scholarly journals The Effects of Gender Signals and Performance in Online Product Reviews

2022 ◽  
Vol 4 ◽  
Author(s):  
Sandipan Sikdar ◽  
Rachneet Sachdeva ◽  
Johannes Wachs ◽  
Florian Lemmerich ◽  
Markus Strohmaier
Keyword(s):  
General Trend ◽  
Product Reviews ◽  
Product Categories ◽  
Learning Classifier ◽  
Specific Effects ◽  
Review Helpfulness ◽  
Social Media Platforms ◽  
And Performance ◽  
Context Specific ◽  
Gender Specific

This work quantifies the effects of signaling gender through gender specific user names, on the success of reviews written on the popular amazon.com shopping platform. Highly rated reviews play an important role in e-commerce since they are prominently displayed next to products. Differences in reviews, perceived—consciously or unconsciously—with respect to gender signals, can lead to crucial biases in determining what content and perspectives are represented among top reviews. To investigate this, we extract signals of author gender from user names to select reviews where the author’s likely gender can be inferred. Using reviews authored by these gender-signaling authors, we train a deep learning classifier to quantify the gendered writing style (i.e., gendered performance) of reviews written by authors who do not send clear gender signals via their user name. We contrast the effects of gender signaling and performance on the review helpfulness ratings using matching experiments. This is aimed at understanding if an advantage is to be gained by (not) signaling one’s gender when posting reviews. While we find no general trend that gendered signals or performances influence overall review success, we find strong context-specific effects. For example, reviews in product categories such as Electronics or Computers are perceived as less helpful when authors signal that they are likely woman, but are received as more helpful in categories such as Beauty or Clothing. In addition to these interesting findings, we believe this general chain of tools could be deployed across various social media platforms.

Validation of the Procrastination at Work Scale

2020 ◽  
Vol 36 (5) ◽  
pp. 767-776
Author(s):  
U. Baran Metin ◽  
Toon W. Taris ◽  
Maria C. W. Peeters ◽  
Max Korpinen ◽  
Urška Smrke ◽  
...  
Keyword(s):  
Work Engagement ◽  
Discriminant Validity ◽  
Psychometric Characteristics ◽  
The Czech Republic ◽  
The United Kingdom ◽  
Confirmatory Factor ◽  
And Performance ◽  
Context Specific ◽  
Negative Links ◽  
Office Employees

Abstract. Procrastination at work has been examined relatively scarcely, partly due to the lack of a globally validated and context-specific workplace procrastination scale. This study investigates the psychometric characteristics of the Procrastination at Work Scale (PAWS) among 1,028 office employees from seven countries, namely, Croatia, the Czech Republic, Finland, Slovenia, Turkey, Ukraine, and the United Kingdom. Specifically, it was aimed to test the measurement invariance of the PAWS and explore its discriminant validity by examining its relationships with work engagement and performance. Multi-group confirmatory factor analysis shows that the basic factor structure and item loadings of the PAWS are invariant across countries. Furthermore, the two subdimensions of procrastination at work exhibited different patterns of relationships with work engagement and performance. Whereas soldiering was negatively related to work engagement and task performance, cyberslacking was unrelated to engagement and performance. These results indicate further validity evidence for the PAWS and the psychometric characteristics show invariance across various countries/languages. Moreover, workplace procrastination, especially soldiering, is a problematic behavior that shows negative links with work engagement and performance.

312-OR: Gender-Specific Effects on Hepatic Fat Metabolism in Type 2 Diabetes before and after Remission

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 312-OR
Author(s):  
AHMAD AL-MRABEH ◽  
SHADEN MELHEM ◽  
SVIATLANA V. ZHYZHNEUSKAYA ◽  
CARL PETERS ◽  
ALISON C. BARNES ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Fat Metabolism ◽  
Specific Effects ◽  
Before And After ◽  
Hepatic Fat ◽  
Gender Specific

scholarly journals Gender-Specific Effects of Cognitive Load on Social Discounting

PLoS ONE ◽  
2016 ◽  
Vol 11 (10) ◽  
pp. e0165289 ◽  
Author(s):  
Tina Strombach ◽  
Zsofia Margittai ◽  
Barbara Gorczyca ◽  
Tobias Kalenscher
Keyword(s):  
Cognitive Load ◽  
Specific Effects ◽  
Social Discounting ◽  
Gender Specific

ERP Evidence for Implicit Priming of Top–Down Control of Attention

2016 ◽  
Vol 28 (5) ◽  
pp. 763-772 ◽  
Author(s):  
Chris Blais ◽  
Emily Hubbard ◽  
George R. Mangun
Keyword(s):  
Associative Learning ◽  
Stroop Effect ◽  
Congruency Effect ◽  
Simon Task ◽  
Electrical Signal ◽  
Lower Visual Field ◽  
Specific Effects ◽  
High Conflict ◽  
Contemporary Work ◽  
Context Specific

Proportion congruency effects are the observation that the magnitude of the Stroop effect increases as the proportion of congruent trials in a block increases. Contemporary work shows that proportion effects can be specific to a particular context. For example, in a Simon task in which items appearing above fixation are mostly congruent and items appearing below fixation are mostly incongruent, the Simon effect is larger for the items appearing at the top. There is disagreement as to whether these context-specific effects result from simple associative learning or, instead, a type of conflict-mediated associative learning. Here, we address this question in an ERP study using a Simon task in which the proportion congruency effect was context-specific, manipulating the proportion of congruent trials based on location (upper vs. lower visual field). We found significant behavioral proportion congruency effects that varied with the specific contexts. In addition, we observed that the N2 response of the ERPs to the stimuli was larger in amplitude for the high congruent (high conflict) versus low congruent (low conflict) conditions/contexts. Because the N2 is known to be greater in amplitude also for trials where conflict is high and is believed to be an electrical signal related to conflict detection in the medial frontal cortex, this supports the idea that conflict-mediated associative learning is involved in the proportion congruency effect.

scholarly journals Expectancy of Stress-Reducing Aromatherapy Effect and Performance on a Stress-Sensitive Cognitive Task

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Irina Chamine ◽  
Barry S. Oken
Keyword(s):  
Task Performance ◽  
Stress Reduction ◽  
Cognitive Task ◽  
Reaction Times ◽  
Event Related Potentials ◽  
Specific Effects ◽  
N200 Amplitude ◽  
Related Potentials ◽  
And Performance

Objective. Stress-reducing therapies help maintain cognitive performance during stress. Aromatherapy is popular for stress reduction, but its effectiveness and mechanism are unclear. This study examined stress-reducing effects of aromatherapy on cognitive function using the go/no-go (GNG) task performance and event related potentials (ERP) components sensitive to stress. The study also assessed the importance of expectancy in aromatherapy actions.Methods. 81 adults were randomized to 3 aroma groups (active experimental, detectable, and undetectable placebo) and 2 prime subgroups (prime suggesting stress-reducing aroma effects or no-prime). GNG performance, ERPs, subjective expected aroma effects, and stress ratings were assessed at baseline and poststress.Results. No specific aroma effects on stress or cognition were observed. However, regardless of experienced aroma, people receiving a prime displayed faster poststress median reaction times than those receiving no prime. A significant interaction for N200 amplitude indicated divergent ERP patterns between baseline and poststress for go and no-go stimuli depending on the prime subgroup. Furthermore, trends for beneficial prime effects were shown on poststress no-go N200/P300 latencies and N200 amplitude.Conclusion. While there were no aroma-specific effects on stress or cognition, these results highlight the role of expectancy for poststress response inhibition and attention.

P.1.c.025 Gender-specific effects of tickling on serotonergic and dopaminergic signal transmission in rats

2007 ◽  
Vol 17 ◽  
pp. S256
Author(s):  
L. Herm ◽  
A. Vonk ◽  
T. Mällo ◽  
D. Matrov ◽  
J. Harro ◽  
...  
Keyword(s):  
Signal Transmission ◽  
Specific Effects ◽  
Gender Specific

scholarly journals Context-specific Effects of Fibulin-5 (DANCE/EVEC) on Cell Proliferation, Motility, and Invasion

2002 ◽  
Vol 277 (30) ◽  
pp. 27367-27377 ◽  
Author(s):  
William P. Schiemann ◽  
Gerard C. Blobe ◽  
Dario E. Kalume ◽  
Akhilesh Pandey ◽  
Harvey F. Lodish
Keyword(s):  
Cell Proliferation ◽  
Specific Effects ◽  
Context Specific

Assessing the Unacquainted: Inferred Reviewer Personality and Review Helpfulness

MIS Quarterly ◽  
2021 ◽  
Vol 45 (3) ◽  
pp. 1113-1148
Author(s):  
Angela Xia Liu ◽  
◽  
Yilin Li ◽  
Sean Xu ◽  
◽  
...  
Keyword(s):  
Personality Traits ◽  
Supervised Classification ◽  
Large Population ◽  
Superior Performance ◽  
Product Reviews ◽  
Review Helpfulness ◽  
Personality Theories ◽  
Deep Learning Model ◽  
Practical Implications

This work examines the question of who is more likely to provide future helpful reviews in the context of online product reviews by synergistically using personality theories and data analytics. It trains a deep learning model to infer a reviewer’s personality traits. This enables analyses to reveal the role of personality traits in review helpfulness among a large population of reviewers. We develop hypotheses on how personality traits are associated with review helpfulness, followed by hypotheses testing that confirms that higher review helpfulness is related to higher openness, conscientiousness, extraversion, and agreeableness and to lower emotional stability. These results suggest the appropriateness of using these five personality traits as inputs for developing a model for predicting future review helpfulness. Based on an ensemble model using supervised classification algorithms, we develop a predictive model and demonstrate its superior performance. Theoretical and practical implications are discussed.

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