Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Social and Information Networks

arXiv:1605.05166 (cs)
[Submitted on 17 May 2016]

Title:Digital Stylometry: Linking Profiles Across Social Networks

Authors:Soroush Vosoughi, Helen Zhou, Deb Roy
View PDF
Abstract:There is an ever growing number of users with accounts on multiple social media and networking sites. Consequently, there is increasing interest in matching user accounts and profiles across different social networks in order to create aggregate profiles of users. In this paper, we present models for Digital Stylometry, which is a method for matching users through stylometry inspired techniques. We experimented with linguistic, temporal, and combined temporal-linguistic models for matching user accounts, using standard and novel techniques. Using publicly available data, our best model, a combined temporal-linguistic one, was able to correctly match the accounts of 31% of 5,612 distinct users across Twitter and Facebook.
Comments: SocInfo'15, Beijing, China. In proceedings of the 7th International Conference on Social Informatics (SocInfo 2015). Beijing, China
Subjects: Social and Information Networks (cs.SI); Artificial Intelligence (cs.AI); Computation and Language (cs.CL); Information Retrieval (cs.IR)
Cite as: arXiv:1605.05166 [cs.SI]
  (or arXiv:1605.05166v1 [cs.SI] for this version)
  https://doi.org/10.48550/arXiv.1605.05166

Submission history

From: Soroush Vosoughi Dr [view email]
[v1] Tue, 17 May 2016 13:47:24 UTC (132 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.SI
< prev   |   next >
new | recent | 2016-05
Change to browse by:
cs
cs.AI
cs.CL
cs.IR

References & Citations

DBLP - CS Bibliography

listing | bibtex
Soroush Vosoughi
Helen Zhou
Deb Roy
export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)