

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Reyero Lobo, Paula, Enrico Daga, Harith Alani, and Miriam Fernandez. "Knowledge-Grounded Target Group Language Recognition in Hate Speech." In Knowledge Graphs: Semantics, Machine Learning, and Languages. IOS Press, 2023. http://dx.doi.org/10.3233/ssw230002.

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Hate speech comes in different forms depending on the communities targeted, often based on factors like gender, sexuality, race, or religion. Detecting it online is challenging because existing systems are not accounting for the diversity of hate based on the identity of the target and may be biased towards certain groups, leading to inaccurate results. Current language models perform well in identifying target communities, but only provide a probability that a hate speech text contains references to a particular group. This lack of transparency is problematic because these models learn biases

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Konferenzberichte zum Thema "Text-based biases"

Liu, Xin, Muhammad Khalifa, and Lu Wang. "BOLT: Fast Energy-based Controlled Text Generation with Tunable Biases." In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). Association for Computational Linguistics, 2023. http://dx.doi.org/10.18653/v1/2023.acl-short.18.

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Lepekhin, Mikhail, and Serge Sharoff. "Experiments with adversarial attacks on text genres." In Dialogue. RSUH, 2022. http://dx.doi.org/10.28995/2075-7182-2022-21-1097-1108.

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Neural models based on pre-trained transformers, such as BERT or XLM-RoBERTa, demonstrate SOTA results in many NLP tasks, including non-topical classification, such as genre identification. However, often these approaches exhibit low reliability to minor alterations of the test texts. One of the problems concerns topical biases in the training corpus, for example, the prevalence of words on a specific topic in a specific genre can trick the genre classifier to recognise any text on this topic in this genre. In order to mitigate this problem, we investigate techniques for attacking genre classi

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Bratke, Pascal, Roland Zimmermann, and Ralph Blum. "Fostering text mining with knowledge graphs: An approach to support business experts in defining domain-specific document sets." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003128.

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Text mining techniques offer an efficient approach to extract information from text-based data, such as online news, for strategic planning tasks like the scenario technique. Data selection and data preprocessing is a crucial step in this process, during which decisive search terms help to sharpen the text corpus for downstream text mining activities. The integration of business knowledge is crucial for the creation of high-quality domain-specific document sets. Manually defining search terms is a time-consuming task for managers. Knowledge graphs accelerate this vital process: Based on a few

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Yadav, Rohan Kumar, Lei Jiao, Ole-Christoffer Granmo, and Morten Goodwin. "Robust Interpretable Text Classification against Spurious Correlations Using AND-rules with Negation." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/616.

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The state-of-the-art natural language processing models have raised the bar for excellent performance on a variety of tasks in recent years. However, concerns are rising over their primitive sensitivity to distribution biases that reside in the training and testing data. This issue hugely impacts the performance of the models when exposed to out-of-distribution and counterfactual data. The root cause seems to be that many machine learning models are prone to learn the shortcuts, modelling simple correlations rather than more fundamental and general relationships. As a result, such text classif

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Banno, Yuka, and Yusaku Okada. "Development of an analysis support tool for near-miss events using AI technology - Improving human factor management capabilities in the field." In 16th International Conference on Applied Human Factors and Ergonomics (AHFE 2025). AHFE International, 2025. https://doi.org/10.54941/ahfe1006566.

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Near-miss analysis is essential for identifying factors contributing to human errors and developing preventive measures. However, conventional text mining methods primarily extract direct causes, such as "lack of attention" or "insufficient verification," often overlooking broader background factors embedded in work environments. This study explores the use of Large Language Models (LLMs) to enhance factor analysis by capturing a more comprehensive range of underlying causes. Using Llama3-ELYZA-JP-8B, we incorporated 87 predefined background factors based on established frameworks, including P

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La Malfa, Emanuele, Rhiannon Michelmore, Agnieszka M. Zbrzezny, Nicola Paoletti, and Marta Kwiatkowska. "On Guaranteed Optimal Robust Explanations for NLP Models." In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/366.

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We build on abduction-based explanations for machine learning and develop a method for computing local explanations for neural network models in natural language processing (NLP). Our explanations comprise a subset of the words of the input text that satisfies two key features: optimality w.r.t. a user-defined cost function, such as the length of explanation, and robustness, in that they ensure prediction invariance for any bounded perturbation in the embedding space of the left-out words. We present two solution algorithms, respectively based on implicit hitting sets and maximum universal sub

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Boukhechba, Mehdi, Mingyue Tang, Brendan Bowman, Jamie Zoellner, and Emaad Abdel-Rahman. "A Smartwatch Based system for Monitoring Fluid Consumption of End Stage Kidney Patients." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1002101.

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Background:End Stage Kidney disease (ESKD) patients must follow unique dietary restrictions. The most onerous of these is the need to restrict fluid intake. The ramifications of poor fluid control include increased mortality and morbidities, frequent hospitalizations with diagnoses of heart failure and pulmonary edema, increased hospital length of stay, and increased total cost of care. Fluid intake control is a bedrock component of treatment for ESKD Patients, but continues to be a major challenge for patients, healthcare providers, and organizations. The ramifications of poor fluid control i

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LIU, ZE-LIN. "THE INFLUENCE OF BIASED SIGNAL SET ON STOCK MARKET—BASED ON THE SHANGHAI COMPOSITE INDEX." In 2021 International Conference on Management, Economics, Business and Information Technology. Destech Publications, Inc., 2021. http://dx.doi.org/10.12783/dtem/mebit2021/35637.

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Based on the two phenomena of over and underreaction, this paper introduces the characteristics of signal set into the model, which studies the price deviation of financial market caused by investors' signal set deviation. The text concludes that investors overreact to information of low weight and underreact to information of high weight, and uses cross-section analysis and time series analysis to verify the correctness of the results.

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He, Zexue, Bodhisattwa Prasad Majumder, and Julian McAuley. "Detect and Perturb: Neutral Rewriting of Biased and Sensitive Text via Gradient-based Decoding." In Findings of the Association for Computational Linguistics: EMNLP 2021. Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.findings-emnlp.352.

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Xue, Yuting, Heng Zhou, Yuxuan Ding, and Xiao Shan. "Adaptive Forgetting, Drafting and Comprehensive Guiding: Text-to-Image Synthesis with Hierarchical Generative Adversarial Networks." In 11th International Conference on Embedded Systems and Applications (EMSA 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120623.

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The generation task from text to image generates cross modal data with consistent content by mining the semantic consistency contained in two different modal information of text and image. Due to the differences between the two modes, the task of text to image generation faces many difficulties and challenges. In this paper, we propose to boost the text-to-image synthesis through an adaptive learning and generating generative adversarial networks (ALG-GANs). First, we propose an adaptive forgetting mechanism in the generator to reduce the error accumulation and learn knowledge flexibly in the

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Berichte der Organisationen zum Thema "Text-based biases"

Peterson, Bradley S., Joey Trampush, Margaret Maglione, et al. ADHD Diagnosis and Treatment in Children and Adolescents. Agency for Healthcare Research and Quality (AHRQ), 2024. http://dx.doi.org/10.23970/ahrqepccer267.

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Objective. The systematic review assessed evidence on the diagnosis, treatment, and monitoring of attention deficit hyperactivity disorder (ADHD) in children and adolescents to inform a planned update of the American Academy of Pediatrics (AAP) guidelines. Data sources. We searched PubMed®, Embase®, PsycINFO®, ERIC, clinicaltrials.gov, and prior reviews for primary studies published since 1980. The report includes studies published to June 15, 2023. Review methods. The review followed a detailed protocol and was supported by a Technical Expert Panel. Citation screening was facilitated by machi

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Parsons, Helen M., Hamdi I. Abdi, Victoria A. Nelson, et al. Transitions of Care From Pediatric to Adult Services for Children With Special Healthcare Needs. Agency for Healthcare Research and Quality (AHRQ), 2022. http://dx.doi.org/10.23970/ahrqepccer255.

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Objective. To understand the evidence base for care interventions, implementation strategies, and between-provider communication tools among children with special healthcare needs (CSHCN) transitioning from pediatric to adult medical care services. Data sources. We searched Ovid MEDLINE, Ovid Embase, the Cochrane Central trials (CENTRAL) registry, and CINAHL to identify studies through September 10, 2021. We conducted grey literature searches to identify additional resources relevant to contextual questions. Review methods. Using a mixed-studies review approach, we searched for intervention

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Stadler, Diane, Rebecca Jungbauer, Azrah Ahmed, Nicole Marshall, Amy Valent, and Annette Totten. Digestible Carbohydrate Intake and Maternal-Infant Outcomes: A Systematic Review. AHRQ, 2025. https://doi.org/10.23970/ahrqepcsrcarbmaternal.

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Background. Optimal nutrition is needed to support individuals during pregnancy and placental development, fetal growth, and growth and development during infancy. Many foods contain digestible carbohydrates, or carbohydrates other than fiber/nondigestible carbohydrate. Digestible carbohydrates, including sugars and starches, are important sources of energy during these life stages. This review was designed to identify and summarize the evidence on the relationships between digestible carbohydrate intake during pregnancy and newborn size and development (Key Question 1) and gestational weight

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Treadwell, Jonathan R., Mingche Wu, and Amy Y. Tsou. Management of Infantile Epilepsies. Agency for Healthcare Research and Quality (AHRQ), 2022. http://dx.doi.org/10.23970/ahrqepccer252.

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Objectives. Uncontrolled seizures in children 1 to 36 months old have serious short-term health risks and may be associated with substantial developmental, behavioral, and psychological impairments. We evaluated the effectiveness, comparative effectiveness, and harms of pharmacologic, dietary, surgical, neuromodulation, and gene therapy treatments for infantile epilepsies. Data sources. We searched Embase®, MEDLINE®, PubMed®, the Cochrane Library, and gray literature for studies published from January 1, 1999, to August 19, 2021. Review methods. Using standard Evidence-based Practice Center me

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A, Bengolea, Chamorro F, Catalano HN, and Izcovich A. Assessing the safety and effectiveness of the bivalent vaccine against respiratory syncytial virus in pregnant women: a systematic review. Epistemonikos Interactive Evidence Synthesis, 2024. http://dx.doi.org/10.30846/ies.ac54af0724.

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Objective The aim of this systematic review is to conduct a comprehensive assessment of the efficacy and safety of the bivalent vaccine against the respiratory syncytial virus (RSV) compared to the placebo or the absence of vaccination in pregnant women to inform a clinical recommendation at the internal medicine department of Hospital Alemán of Buenos Aires. Methods In order to identify randomized clinical trials that evaluate our question of interest, we carry out thorough searches in Epistemonikos and Pubmed, from the date of creation of each source until January of the year 2024. Additiona

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Selph, Shelley S., Andrea C. Skelly, Tracy Dana, et al. Psychosocial and Pharmacologic Interventions for Disruptive Behavior in Children and Adolescents: A Systematic Review. Agency for Healthcare Research and Quality, 2025. https://doi.org/10.23970/ahrqepcsrdisruptive.

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Objectives. To determine the most effective treatments for clinically significant disruptive behaviors in children and adolescents. Data sources. Ovid® MEDLINE®, the Cochrane Library, PsycINFO®, and Embase® databases were searched from 2014 to July 22, 2024. Additionally, we reviewed all studies included in the prior 2015 Agency for Healthcare Research and Quality review. Review methods. We dual reviewed abstracts and full-text articles; data extraction was checked by a second reviewer; risk of bias and strength of evidence were assessed by two reviewers; and disagreements were resolved by con

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