| dc.contributor.author | Gilani, Z | |
| dc.contributor.author | Farahbakhsh, R | |
| dc.contributor.author | TYSON, G | |
| dc.contributor.author | Crowcroft, J | |
| dc.date.accessioned | 2019-02-08T14:47:31Z | |
| dc.date.available | 2018-12-10 | |
| dc.date.available | 2019-02-08T14:47:31Z | |
| dc.date.issued | 2019 | |
| dc.identifier.issn | 1559-1131 | |
| dc.identifier.uri | https://qmro.qmul.ac.uk/xmlui/handle/123456789/55251 | |
| dc.description.abstract | Recent research has shown a substantial active presence of bots in online social networks (OSNs). In this
paper we perform a comparative analysis of the usage and impact of bots and humans on Twitter — one
of the largest OSNs in the world. We collect a large-scale Twitter dataset and define various metrics based
on tweet metadata. Using a human annotation task we assign ‘bot’ and ‘human’ ground-truth labels to the
dataset, and compare the annotations against an online bot detection tool for evaluation. We then ask a series
of questions to discern important behavioural characteristics of bots and humans using metrics within and
among four popularity groups. From the comparative analysis we draw clear differences and interesting
similarities between the two entities | en_US |
| dc.publisher | Association for Computing Machinery | en_US |
| dc.relation.ispartof | ACM Transactions on the Web | |
| dc.title | A Large Scale Behavioural Analysis of Bots and Humans on Twitter | en_US |
| dc.type | Article | en_US |
| dc.rights.holder | © 2019 Association for Computing Machinery | |
| pubs.notes | Not known | en_US |
| pubs.publication-status | Accepted | en_US |
| dcterms.dateAccepted | 2018-12-10 | |
| rioxxterms.funder | Default funder | en_US |
| rioxxterms.identifier.project | Default project | en_US |
