• Corpus ID: 8475051

Social Networking by Proxy: A Case Study of Catster, Dogster and Hamsterster

@article{Dnker2015SocialNB,
  title={Social Networking by Proxy: A Case Study of Catster, Dogster and Hamsterster},
  author={Daniel D{\"u}nker and J{\'e}r{\^o}me Kunegis},
  journal={ArXiv},
  year={2015},
  volume={abs/1501.04527}
}
The proliferation of online social networks in the last decadehas not stopped short of pets, and many di erent onlineplatforms now exist catering to owners of various pets suchas cats and dogs. These online pet social networks providea unique opportunity to study an online social network inwhich a single user manages multiple user pro les, i.e. onefor each pet they own. These types of multi-pro le net-works allow us to investigate two questions: (1) What isthe relationship between the pet-level… 

Figures and Tables from this paper

A New Generative Statistical Model for Graphs: The Latent Order Logistic (LOLOG) Model

TLDR
A new family of probability models motivated by the idea of network growth, which is called the Latent Order Logistic (LOLOG) model, is proposed, a fully general framework capable of describing any probability distribution over graph configurations, though not all distributions are easily expressible or estimable as a LOLOG.

References

SHOWING 1-10 OF 32 REFERENCES

On the internet, everybody knows you're a dog: the human-pet relationship in online social networks

  • J. Golbeck
  • Computer Science
    CHI Extended Abstracts
  • 2009
TLDR
This work presents several results on the difference in behavior between dog and cat owners in pet-oriented social networks, and extends this analysis to divisions between urban and rural users.

Using Friendship Ties and Family Circles for Link Prediction

TLDR
It is shown that when there are tightly-knit family circles in a social network, the accuracy of link prediction models can be improved, by making use of the family circle features based on the likely structural equivalence of family members.

Learning to Discover Social Circles in Ego Networks

TLDR
A novel machine learning task of identifying users' social circles is defined as a node clustering problem on a user's ego-network, a network of connections between her friends, and a model for detecting circles is developed that combines network structure as well as user profile information.

Learning to Discover Social Circles in Ego Networks

TLDR
A novel machine learning task of identifying users’ social circles is defined as a node clustering problem on a user’s ego-network, a network of connections between her friends, and a model for detecting circles is developed that combines network structure as well as user profile information.

Fairness on the web: alternatives to the power law

TLDR
Several measures of fairness and inequality based on the degree distribution in networks are presented, as alternatives to the well-established power-law exponent and the Lorenz curve, and on the information-theoretical concept of entropy are proposed.

A Case Study of Sockpuppet Detection in Wikipedia

TLDR
This paper presents preliminary results of using authorship attribution methods for the detection of sockpuppeteering in Wikipedia, and shows that this approach is promising and that it can be a viable alternative to the current human process that Wikipedia uses to resolve suspected sockpuppet cases.

Network growth and the spectral evolution model

TLDR
A link prediction algorithm based on the extrapolation of a network's spectral evolution, which shows that it performs particularly well for networks with irregular, but spectral, growth patterns.

Sockpuppet Detection in Wikipedia: A Corpus of Real-World Deceptive Writing for Linking Identities

TLDR
This paper used a semi-automated method for crawling and curating a dataset of real sockpuppet investigation cases from Wikipedia, which is the first corpus available on real-world deceptive writing.

Learning spectral graph transformations for link prediction

TLDR
This work presents a unified framework for learning link prediction and edge weight prediction functions in large networks, based on the transformation of a graph's algebraic spectrum, by reducing the problem to a one-dimensional regression problem whose runtime only depends on the method's reduced rank and that can be inspected visually.

The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations

TLDR
A small, closed population of bottlenose dolphins living at the southern extreme of the species' range is described, which hypothesise that ecological constraints are important factors shaping social interactions within cetacean societies.