Difference between revisions of "Project:Dating Privacy"

From Wikibase Personal data
Jump to navigation Jump to search
Line 6: Line 6:
 
Meetings online at https://epfl.meet.switch.ch/dating-data<br>
 
Meetings online at https://epfl.meet.switch.ch/dating-data<br>
 
Every first Wednesday of the month at 20h15<br>
 
Every first Wednesday of the month at 20h15<br>
 +
Meeting Notes https://docs.google.com/document/d/1Co_ccRQf1tidcZpO2MVcvWCVnvaR0fCEEW2IPLpZ-q4/edit?usp=drivesdk<br>
 +
Drive  https://drive.google.com/drive/folders/1UvDaW8ZN0LeKMPRCCuiNTDkV6QLx8tq8<br>
 +
  
 
==Objectives==
 
==Objectives==

Revision as of 09:58, 5 February 2021

Description

"Dating Data" is a collective contributing to take control of personal data and to data literacy in a secured and ethical manner for end users and research purposes.

It is comprised of members coming from different countries, disciplines (mathematics, sociology, journalism, law, physics) and foreparts (academia, private, independent, citizen NGO).

Meetings online at https://epfl.meet.switch.ch/dating-data
Every first Wednesday of the month at 20h15
Meeting Notes https://docs.google.com/document/d/1Co_ccRQf1tidcZpO2MVcvWCVnvaR0fCEEW2IPLpZ-q4/edit?usp=drivesdk
Drive https://drive.google.com/drive/folders/1UvDaW8ZN0LeKMPRCCuiNTDkV6QLx8tq8


Objectives

  1. Implement tools that allow users to request and analyse their data
  2. Find and ask for SAR with a concrete example and cooperate with communities in order to 1 increase the impact 2 relay the info
  3. Enrich the wiki with data structures extracted from the SARs
  4. Develop methodologies that allow for research without dependency on commercial platforms
  5. Formalize the working group and project with an official legal entity

Problematic Proposals

  1. Sharing personal data with third parties which is not necessary for the app functioning. The Grindr case study. Check third-parties that are the biggest players
  2. Sexual harassment
  3. Scams, phishing, fake profiles
  4. Users are affected by malicious behaviours 1 and 2 so how are dating apps moderating this and protecting users via the analysis of their personal data?
  5. Between 10-20% of users find a partner in France, Switzerland and United States. Do users really get the outcomes they want from the app in exchange for providing their data?
  6. Subscription rates changing according to user demographic characteristics (ex. Tinder)

More info in this doc https://tinyurl.com/goaldatingdata

Participants

Pidoux
Podehaye
Genferei
Frandrews
HermineL

TO DO / On going

Map the ecosystem
How many apps are available? Maybe be restricted to Europe.

  1. Digital methods project "Mapping data ecologies of the dating industry" https://docs.google.com/presentation/d/1n-p_efBmkK2v1KGCbHyHb_csmR6D7KN8SX3qron9Cn4/edit
  1. Tools to sample how many apps are in the Google and Play stores:

"Google Play Store Scraper" is a simple tool to extract the details of individual apps, collect their related apps, retrieve app permissions, and retrieve a list of apps for a given keyword.
"iTunes App Store Scraper"
https://wiki.digitalmethods.net/Dmi/ToolDatabase

Permissions per app via Exodus
List apps per ranking, add ranking to every app following the table in the google doc
Archive Privacy policies
Add link to privacy policy
Defining the project scope

Dating apps' list

  • Wiki

-->list of dating apps available on this wiki

-->list of dating apps available on wikidata

List of apps per downloads

Privacy Policies

links can be found in the wiki

maybe this is useful: Princeton-Leuven Longitudinal Corpus of Privacy Policies. Front-end here: https://privacypolicies.cs.princeton.edu/ghfront/ and the repository here: https://github.com/citp/privacy-policy-historical

Partners/third parties

“Out Of Control” – A Review Of Data Sharing By Popular Mobile Apps published in January 2020
see Technical report https://fil.forbrukerradet.no/wp-content/uploads/2020/01/mnemonic-security-test-report-v1.0.pdf
report https://fil.forbrukerradet.no/wp-content/uploads/2020/01/2020-01-14-out-of-control-final-version.pdf
Complaint letters https://www.forbrukerradet.no/side/complaints-against-grindr-and-five-third-party-companies/


LUMAscape https://www.okanjo.com/blog/2016/12/14/ssp-dsp-dmp-rtb-wtf

Patents

List of Match Group patents: https://policies.tinder.com/intellectual-property/intl/en
Tinder Patents: 

  number={US20160154569 A1},
  author = {Rad, Sean and
            Carrico, Todd M. and
            Hoskins, Kenneth B and
            Stone, James C.},
  url = {https://worldwide.espacenet.com/publicationDetails/biblio?II=0&ND=3&adjacent=true&locale=en_EP&FT=D&date=20160602&CC=US&NR=2016154569A1&KC=A1#}, 
  title = {Matching Process System And Method}, 

  number={US9733811B2},
  author = {Carrico, Todd M. and
            Hoskins, Kenneth B and
            Rad, Sean and
            Stone, James C. and
            Badeen, Jonathan},
  url = {https://worldwide.espacenet.com/patent/search/family/050234419/publication/US10203854B2?q=pn\%3DUS10203854B2}, 
  title = {Matching Process System And Method},

Match Group
SYSTEM AND METHOD FOR USER COMMUNICATION IN A NETWORK 
https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2020137019A1&KC=A1&FT=D&DB=en.worldwide.espacenet.com&locale=en_EP&date=20200430&rss=true#

Hinge: Brevet publié en 2013 puis abandonné, jamais délivré. https://worldwide.espacenet.com/publicationDetails/biblio?CC=US&NR=2013066972A1&KC=A1&FT=D&ND=3&date=20130314&DB=EPODOC&locale=en_EP#

Facebook Dating: https://worldwide.espacenet.com/searchResults?submitted=true&locale=en_EP&DB=en.worldwide.espacenet.com&ST=advanced&EXTFTXT=%22dating+service%22&PN=&AP=&PR=&PD=&PA=facebook&IN=sharp&CPC=&IC=

Media

Legal

Tinder Annual report: Tinder on-going accusations. The Irish DPC case, also prices can vary according to users' age https://s22.q4cdn.com/279430125/files/doc_financials/2019/ar/Match-Group-2019-Annual-Report.pdf
My GDPR Complaint Against Tinder https://forum.personaldata.io/t/my-gdpr-complaint-against-tinder/70
Data Protection Commission launches Statutory Inquiry into MTCH Technology Services Limited (Tinder) https://www.dataprotection.ie/en/news-media/latest-news/data-protection-commission-launches-statutory-inquiry-mtch-technology

Data leaks/scandals

Ashley Madison
Ashley Madison Leak No Big Deal? Think Again https://www.makeuseof.com/tag/priority-ashley-madison-leak-no-big-deal-think/
Les résultats de Grindr révélés grâce au scandale Ashley Madison "Grindr a eu des revenus résultant à la fois des abonnements et de la publicité de près de 16 millions de dollars en 2012" https://www.fugues.com/243577-article-les-resultats-de-grindr-reveles-grace-au-scandale-ashley-madison.html

OkCupid:
Here is a mirror for the OKCupid OSF Emil Kirkegaard dataset https://www.reddit.com/r/datasets/comments/4jj53i/here_is_a_mirror_for_the_okcupid_osf_emil/
Researchers Caused an Uproar By Publishing Data From 70,000 OkCupid Users https://fortune.com/2016/05/18/okcupid-data-research/
Controversy over OKCupid keynote at CHI 2018 https://www.reddit.com/r/sciences/comments/8edxm3/controversy_over_okcupid_keynote_at_chi_2018/

Grindr:
Données privées : le site de rencontres Grindr mis en cause https://www.lemonde.fr/pixels/article/2018/04/03/donnees-privees-le-site-de-rencontres-grindr-mis-en-cause_5279794_4408996.html

Lovoo
LOVOO’s CEO Benjamin Bak resigns https://inside.lovoo.com/en/lovoos-ceo-benjamin-bak-resigns-2/

happn
En détournant l’app Happn, un hacker peut tracer votre chemin en temps réel https://cyberguerre.numerama.com/5827-en-detournant-lapp-happn-un-hacker-peut-tracer-votre-chemin-en-temps-reel.html

References with databases

Rosenfeld, Michael J., Reuben J. Thomas, and Sonia Hausen. 2019 How Couples Meet and Stay Together 2017 fresh sample. [Computer files]. Stanford, CA: Stanford University Libraries.
The OKCupid dataset: A very large public dataset of dating site users https://www.researchgate.net/project/The-OKCupid-dataset-A-very-large-public-dataset-of-dating-site-users
- Full paper: https://web.archive.org/web/20200728135539/https://openpsych.net/files/papers/Kirkegaard_2016g.pdf

Surveys

Tinder usage statistics: https://www.businessofapps.com/data/tinder-statistics/\#2
Pew Research Center (Feb 2020): The Virtues and Downsides of Online Dating. Retrieved from https://www.pewresearch.org/internet/2020/02/06/the-virtues-and-downsides-of-online-dating/
Swiss Federal Statistical Office (Nov 2019): Families and Generations Survey. Retrieved from https://www.bfs.admin.ch/bfs/fr/home/statistiques/population/enquetes/efg.assetdetail.10467789.html
INED France (2016) https://www.ined.fr/fr/publications/editions/population-et-societes/sites-rencontres-qui-y-trouve-son-conjoint/

Technical references

An Evidence‐based Forensic Taxonomy of Windows Phone Dating Apps https://onlinelibrary.wiley.com/doi/full/10.1111/1556-4029.13820
Privacy Risks in Mobile Dating Apps https://arxiv.org/abs/1505.02906
Technical report by mnemonic with the Norwegian consummer assoc showing data trading and GDPR compliance coded: https://fil.forbrukerradet.no/wp-content/uploads/2020/01/mnemonic-security-test-report-v1.0.pdf
Tinder engineering blog: https://medium.com/tinder-engineering/
TinVec explanation by Tinder's lead engineer: https://youtu.be/j2rfLFYYdfM
Happn by exodus: https://reports.exodus-privacy.eu.org/en/reports/com.ftw_and_co.happn/latest/
OkCupid engineering website: Evaluating Perceptual Image Hashes at OkCupid https://tech.okcupid.com/evaluating-perceptual-image-hashes-okcupid/
How OkCupid organizes its multi-page React app https://tech.okcupid.com/how-okcupid-organizes-its-multi-page-react-app/
Lovoo engineering: dotGo 2016: Go machine learning at large scale https://lovoodotblog.wordpress.com/2016/11/01/dotgo-2016-go-machine-learning-at-large-scale/
Lovoo github: https://github.com/lovoo
bbuzz 17: Anti-Spam and Machine learning at LOVOO https://lovoodotblog.wordpress.com/2017/06/16/bbuzz-17-anti-spam-and-machine-learning-at-lovoo/


List of apps with SAR

App Female Male Country
Adopteunmec 1 0 CH
Badoo 1 0 CH
Bumble 1 0 CH
happn 1 0 CH
HER 1 0 CH
Once 1 0 CH
Parship 1 0 CH
PlanetRomeo 0 1 CH
Scruff 0 1 CH
Tinder 1 1 CH
Retrieved from "https://wiki.personaldata.io/w/index.php?title=Project:Dating_Privacy&oldid=91886"