Identification of Deception Detection on Social Media (Twitter) Data Sets using Naive Base Classification and RVNN Model

N. Kanagavalli; S. BaghavathiPriya; S. Ilavarasan

Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India

Research Article

Identification of Deception Detection on Social Media (Twitter) Data Sets using Naive Base Classification and RVNN Model

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@INPROCEEDINGS{10.4108/eai.7-6-2021.2308570,
    author={N.  Kanagavalli and S.  BaghavathiPriya and S.  Ilavarasan},
    title={Identification of Deception Detection on Social Media (Twitter) Data Sets using Naive Base Classification and RVNN Model},
    proceedings={Proceedings of the First International Conference on Computing, Communication and Control System, I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India},
    publisher={EAI},
    proceedings_a={I3CAC},
    year={2021},
    month={6},
    keywords={rumor social media cnn model rvnn model twitter data set},
    doi={10.4108/eai.7-6-2021.2308570}
}

N. Kanagavalli
S. BaghavathiPriya
S. Ilavarasan
Year: 2021
Identification of Deception Detection on Social Media (Twitter) Data Sets using Naive Base Classification and RVNN Model
I3CAC
EAI
DOI: 10.4108/eai.7-6-2021.2308570

N. Kanagavalli¹^,*, S. BaghavathiPriya², S. Ilavarasan³

1: Assistant Professor, Department of CSE, Rajalakshmi Institute of Technology, Chennai
2: Professor, Department of CSE, Rajalakshmi Engineering College, Chennai
3: Assistant Professor (SG), Department of IT, Saveetha Engineering College, Chennai

*Contact email: kvalli.818@gmail.com

Abstract

Twitter being a famous social media site not only helps people to share their thoughts in microblogs but also plays a pivotal role in situations of emergency for communication, announcement and so on. However, it results in anaversive effect when inappropriate tweet is reposted or shared to people thereby spreading rumors. This work describesthe methodologies in identifying the rumors using specific attributes like precision, fi-score, recall and support thereby solving the ranging rumor issues across the social media platform. A system detects candidate’s rumor from twitter and then evaluates it applicably. The result of experiment shows the proposed algorithm in order to detect the rumors with acceptable accuracy.

Keywords: rumor social media cnn model rvnn model twitter data set

Published: 2021-06-04
Publisher: EAI

: http://dx.doi.org/10.4108/eai.7-6-2021.2308570