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Melody Sepahpour-Fard

dblp:314/6954 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
0000-0002-8472-9514ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%
Artificial intelligence
1 paper
Information extraction and text analysis · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities › social computing
online community analysis
0.612022
How Do Mothers and Fathers Talk About Parenting to Different Audiences?: Stereotypes and Audience Effects: An Analysis of r/Daddit, r/Mommit, and r/Parenting Using Topic Modelling · WWW 2022
Natural language and speech › Information extraction and text analysis
topic model
0.212022
How Do Mothers and Fathers Talk About Parenting to Different Audiences?: Stereotypes and Audience Effects: An Analysis of r/Daddit, r/Mommit, and r/Parenting Using Topic Modelling · WWW 2022

Methods — techniques the papers use, named apart from their topics

latent dirichlet allocation · 1.1
YearPublicationVenuePosition
2022 How Do Mothers and Fathers Talk About Parenting to Different Audiences?: Stereotypes and Audience Effects: An Analysis of r/Daddit, r/Mommit, and r/Parenting Using Topic Modelling
abstract
While major strides have been made towards gender equality in public life, serious inequality remains in the domestic sphere, especially around parenting. The present study analyses discussions about parenting on Reddit (i.e., a content aggregation website) to explore audience effects and gender stereotypes. It suggests a novel method to study topical variation in individuals’ language when interacting with different audiences. Comments posted in 2020 were collected from three parenting subreddits (i.e., topical communities), described as being for fathers (r/Daddit), mothers (r/Mommit), and all parents (r/Parenting). Users posting on r/Parenting and r/Daddit or on r/Parenting and r/Mommit were assumed to identify as fathers or mothers, respectively, allowing gender comparison. Users’ comments on r/Parenting (to a mixed-gender audience) were compared with their comments to single-gender audiences on r/Daddit or r/Mommit using Latent Dirichlet Allocation (LDA) topic modelling.
Melody Sepahpour-Fard, Michael Quayle
WWW1