This study explores the impact of gender revelation on the level of support received on online platforms. It introduces a novel dataset and methodology for identifying supportive responses, along with innovative techniques for inferring gender from text and names. Applying these methods to a vast corpus of 102 million online interactions, the analysis reveals a consistent pattern: identifying as a woman correlates with receiving more support but also facing more disparagement.
-
Wang, Zijian, and David Jurgens. "It’s going to be okay: Measuring access to support in online communities." Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2018.
-
Members
- Voyage
- GazzaGarratt
- rainx
- Adriano Faria
- opentype
- Dilip
- Nathan Explosion
- YourSharona
- JoelR
- DawPi
- Live Games
- bernhara
- Kentraiyle Robinson
- IC Essentials
- Myr
- Chris Anderson
- Como
- Brian
- MichaelR
- Edward Ellas
- Square Wheels
- IPS THEME
- aXenDev
- PrettyPixels
- Analog
- Denis Dyack
- A Zayed
- Labis
- DursunKaptan
- V0RT3X
- MissB
- TheLlamaman
- Andy Y
- envy
- eivindsimensen
- JoeyM
- aLEX49566
- adik
- Codepixel
- alsl sndnxnx
- burnyourfeelings
- N700
- isvans
- Marius
- Matt
- terabyte
- Thomas Taschler
- Surpac
- JoshB
- Ioannis D
- abobader
- ReyDev
- Richard Arch
- bdmusic 24
- Majster87
- TomCat
- Paul
- Pmw
- Torgeir Rui
- Kammer et
- Nicolas PC
- XwReK
- Claudia999
- Kirill Gromov
- Synergy
- bing11
- Marvin Moore
- ArashDev
- onlyME
- ali hagi
- StevenM
- NewVicious
- lukash
- TracyIsland
- Andhrafriends Admin
- Daffy
- hyprem
- GuitarGathering
- Tripp
- Askancy
- MLK
- Jelly Belly
- eveneme eveneme
- Nomad
- Morphe
- lordi
- shahed
- John Horton
- PayMap
- Serval
- Nomer3
- Dennis Maidon
- Zennuie
- COSMIN
- wulfx01
- Matthew Hawley
- Verto
- George Anderssen
- Toby
- Cheryl