Temporal Analysis of Reddit Networks via Role Embeddings

08/14/2019
by   Siobhan Grayson, et al.
0

Inspired by diachronic word analysis from the field of natural language processing, we propose an approach for uncovering temporal insights regarding user roles from social networks using graph embedding methods. Specifically, we apply the role embedding algorithm, struc2vec, to a collection of social networks exhibiting either "loyal" or "vagrant" characteristics derived from the popular online social news aggregation website Reddit. For each subreddit, we extract nine months of data and create network role embeddings on consecutive time windows. We are then able to compare and contrast how user roles change over time by aligning the resulting temporal embeddings spaces. In particular, we analyse temporal role embeddings from an individual and a community-level perspective for both loyal and vagrant communities present on Reddit.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/12/2019

Visualizing Trends of Key Roles in News Articles

There are tons of news articles generated every day reflecting the activ...
research
06/18/2020

A unified framework for equivalences in social networks

A key concern in network analysis is the study of social positions and r...
research
11/09/2016

Predicting User Roles in Social Networks using Transfer Learning with Feature Transformation

How can we recognise social roles of people, given a completely unlabell...
research
08/22/2019

From Community to Role-based Graph Embeddings

Roles are sets of structurally similar nodes that are more similar to no...
research
10/16/2019

Tutorial on NLP-Inspired Network Embedding

This tutorial covers a few recent papers in the field of network embeddi...
research
09/30/2021

Brand Attitude in Social Networks: The Role of eWoM

The aim of this study is to analyze the impact of electronic word-of-mou...
research
04/06/2023

BotTriNet: A Unified and Efficient Embedding for Social Bots Detection via Metric Learning

A persistently popular topic in online social networks is the rapid and ...

Please sign up or login with your details

Forgot password? Click here to reset