Abstract
In the wake of fresh allegations that personality data from Facebook users have been illegally used to influence the outcome of the US general election and the Brexit vote, the debate over manipulation of social big data is gaining further momentum. This chapter addresses the social data privacy and data integrity vulnerabilities threatening the future of applications based on anticipatory computing paradigms. We investigate the organic reach phenomenon on social networks known to be responsible for propagation of ‘fake’ social content, undermining social media data integrity. We describe experimental work demonstrating that the trustworthiness of a message originator and low levels of the personality trait Agreeableness in the message receiver may increase the organic reach of ‘fake’ content on social networks. These effects may have implications for policy and practise, particularly in relevance to the threat of social data manipulation for anticipatory computing applications.
Original language | English |
---|---|
Title of host publication | Cyber Influence and Cognitive Threats |
Editors | V. Benson, J. Mcalaney |
Publisher | Elsevier |
Pages | 145-158 |
Number of pages | 14 |
ISBN (Electronic) | 9780128192047 |
ISBN (Print) | 9780128192054 |
DOIs | |
Publication status | Published - 2020 |
Bibliographical note
Imprint: Academic Press.Keywords
- Anticipatory computing
- Big data analytics
- Cybersecurity
- Data integrity
- Organic reach
- Risk
- Social networks
- Trust