Measuring the impact of spammers on e-mail and Twitter networks

TL;DR

This study examines whether spammers significantly distort social network structures in Twitter and email data, finding minimal impact on core network metrics and providing insights into network robustness and analysis strategies.

Contribution

It offers a comparative analysis of network robustness after removing spammers and connected nodes, extending understanding of social network stability and metric reliability.

Findings

Spammers do not significantly alter network structure metrics.

Network robustness remains stable after removing spammers and extreme nodes.

Language analysis reveals insights when email content cannot be accessed.

Abstract

This paper investigates the research question if senders of large amounts of irrelevant or unsolicited information - commonly called "spammers" - distort the network structure of social networks. Two large social networks are analyzed, the first extracted from the Twitter discourse about a big telecommunication company, and the second obtained from three years of email communication of 200 managers working for a large multinational company. This work compares network robustness and the stability of centrality and interaction metrics, as well as the use of language, after removing spammers and the most and least connected nodes. The results show that spammers do not significantly alter the structure of the information-carrying network, for most of the social indicators. The authors additionally investigate the correlation between e-mail subject line and content by tracking language sentiment, emotionality, and complexity, addressing the cases where collecting email bodies is not permitted for privacy reasons. The findings extend the research about robustness and stability of social networks metrics, after the application of graph simplification strategies. The results have practical implication for network analysts and for those company managers who rely on network analytics (applied to company emails and social media data) to support their decision-making processes.