DeBot: Twitter Bot Detection via Warped Correlation

Chavoshi, Nikan, Hamooni, Hossein, Mueen, Abdullah·2016·2016 IEEE 16th International Conference on Data Mining (ICDM)

Cited by (260)

Items 101–200 of 260

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    Ross Schuchard, Andrew T. Crooks · 2021 · PLoS ONE
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    Fazil, Mohd, Abulaish, Muhammad · 2020 · Journal of Intelligent & Fuzzy Systems
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    Ross Schuchard, Andrew T. Crooks, Anthony Stefanidis, Arie Croitoru · 2019 · Humanities and Social Sciences Communications
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    William Williamson III, James W. Scrofani · 2019 · Hawaii International Conference on System Sciences (HICSS)
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  48. Detecting Malicious Twitter Bots Using Machine Learning
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  51. Anticipated versus Actual Effects of Platform Design Change: A Case Study of Twitter's Character Limit
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  52. CALEB: A Conditional Adversarial Learning Framework to enhance bot detection
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  53. Detecting Malicious Social Robots with Generative Adversarial Networks
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  54. Lexicon-Based Sentiment Analysis and Emotion Classification of Climate Change Related Tweets
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  56. Speaking like Humans, Spreading like Machines: A Study on Opinion Manipulation by Artificial-Intelligence-Generated Content Driving the Internet Water Army on Social Media
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  60. Beyond Interaction Patterns: Assessing Claims of Coordinated Inter-State Information Operations on Twitter/X
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