2021 ◽  
Author(s):  
Cian Ryan ◽  
Brian O’Sullivan ◽  
Amr Elrasad ◽  
Aisling Cahill ◽  
Joe Lemley ◽  
...  

2021 ◽  
Author(s):  
Yasith Jayawardana ◽  
Gavindya Jayawardena ◽  
Andrew T. Duchowski ◽  
Sampath Jayarathna

Author(s):  
Mohammad Norouzifard ◽  
Joanna Black ◽  
Benjamin Thompson ◽  
Reinhard Klette ◽  
Jason Turuwhenua

2020 ◽  
Vol 26 (4) ◽  
pp. 496-507
Author(s):  
Kheir Daouadi ◽  
Rim Rebaï ◽  
Ikram Amous

Nowadays, bot detection from Twitter attracts the attention of several researchers around the world. Different bot detection approaches have been proposed as a result of these research efforts. Four of the main challenges faced in this context are the diversity of types of content propagated throughout Twitter, the problem inherent to the text, the lack of sufficient labeled datasets and the fact that the current bot detection approaches are not sufficient to detect bot activities accurately. We propose, Twitterbot+, a bot detection system that leveraged a minimal number of language-independent features extracted from one single tweet with temporal enrichment of a previously labeled datasets. We conducted experiments on three benchmark datasets with standard evaluation scenarios, and the achieved results demonstrate the efficiency of Twitterbot+ against the state-of-the-art. This yielded a promising accuracy results (>95%). Our proposition is suitable for accurate and real-time use in a Twitter data collection step as an initial filtering technique to improve the quality of research data.


Author(s):  
F. W. Albalas ◽  
B. A. Abu-Alhaija ◽  
A. Awajan ◽  
A. Awajan ◽  
Khalid Al-Begain

New web technologies have encouraged the deployment of various network applications that are rich with multimedia and real-time services. These services demand stringent requirements are defined through Quality of Service (QoS) parameters such as delay, jitter, loss, etc. To guarantee the delivery of these services QoS routing algorithms that deal with multiple metrics are needed. Unfortunately, QoS routing with multiple metrics is considered an NP-complete problem that cannot be solved by a simple algorithm. This paper proposes three source based QoS routing algorithms that find the optimal path from the service provider to the user that best satisfies the QoS requirements for a particular service. The three algorithms use the same filtering technique to prune all the paths that do not meet the requirements which solves the complexity of NP-complete problem. Next, each of the three algorithms integrates a different Multiple Criteria Decision Making method to select one of the paths that have resulted from the route filtering technique. The three decision making methods used are the Analytic Hierarchy Process (AHP), Multi-Attribute Utility Theory (MAUT), and Kepner-Tregoe KT. Results show that the algorithms find a path using multiple constraints with a high ability to handle multimedia and real-time applications.


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