Results 61 to 70 of about 7,753,315 (190)
AN INVESTIGATION OF BOT ACCOUNT IDENTIFICATION ON TWITTER DATA
, 2021 Twitter bots are automated accounts which are programmed to perform certain tasks which resemble those of daily active users such as tweeting, liking a tweet or following.
Pasya, Nikitha
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DCGNN: Dual-Channel Graph Neural Network for Social Bot Detection
International Conference on Information and Knowledge Management, 2023 The importance of social bot detection has been increasingly recognized due to its profound impact on information dissemination. Existing methodologies can be categorized into feature engineering and deep learning-based methods, which mainly focus on ...
Nuoyan Lyu +3 more
semanticscholar +1 more source
Resultaten van het Rijkswaterstaat JAMP 2008 monitoringsprogramma van bot (Platichthys flesus L.). Biologische gegevens van bot en milieukritische stoffen in bot [PDF]
, 2009 De in dit rapport beschreven werkzaamheden zijn door Wageningen IMARES uitgevoerd op basis van een opdracht van Rijkswaterstaat in het kader van het Joint Assessment and Monitoring Program van de OSPARCOM.
Hoek-van Nieuwenhuizen, M., van +1 more
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Unmasking social bots: how confident are we?
EPJ Data ScienceSocial bots remain a major vector for spreading disinformation on social media and a menace to the public. Despite the progress made in developing multiple sophisticated social bot detection algorithms and tools, bot detection remains a challenging ...
James Giroux +3 more
doaj +1 more source
IEEE AccessSocial networking platforms like X (Twitter) serve as hubs for open human interaction, but they are also increasingly infiltrated by automated accounts masquerading as human users.
Danish Javed +5 more
doaj +1 more source
BotBR: Social Bot Detection with Balanced Feature Fusion and Reliability-Enhanced Graph Learning
Annual International ACM SIGIR Conference on Research and Development in Information RetrievalThe rise of social bots poses a significant threat to online platforms, making their detection an urgent priority. Recent advancements in Graph Neural Networks (GNNs) have significantly improved bot detection by leveraging the rich relational data within
Qilong Lin, Jingya Zhou
semanticscholar +1 more source
Real-Time Twitter Data Analysis: A Survey
UHD Journal of Science and Technology, 2022 Internet users are used to a steady stream of facts in the contemporary world. Numerous social media platforms, including Twitter, Facebook, and Quora, are plagued with spam accounts, posing a significant problem.
Hakar Mohammed Rasul, Alaa Khalil Jumaa
doaj +1 more source
BotCF: Improving the Social Bot Detection Performance By Focusing on the Community Features
IEEE Transactions on Network and Service ManagementVarious malicious activities performed by social bots have brought a crisis of trust to online social networks. Existing social bot detection methods often overlook the significance of community structure features and effective fusion strategies for ...
Feng Liu +6 more
semanticscholar +1 more source
Challenges in machine learning-based social bot detection: a systematic review
Discover Artificial IntelligenceThe rise of social digital network platforms has led to the widespread presence of social bots, automated entities that actively engage with users and content.
Nasser Alkathiri, Khaled Slhoub
semanticscholar +1 more source
Twitter Bot Detection Using Diverse Content Features and Applying Machine Learning Algorithms
Sustainability, 2023 A social bot is an intelligent computer program that acts like a human and carries out various activities in a social network. A Twitter bot is one of the most common forms of social bots. The detection of Twitter bots has become imperative to draw lines
F. Alarfaj +5 more
semanticscholar +1 more source