Greeshma Lingam
Biographic Data
| ID | 10055516 |
|---|---|
| NAME | Greeshma Lingam |
| GIVEN NAMES | Greeshma |
| FAMILY NAME | Lingam |
| SIGNATURE | LINGAM G |
| AFFILIATIONS | National Institute of Technology Warangal |
| ORCID | 0009-0003-1039-6491 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 2 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2020 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Fuzzy-Based Deep Reinforcement Learning for Suicidal Ideation Detection in Online Social Networks
Suicidal ideation is a major psychological problem, and preventing this social risk is recognized as an important research topic. In reality, there can be several reasons why a person experiences suicidal ideation. Each individual can express views, emotions, and several types of symptoms related to suicidal ideation on the most popular social media platforms. In online social networks (OSNs), identification of suicidal ideation is one of the maj…
Detection of Malicious Social Bots Using Learning Automata With URL Features in Twitter Network
Malicious social bots generate fake tweets and automate their social relationships either by pretending like a follower or by creating multiple fake accounts with malicious activities. Moreover, malicious social bots post shortened malicious URLs in the tweet in order to redirect the requests of online social networking participants to some malicious servers. Hence, distinguishing malicious social bots from legitimate users is one of the most imp…
No prominent works on this page.
Detection of Malicious Social Bots Using Learning Automata With URL Features in Twitter Network
Malicious social bots generate fake tweets and automate their social relationships either by pretending like a follower or by creating multiple fake accounts with malicious activities. Moreover, malicious social bots post shortened malicious URLs in the tweet in order to redirect the requests of online social networking participants to some malicious servers. Hence, distinguishing malicious social bots from legitimate users is one of the most imp…
Fuzzy-Based Deep Reinforcement Learning for Suicidal Ideation Detection in Online Social Networks
Suicidal ideation is a major psychological problem, and preventing this social risk is recognized as an important research topic. In reality, there can be several reasons why a person experiences suicidal ideation. Each individual can express views, emotions, and several types of symptoms related to suicidal ideation on the most popular social media platforms. In online social networks (OSNs), identification of suicidal ideation is one of the maj…
Social media (2 works) · Botnet (1 work) · Computer Science (1 work) · Computer security (1 work) · Digital Mental Health Interventions (1 work) · Emotion and Mood Recognition (1 work) · Internet Traffic Analysis and Secure E-voting (1 work) · Mental Health via Writing (1 work) · Network Security and Intrusion Detection (1 work) · Poison control (1 work)