Quantifying gender biases towards politicians on Reddit

Article Properties
Abstract
Cite
Marjanovic, Sara, et al. “Quantifying Gender Biases towards Politicians on Reddit”. PLOS ONE, vol. 17, no. 10, 2022, p. e0274317, https://doi.org/10.1371/journal.pone.0274317.
Marjanovic, S., Stańczak, K., & Augenstein, I. (2022). Quantifying gender biases towards politicians on Reddit. PLOS ONE, 17(10), e0274317. https://doi.org/10.1371/journal.pone.0274317
Marjanovic S, Stańczak K, Augenstein I. Quantifying gender biases towards politicians on Reddit. PLOS ONE. 2022;17(10):e0274317.
Journal Categories
Medicine
Science
Science
Science (General)
Refrences
Title Journal Journal Categories Citations Publication Date
Leading the Fight Against the Pandemic: Does Gender Really Matter? Feminist Economics
  • Social Sciences: Economic theory. Demography: Economics as a science
  • Social Sciences: The family. Marriage. Woman: Women. Feminism
  • Social Sciences: Commerce: Business
  • Social Sciences: Economic theory. Demography: Economics as a science
 42 2021
MULTILINGUAL SENTIMENT NORMALIZATION FOR SCANDINAVIAN LANGUAGES

 Scandinavian Studies in Language
  • Language and Literature: Philology. Linguistics
  • Language and Literature: Germanic languages. Scandinavian languages
 1 2021
Misogyny Detection in Twitter: a Multilingual and Cross-Domain Study Information Processing & Management
  • Bibliography. Library science. Information resources
  • Science: Science (General): Cybernetics: Information theory
  • Bibliography. Library science. Information resources: Information resources (General)
  • Technology: Technology (General): Industrial engineering. Management engineering: Information technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication
  • Social Sciences
 38 2020
The Pushshift Reddit Dataset

 Proceedings of the International AAAI Conference on Web and Social Media 152 2020
Content Analysis of Textbooks via Natural Language Processing: Findings on Gender, Race, and Ethnicity in Texas U.S. History Textbooks

 AERA Open
  • Education
  • Education: Theory and practice of education
  • Education
  • Social Sciences
 31 2020
Citations
Title Journal Journal Categories Citations Publication Date
How do medical professionals make sense (or not) of AI? A social-media-based computational grounded theory study and an online survey Computational and Structural Biotechnology Journal
  • Science: Biology (General)
  • Science: Biology (General)
  • Science: Chemistry: Organic chemistry: Biochemistry
 1 2024
Does the Gender of Doctors Change a Patient’s Perception? Health Communication
  • Language and Literature: Philology. Linguistics: Communication. Mass media
  • Medicine: Public aspects of medicine
  • Social Sciences
 2024
Creating a Chinese gender lexicon for detecting gendered wording in job advertisements Information Processing & Management
  • Bibliography. Library science. Information resources
  • Science: Science (General): Cybernetics: Information theory
  • Bibliography. Library science. Information resources: Information resources (General)
  • Technology: Technology (General): Industrial engineering. Management engineering: Information technology
  • Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication
  • Social Sciences
 2023
Citations Analysis
Category Category Repetition
Social Sciences2
Science: Biology (General)1
Science: Chemistry: Organic chemistry: Biochemistry1
Language and Literature: Philology. Linguistics: Communication. Mass media1
Medicine: Public aspects of medicine1
Bibliography. Library science. Information resources1
Science: Science (General): Cybernetics: Information theory1
Bibliography. Library science. Information resources: Information resources (General)1
Technology: Technology (General): Industrial engineering. Management engineering: Information technology1
Technology: Electrical engineering. Electronics. Nuclear engineering: Telecommunication1
The category Social Sciences 2 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Creating a Chinese gender lexicon for detecting gendered wording in job advertisements and was published in 2023. The most recent citation comes from a 2024 study titled Does the Gender of Doctors Change a Patient’s Perception?. This article reached its peak citation in 2024, with 2 citations. It has been cited in 3 different journals. Among related journals, the Health Communication cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year