TY - JOUR
T1 - Stereotyping in the digital age
T2 - Male language is "ingenious", female language is "beautiful" - And popular
AU - Meier, Tabea
AU - Boyd, Ryan L.
AU - Mehl, Matthias R.
AU - Milek, Anne
AU - Pennebaker, James W.
AU - Martin, Mike
AU - Wolf, Markus
AU - Horn, Andrea B.
N1 - Funding Information:
Financial support by the Jacobs Foundation helped to conduct this research (https://jacobsfoundation.org/en/; doctoral fellowship awarded to TM) ABH received financial support by the Swiss National Science Foundation (https://www.snf.ch/en/; 1 grant: SNF PMPDP1_164470). Preparation of this manuscript was additionally aided by grants from the National Institutes of Health (https://www.nih.gov; 5R01GM112697-02 awarded to JWP, RLB), John Templeton Foundation (https://www.templeton. org; 2 grants #48503 and #61156 awarded to JWP, RLB), the Federal Bureau of Investigation (https://www.fbi.gov; 1 grant 15F06718R0006603 awarded to JWP, RLB), and the National Science Foundation (https://www.nsf.gov; 1 grant IIS- 1344257 awarded to JWP, RLB). The views, opinions, and findings contained in this document are those of the authors and should not be construed as position, policy, or decision of the aforementioned agencies, unless so designated by other documents. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2020 Meier et al.
PY - 2020/12
Y1 - 2020/12
N2 - The huge power for social influence of digital media may come with the risk of intensifying common societal biases, such as gender and age stereotypes. Speaker's gender and age also behaviorally manifest in language use, and language may be a powerful tool to shape impact. The present study took the example of TED, a highly successful knowledge dissemination platform, to study online influence. Our goal was to investigate how gender- and agelinked language styles-beyond chronological age and identified gender-link to talk impact and whether this reflects gender and age stereotypes. In a pre-registered study, we collected transcripts of TED Talks along with their impact measures, i.e., views and ratios of positive and negative talk ratings, from the TED website. We scored TED Speakers' (N = 1, 095) language with gender- and age-morphed language metrics to obtain measures of female versus male, and younger versus more senior language styles. Contrary to our expectations and to the literature on gender stereotypes, more female language was linked to higher impact in terms of quantity, i.e., more talk views, and this was particularly the case among talks with a lot of views. Regarding quality of impact, language signatures of gender and age predicted different types of positive and negative ratings above and beyond main effects of speaker's gender and age. The differences in ratings seem to reflect common stereotype contents of warmth (e.g., "beautiful"for female, "courageous"for female and senior language) versus competence (e.g., "ingenious", "informative"for male language). The results shed light on how verbal behavior may contribute to stereotypical evaluations. They also illuminate how, within new digital social contexts, female language might be uniquely rewarded and, thereby, an underappreciated but highly effective tool for social influence. WC = 286 (max. 300 words).
AB - The huge power for social influence of digital media may come with the risk of intensifying common societal biases, such as gender and age stereotypes. Speaker's gender and age also behaviorally manifest in language use, and language may be a powerful tool to shape impact. The present study took the example of TED, a highly successful knowledge dissemination platform, to study online influence. Our goal was to investigate how gender- and agelinked language styles-beyond chronological age and identified gender-link to talk impact and whether this reflects gender and age stereotypes. In a pre-registered study, we collected transcripts of TED Talks along with their impact measures, i.e., views and ratios of positive and negative talk ratings, from the TED website. We scored TED Speakers' (N = 1, 095) language with gender- and age-morphed language metrics to obtain measures of female versus male, and younger versus more senior language styles. Contrary to our expectations and to the literature on gender stereotypes, more female language was linked to higher impact in terms of quantity, i.e., more talk views, and this was particularly the case among talks with a lot of views. Regarding quality of impact, language signatures of gender and age predicted different types of positive and negative ratings above and beyond main effects of speaker's gender and age. The differences in ratings seem to reflect common stereotype contents of warmth (e.g., "beautiful"for female, "courageous"for female and senior language) versus competence (e.g., "ingenious", "informative"for male language). The results shed light on how verbal behavior may contribute to stereotypical evaluations. They also illuminate how, within new digital social contexts, female language might be uniquely rewarded and, thereby, an underappreciated but highly effective tool for social influence. WC = 286 (max. 300 words).
UR - http://www.scopus.com/inward/record.url?scp=85098264756&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85098264756&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0243637
DO - 10.1371/journal.pone.0243637
M3 - Article
C2 - 33326456
AN - SCOPUS:85098264756
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 12
M1 - e0243637
ER -