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

Kanagavalli, N. and BaghavathiPriya, S. and Ilavarasan, S. (2021) Identification of Deception Detection on Social Media (Twitter) Data Sets using Naive Base Classification and RVNN Model. In: I3CAC 2021, 7-8 June 2021, Bharath University, Chennai, India.

[img]
Preview
Text (PDF)
eai.7-6-2021.2308570.pdf - Published Version

Download (370kB) | Preview

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.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: rumor social media cnn model rvnn model twitter data set
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
Depositing User: EAI Editor IV
Date Deposited: 11 Jun 2021 08:07
Last Modified: 11 Jun 2021 08:07
URI: https://eprints.eudl.eu/id/eprint/3951

Actions (login required)

View Item View Item