Lakshmi Babu Saheer
Biographic Data
| ID | 6624446 |
|---|---|
| NAME | Lakshmi Babu Saheer |
| GIVEN NAMES | Lakshmi Babu |
| FAMILY NAME | Saheer |
| SIGNATURE | SAHEER L B |
| AFFILIATIONS | Anglia Ruskin University |
| ORCID | 0000-0002-5263-596X |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 3 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Analyzing Radicalization Dynamics in the Language of Non-Violent Extremists Online in the UK (2016–2021)
Societal crises, such as COVID-19, produce societal instability and create a fertile ground for radicalization. Extremists exploit such crises by distributing disinformation to amplify uncertainty and distrust. Based on these developments, this study presents a longitudinal analysis across three different non-violent extremist ideologies in the UK (Islamist, far right and eco-radicals). As part of the study, public social media channels Twitter/X…
Mapping the Online Hard & Soft Recruitment Patterns of Nonviolent Extremists Online in the UK (2016-2021)
Speech Emotion Recognition Using Attention Model
Speech emotion recognition is an important research topic that can help to maintain and improve public health and contribute towards the ongoing progress of healthcare technology. There have been several advancements in the field of speech emotion recognition systems including the use of deep learning models and new acoustic and temporal features. This paper proposes a self-attention-based deep learning model that was created by combining a two-d…
No prominent works on this page.
Speech Emotion Recognition Using Attention Model
Speech emotion recognition is an important research topic that can help to maintain and improve public health and contribute towards the ongoing progress of healthcare technology. There have been several advancements in the field of speech emotion recognition systems including the use of deep learning models and new acoustic and temporal features. This paper proposes a self-attention-based deep learning model that was created by combining a two-d…
Analyzing Radicalization Dynamics in the Language of Non-Violent Extremists Online in the UK (2016–2021)
Societal crises, such as COVID-19, produce societal instability and create a fertile ground for radicalization. Extremists exploit such crises by distributing disinformation to amplify uncertainty and distrust. Based on these developments, this study presents a longitudinal analysis across three different non-violent extremist ideologies in the UK (Islamist, far right and eco-radicals). As part of the study, public social media channels Twitter/X…
Mapping the Online Hard & Soft Recruitment Patterns of Nonviolent Extremists Online in the UK (2016-2021)
Computer Science (2 works) · Psychology (2 works) · Terrorism, Counterterrorism, and Political Violence (2 works) · Agency (philosophy (1 work) · Anger (1 work) · Artificial Intelligence (1 work) · Computer security (1 work) · Context (archaeology (1 work) · Convolutional neural network (1 work) · Criminology (1 work)