Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.11851/4039
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Torusdağ, Buğra M. | - |
dc.contributor.author | Kutlu, Mücahid | - |
dc.contributor.author | Selçuk, Ali Aydın | - |
dc.date.accessioned | 2021-01-25T11:28:55Z | |
dc.date.available | 2021-01-25T11:28:55Z | |
dc.date.issued | 2020-09 | |
dc.identifier.citation | Torusdağ, M. B., Kutlu, M., and Selçuk, A. A. (2020, September). Are We Secure from Bots? Investigating Vulnerabilities of Botometer. In 2020 5th International Conference on Computer Science and Engineering (UBMK) (pp. 343-348). IEEE. | en_US |
dc.identifier.isbn | 978-172817565-2 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/9219433 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.11851/4039 | - |
dc.description.abstract | Social media platforms such as Twitter provide an incredibly efficient way to communicate with people. While these platforms have many benefits, they can also be used for deceiving people, spreading misinformation, manipulation, and harassment. Social bots are usually employed for these kind of activities to artificially increase the amount of a particular post. To mitigate the effects of social bots, many bot detection systems are developed. However, the evaluation of these methods are challenging due to lack limited available datasets and the variety of bots people might develop. In this work, we investigate vulnerabilities of state-of-the-art Botometer social bot detection system by creating our own bot scenarios instead of using public datasets. In our experiments, we show that Botometer is not able to detect our social bots, showing that we need more enhanced bot detection models and test collections to better evaluate systems' performances. © 2020 IEEE. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
dc.relation.ispartof | 5th International Conference on Computer Science and Engineering | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | botometer | en_US |
dc.subject | machine learning | en_US |
dc.subject | social cyber security | en_US |
dc.subject | social media | en_US |
dc.subject | Twitter Bot Accounts | en_US |
dc.title | Are We Secure From Bots? Investigating Vulnerabilities of Botometer | en_US |
dc.type | Conference Object | en_US |
dc.department | Faculties, Faculty of Engineering, Department of Computer Engineering | en_US |
dc.department | Fakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü | tr_TR |
dc.identifier.startpage | 343 | |
dc.identifier.endpage | 348 | |
dc.authorid | 0000-0002-5660-4992 | - |
dc.authorid | 0000-0002-8963-1647 | - |
dc.identifier.wos | WOS:000629055500067 | en_US |
dc.identifier.scopus | 2-s2.0-85095689594 | en_US |
dc.institutionauthor | Kutlu, Mücahid | - |
dc.institutionauthor | Selçuk, Ali Aydın | - |
dc.identifier.doi | 10.1109/UBMK50275.2020.9219433 | - |
dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
item.openairetype | Conference Object | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
item.fulltext | No Fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.cerifentitytype | Publications | - |
crisitem.author.dept | 02.3. Department of Computer Engineering | - |
crisitem.author.dept | 02.3. Department of Computer Engineering | - |
Appears in Collections: | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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