Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination

From Wikipedia Quality
Revision as of 22:29, 2 April 2019 by Emilia (talk | contribs) (Created page with "{{Infobox work | title = 2019 | date = Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination | authors = Jahna Otterbacher<br />Ioannis Katakis<br /...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to: navigation, search


2019
Authors
Jahna Otterbacher
Ioannis Katakis
Pantelis Agathangelou
Publication date
"Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination" contains an extrinsic dash or other characters that are invalid for a date interpretation.
Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination
DOI
10.1142/9789813274884_0012
Links
Original

2019 - scientific work about Wikipedia quality published in Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination, written by Jahna Otterbacher, Ioannis Katakis and Pantelis Agathangelou.

Overview

Biographies make up a significant portion of Wikipedia entries and are a source of information and inspiration for the public. Authors examine a threat to their objectivity, linguistic biases, which are pervasive in human communication. Linguistic bias, the systematic asymmetry in the language used to describe people as a function of their social groups, plays a role in the perpetuation of stereotypes. Theory predicts that authors describe people who are expected — because they are members of own in-groups or are stereotype-congruent — with more abstract, subjective language, as compared to others. Abstract language has the power to sway impressions of others as it implies stability over time. Extending monolingual work, authors consider biographies of intellectuals at the English- and Greek-language Wikipedia. Authors use recently introduced sentiment analysis tool, DidaxTo, which extracts domain-specific opinion words to build lexicons of subjective words in each language and for each gender, and compare the extent to which abstract language is used. Contrary to expectation, authors find evidence of gender-based linguistic bias, with women being described more abstractly as compared to men. However, this is limited to English-language biographies. Authors discuss the implications of using DidaxTo to monitor linguistic bias in texts produced via crowdsourcing.

Embed

Wikipedia Quality

Otterbacher, Jahna; Katakis, Ioannis; Pantelis, Agathangelou. (Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination). "[[2019]]". Multilingual Text Analysis: Challenges, Models, And Approaches (2019): 411. DOI: 10.1142/9789813274884_0012.

English Wikipedia

{{cite journal |last1=Otterbacher |first1=Jahna |last2=Katakis |first2=Ioannis |last3=Pantelis |first3=Agathangelou |title=2019 |date=Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination |doi=10.1142/9789813274884_0012 |url=https://wikipediaquality.com/wiki/2019 |journal=Multilingual Text Analysis: Challenges, Models, And Approaches (2019): 411}}

HTML

Otterbacher, Jahna; Katakis, Ioannis; Pantelis, Agathangelou. (Linguistic Bias in Crowdsourced Biographies: A Cross-lingual Examination). &quot;<a href="https://wikipediaquality.com/wiki/2019">2019</a>&quot;. Multilingual Text Analysis: Challenges, Models, And Approaches (2019): 411. DOI: 10.1142/9789813274884_0012.