Increasing the Flow of Rumors in Social Networks by Spreading Groups

TL;DR

This paper proposes a method to enhance rumor dissemination in social networks by utilizing spreading groups, which can be automated, to initiate message flow and reach influential nodes efficiently.

Contribution

It introduces an information flow model and demonstrates its effectiveness using a dataset of Nasdaq-related tweets, highlighting a cost-effective way to accelerate message spread.

Findings

Spreading groups effectively increase rumor reach.

Automated bots can form spreading groups.

Model validated on Nasdaq tweet dataset.

Abstract

The paper addresses a method for spreading messages in social networks through an initial acceleration by Spreading Groups. These groups start the spread which eventually reaches a larger portion of the network. The use of spreading groups creates a final flow which resembles the spread through the nodes with the highest level of influence (opinion leaders). While harnessing opinion leaders to spread messages is generally costly, the formation of spreading groups is merely a technical issue, and can be done by computerized bots. The paper presents an information flow model and inspects the model through a dataset of Nasdaq-related tweets.