2018/09/24 by A. Fronzetti Colladon, Andrea Fronzetti Colladon, Peter A. Gloor +1 · 2 voices · 1 citation
Computer Science · Physics and Astronomy · #Complex Network Analysis Techniques #Opinion Dynamics and Social Influence #Spam and Phishing Detection #cs.CL #cs.IR #cs.SI
paper · pdf · doi:10.1016/j.ijinfomgt.2018.09.009
published as International Journal of Information Management 48, 254-262 (2019)
openalex publication_date 2018/09/24 · crossref created 2018/09/24 · crossref issued 2019/10/01 · crossref published 2019/10/01 · crossref published-print 2019/10/01 · arxiv created 2021/05/21 · arxiv published 2021/05/21 · arxiv updated 2021/05/24 · crossref deposited 2022/09/02 · openalex created_date 2025/10/10 · crossref indexed 2025/11/20 · openalex updated_date 2026/07/28
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.