Is bigger always better? Potential biases of big data derived from social network sites
E Hargittai - The ANNALS of the American Academy of …, 2015 - journals.sagepub.com
This article discusses methodological challenges of using big data that rely on specific sites
and services as their sampling frames, focusing on social network sites in particular. It draws …
and services as their sampling frames, focusing on social network sites in particular. It draws …
Escape: Efficiently counting all 5-vertex subgraphs
A Pinar, C Seshadhri, V Vishal - … of the 26th international conference on …, 2017 - dl.acm.org
Counting the frequency of small subgraphs is a fundamental technique in network analysis
across various domains, most notably in bioinformatics and social networks. The special …
across various domains, most notably in bioinformatics and social networks. The special …
Path sampling: A fast and provable method for estimating 4-vertex subgraph counts
Counting the frequency of small subgraphs is a fundamental technique in network analysis
across various domains, most notably in bioinformatics and social networks. The special …
across various domains, most notably in bioinformatics and social networks. The special …
Approximately counting triangles in sublinear time
We consider the problem of estimating the number of triangles in a graph. This problem has
been extensively studied in both theory and practice, but all existing algorithms read the …
been extensively studied in both theory and practice, but all existing algorithms read the …
A space efficient streaming algorithm for triangle counting using the birthday paradox
We design a space efficient algorithm that approximates the transitivity (global clustering
coefficient) and total triangle count with only a single pass through a graph given as a …
coefficient) and total triangle count with only a single pass through a graph given as a …
Triadic measures on graphs: The power of wedge sampling
Graphs are used to model interactions in a variety of contexts, and there is a growing need
to quickly assess the structure of a graph. Some of the most useful graph metrics, especially …
to quickly assess the structure of a graph. Some of the most useful graph metrics, especially …
A fast and provable method for estimating clique counts using turán's theorem
S Jain, C Seshadhri - Proceedings of the 26th international conference …, 2017 - dl.acm.org
Clique counts reveal important properties about the structure of massive graphs, especially
social networks. The simple setting of just 3-cliques (triangles) has received much attention …
social networks. The simple setting of just 3-cliques (triangles) has received much attention …
Better algorithms for counting triangles in data streams
A McGregor, S Vorotnikova, HT Vu - … of the 35th ACM SIGMOD-SIGACT …, 2016 - dl.acm.org
We present space-efficient data stream algorithms for approximating the number of triangles
in a graph up to a factor 1+ ε. While it can be shown that determining whether a graph is …
in a graph up to a factor 1+ ε. While it can be shown that determining whether a graph is …
On approximating the number of k-cliques in sublinear time
T Eden, D Ron, C Seshadhri - Proceedings of the 50th annual ACM …, 2018 - dl.acm.org
We study the problem of approximating the number of k-cliques in a graph when given query
access to the graph. We consider the standard query model for general graphs via (1) …
access to the graph. We consider the standard query model for general graphs via (1) …
Listing triangles
We present new algorithms for listing triangles in dense and sparse graphs. The running
time of our algorithm for dense graphs is ̃\mathcalO(n^ω+n^3(ω-1)/(5-ω)t^2(3-ω)/(5-ω)), and …
time of our algorithm for dense graphs is ̃\mathcalO(n^ω+n^3(ω-1)/(5-ω)t^2(3-ω)/(5-ω)), and …