drmuskangarg Goto Github PK
Name: Muskan Garg, PhD
Type: User
Bio: I am interested in research areas: natural language processing and information retrieval. Working on mental health detection and analysis on social media data.
Name: Muskan Garg, PhD
Type: User
Bio: I am interested in research areas: natural language processing and information retrieval. Working on mental health detection and analysis on social media data.
100 days of NLP
A dataset which contains 250 unique Tweets in each topic. This is a balanced form of the UTweet10 dataset. This BTweet10 repository is used for our work Keyphrase Extraction using Markov Decision Process from Social Media Data which was published in the proceedings of DSMLAI 2021 held in Namibia.
This repository is created to support the paper 'CAMS: An Annotated Corpus for Causal Analysis of Mental health on Social media' which is submitted to Language Resources and Evaluation Conference 2022 we introduce a new dataset for Causal Analysis of Mental health illness in Social media posts (CAMS). We first introduce the annotation schema for this task of causal analysis. The causal analysis comprises two types of annotations, viz, causal interpretation and causal categorization. We show the efficacy of our scheme in two ways: (i) crawling and annotating 3155 Reddit data and (ii) re-annotate the publicly available SDCNL dataset of 1896 instances for interpretable causal analysis. We further combine them as CAMS dataset.
Reddit dataset on caregivers experiences about cognitive decline
The categorization of CCS codes.
Expert Talk on Natural Language Processing and its Applications
Detailed Explanation
The undergraduate subject of Conversational AI
The descriptive analysis of EdgeGraph: A graph-based textual representation forKeyphrase Extraction using Random Walk
The dataset contains classification task for two interpersonal risk factors in social media posts: Thwarted Belongingness and Perceived Burdensomeness. This work is under review with ACL 2023
We construct and release our dataset on identifying fine-grained analysis of Interpersonal risk factors in Reddit posts.
We expect the release of the dataset and the evaluations will help facilitate the development of new methods for detecting lonesomeness in user-generated text.
LoST dataset
Characterizing the Progression from Mild Cognitive Impairment to Dementia: A Network Analysis of Longitudinal Clinical Visits
This repository of mental health classification using deep learning is created to study the phenomenon of classifying social media posts with importance aspects of mental health.
The study of the structural properties of the Microblog WCN for six different network metrics. This work is implementation for The structure of word co-occurrence network for microblogs published in_ Physica A: Statistical Mechanics and its Applications_. The study of structure and dynamics of complex networks has gained attention and witnessed growth in recent years. There are existing works on the Word Co-occurrence Networks (WCN) for English and Chinese languages. We explore the network science properties to study the structure of WCN for microblogs. The key parameters for microblogs WCN are scale-free property, small world feature, hierarchical organization, assortativity and spectral analysis.
This repository is build in association with our position paper on "Multimodality for NLP-Centered Applications: Resources, Advances and Frontiers". As a part of this release we share the information about recent multimodal datasets which are available for research purposes. We found that although 100+ multimodal language resources are available in literature for various NLP tasks, still publicly available multimodal datasets are under-explored for its re-usage in subsequent problem domains.
Introducing the MultiWD dataset, a meticulously curated collection of 3281 instances, purposefully created and annotated to enable the identification of multiple wellness dimensions within Reddit posts.
M Tech Course (PCS224) for Natural Language Processing
PCS224: NLP for Masters
Python for Data Engineers
This Github repository is generated for our work on UBIS: Unigram Bigram Importance Score for feature extraction and selection using graph of words which is under review in Expert Systems with Applications. It is interesting to note that the importance of uni-grams and bi-grams may contribute more efficiently in determining the feature space vector. In this research work, the Graph of Words (GoW) based selective feature extraction technique is proposed as Uni-gram Bi-gram Importance Score (UBIS) as obtained from node score and edge score in Graph of Words.
A toy dataset for Tweet summarization. This dataset is used in 'A survey on different dimensions for graphical keyword extraction techniques' which is published in Artificial Intelligence Review. We use this dataset to implement different graph-based keyword extraction techniques over Microblogs as compared to other well-formed datasets.
The WellnessDimension dataset is a four class classification problem to build explainable AI models. This repository is under review with ACL 2023.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.