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Conversational Artificial Intelligence
book

Conversational Artificial Intelligence

by Romil Rawat, Rajesh Kumar Chakrawarti, Sanjaya Kumar Sarangi, Anand Rajavat, Mary Sowjanya Alamanda, Kotagiri Srividya, K. Sakthidasan Sankaran
March 2024
Intermediate to advanced content levelIntermediate to advanced
800 pages
28h 48m
English
Wiley-Scrivener
Content preview from Conversational Artificial Intelligence

5Extracting and Analyzing Factors to Identify the Malicious Conversational AI Bots on Twitter

Gitika Vyas1*, Piyush Vyas1, Prathamesh Muzumdar2, Anitha Chennamaneni1, Anand Rajavat3 and Romil Rawat4

1Computer Information Systems, Texas A&M University-Central Texas, Killeen, Texas, USA

2University of South Florida, Florida, USA

3Department of Computer Science Engineering, Director, Shri Vaishnav Institute of Information Technology, Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India

4Department of Computer Science, Shri Vaishnav Vidyapeeth Vishwavidyalaya, Indore, India

Abstract

On social media, many third-party vendors utilize Conversational Artificial Intelligence (CAI) to use social bots to spread marketing campaigns and to increase followers, thereby opening the door for malicious bots to compromise the security on social media, especially on Twitter where the posts are concise, making it hard to distinguish between human written posts and bot-generated tweets. Thus, such malicious bots on Twitter can break into user accounts, spread misinformation, breach account data, and market advertising spam. Hence, this chapter aims to conduct a detailed exploratory study to identify the crucial Twitter account features that help to detect malicious bots. Machine learning-based techniques such as information gain, correlation, and chi-square feature selections are used in this chapter to select the top feature set by comparing all three techniques. Twitter account data provided ...

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Publisher Resources

ISBN: 9781394200566Purchase Link