Akshi Kumar
Biographic Data
| ID | 3925016 |
|---|---|
| NAME | Akshi Kumar |
| GIVEN NAMES | Akshi |
| FAMILY NAME | Kumar |
| SIGNATURE | KUMAR A |
| AFFILIATIONS | Goldsmiths University of London |
| ORCID | 0000-0003-4263-7168 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
DynaMentA
Mental health classification is inherently challenging, requiring models to capture complex emotional and linguistic patterns. Although large language models (LLMs) such as ChatGPT, Mental-Alpaca, and MentaLLaMA show promise, they are not trained on clinically grounded data and often overlook subtle psychological cues. Their predictions tend to overemphasize emotional intensity, while failing to capture contextually relevant indicators that are c…
Natural language processing as Digital Veda (डिजिटल वेद)
This article conceptualizes Natural Language Processing (NLP) as the Digital Veda (डिजिटल वेद), framing it as a culturally rooted communicative infrastructure inspired by the Vedic tradition of structured knowledge preservation and ethical discourse. Drawing on India’s linguistic and philosophical heritage, it positions NLP not as a neutral tool, but as an evolving ecosystem shaped by human values, language ideologies, and socio-cultural narrativ…
OptNet-Fake
Exposure to half-truths or lies has the potential to undermine democracies, polarize public opinion, and promote violent extremism. Identifying the veracity of fake news is a challenging task in distributed and disparate cyber-socio platforms. To enhance the trustworthiness of news on these platforms, in this article, we put forward a fake news detection model, OptNet-Fake. The proposed model is architecturally a hybrid that uses a meta-heuristic…
TLP-Negcn
Temporal link prediction (TLP) is a prominent problem in network analysis that focuses on predicting the existence of future connections or relationships between entities in a dynamic network over time. The predictive capabilities of existing models of TLP are often constrained due to their difficulty in adapting to the changes in dynamic network structures over time. In this article, an improved TLP model, denoted as TLP-NEGCN, is introduced by …
EmoMBTI-Net
Emojis, integral to digital communication, often encapsulate complex emotional layers that enhance text beyond mere words. This research leverages the expressive power of emojis to predict Myers-Briggs Type Indicator (MBTI) personalities, diverging from conventional text-based approaches. We developed a unique dataset, EmoMBTI, by mapping emojis to specific MBTI traits using diverse posts scraped from Reddit. This dataset enabled the integration …
Social, mobile, analytic and cloud technologies
No prominent works on this page.
Social, mobile, analytic and cloud technologies
OptNet-Fake
Exposure to half-truths or lies has the potential to undermine democracies, polarize public opinion, and promote violent extremism. Identifying the veracity of fake news is a challenging task in distributed and disparate cyber-socio platforms. To enhance the trustworthiness of news on these platforms, in this article, we put forward a fake news detection model, OptNet-Fake. The proposed model is architecturally a hybrid that uses a meta-heuristic…
TLP-Negcn
Temporal link prediction (TLP) is a prominent problem in network analysis that focuses on predicting the existence of future connections or relationships between entities in a dynamic network over time. The predictive capabilities of existing models of TLP are often constrained due to their difficulty in adapting to the changes in dynamic network structures over time. In this article, an improved TLP model, denoted as TLP-NEGCN, is introduced by …
EmoMBTI-Net
Emojis, integral to digital communication, often encapsulate complex emotional layers that enhance text beyond mere words. This research leverages the expressive power of emojis to predict Myers-Briggs Type Indicator (MBTI) personalities, diverging from conventional text-based approaches. We developed a unique dataset, EmoMBTI, by mapping emojis to specific MBTI traits using diverse posts scraped from Reddit. This dataset enabled the integration …
DynaMentA
Mental health classification is inherently challenging, requiring models to capture complex emotional and linguistic patterns. Although large language models (LLMs) such as ChatGPT, Mental-Alpaca, and MentaLLaMA show promise, they are not trained on clinically grounded data and often overlook subtle psychological cues. Their predictions tend to overemphasize emotional intensity, while failing to capture contextually relevant indicators that are c…
Natural language processing as Digital Veda (डिजिटल वेद)
This article conceptualizes Natural Language Processing (NLP) as the Digital Veda (डिजिटल वेद), framing it as a culturally rooted communicative infrastructure inspired by the Vedic tradition of structured knowledge preservation and ethical discourse. Drawing on India’s linguistic and philosophical heritage, it positions NLP not as a neutral tool, but as an evolving ecosystem shaped by human values, language ideologies, and socio-cultural narrativ…
Computer Science (5 works) · Artificial Intelligence (4 works) · Data science (3 works) · Sentiment Analysis and Opinion Mining (3 works) · World Wide Web (3 works) · Complex Network Analysis Techniques (2 works) · Engineering (2 works) · Human Mobility and Location-Based Analysis (2 works) · Machine learning (2 works) · Psychology (2 works)