A5041173496- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
- Wikis in Education and Collaboration
- Topic Modeling
- Advanced Graph Neural Networks
- Natural Language Processing Techniques
- Peer-to-Peer Network Technologies
- Social Media and Politics
- Hate Speech and Cyberbullying Detection
- Bioinformatics and Genomic Networks
- Cancer-related gene regulation
- Graph theory and applications
- Mental Health Research Topics
- Monoclonal and Polyclonal Antibodies Research
- Social Capital and Networks
- Effects of Radiation Exposure
- Media Influence and Politics
- Rough Sets and Fuzzy Logic
- Game Theory and Applications
- Cancer survivorship and care
- Cutaneous lymphoproliferative disorders research
- Populism, Right-Wing Movements
- Maternal and Perinatal Health Interventions
- vaccines and immunoinformatics approaches
- Misinformation and Its Impacts
All India Institute of Medical Sciences
2024
Medanta The Medicity
2023
Microsoft Research (India)
2023
Indian Institute of Technology Kharagpur
2016-2022
Technical University of Darmstadt
2021-2022
RWTH Aachen University
2019
Indian Institute of Technology Patna
2015-2018
Information Technology University
2017
University of Burdwan
2017
With the ongoing debate on 'freedom of speech' vs. 'hate speech,' there is an urgent need to carefully understand consequences inevitable culmination two, i.e., hate over time. An ideal scenario this would be observe effects speech in (almost) unrestricted environment. Hence, we perform first temporal analysis Gab.com, a social media site with very loose moderation policy. We generate snapshots Gab from millions posts and users. Using these snapshots, compute activity vector based DeGroot...
With the ongoing debate on 'freedom of speech' vs. 'hate there is an urgent need to carefully understand consequences inevitable culmination two, i.e., hate over time. An ideal scenario this would be observe effects speech in (almost) unrestricted environment. Hence, we perform first temporal analysis Gab.com, a social media site with very loose moderation policy. We generate snapshots Gab from millions posts and users. Using these snapshots, compute activity vector based DeGroot model...
In this paper, we explore how the C4.5 algorithm can be applied to breast cancer datasets in order extract and formulate rules for identifying risk factors. For study, have used Wisconsin dataset containing 9 attributes related various cell features anomalies. We then that create a decision tree. From inferred tree, patients at been derived. With training-set size of 200 patient records, our system was found an accuracy 96.7%.
Wikipedia can easily be justified as a behemoth, considering the sheer volume of content that is added or removed every minute to its several projects. This creates an immense scope, in field natural language processing toward developing automated tools for moderation and review. In this paper we propose Self Attentive Revision Encoder (StRE) which leverages orthographic similarity lexical units predicting quality new edits. contrast existing propositions primarily employ features like page...
With the widespread use of knowledge graphs (KG) in various automated AI systems and applications, it is very important to ensure that information retrieval algorithms leveraging them are free from societal biases. Previous works have depicted biases persist KGs, as well employed several metrics for measuring However, such studies lack systematic exploration sensitivity bias measurements, through varying sources data, or embedding used. To address this research gap, work, we present a...
Recent advances in the field of network representation learning are mostly attributed to application skip-gram model context graphs. State-of-the-art analogues graphs define a notion neighbourhood and aim find vector for node, which maximizes likelihood preserving this neighborhood. In paper, we take drastic departure from existing node by utilizing idea coreness. More specifically, utilize well-established that nodes with similar core numbers play equivalent roles hence induce novel an...
Millions of people irrespective socioeconomic and demographic backgrounds, depend on Wikipedia articles everyday for keeping themselves informed regarding popular as well obscure topics. Articles have been categorized by editors into several quality classes, which indicate their reliability encyclopedic content. This manual designation is an onerous task because it necessitates profound knowledge about language, navigating circuitous set wiki guidelines. In this paper we propose Neural...
Networks created from real-world data contain some inaccuracies or noise, manifested as small changes in the network structure. An important question is whether these can signficantly affect analysis results.
Many scale-free networks exhibit a "rich club" structure, where high degree vertices form tightly interconnected subgraphs. In this paper, we explore the emergence of clubs" in context shortest path based centrality metrics. We term these subgraphs connected closeness or betweeness as rich clubs (RCC). Our experiments on real world and synthetic high- light inter-relations between RCCs, expander graphs, core-periphery structure network. show empirically theoretically that RCCs exist, if...
In this paper, we introduce social yield, a measure of collaboration success the collaborating authors in coauthorship network. We then attempt to empirically observe link dynamics networks induced by yield collaborations. Observation indicate that certain observed behavior like presence large number small sized communities and highly dynamic links can be explained based on distribution these It is also among collaborations affects resilience targeted removal.
In this paper we evaluate the effect of noise on community scoring and centrality-based parameters with respect to two different aspects network analysis: (i) sensitivity, that is how parameter value changes as edges are removed (ii) reliability in context message spreading, time taken broadcast a removed. Our experiments synthetic real-world networks three models demonstrate for both over all models, permanence qualifies most effective metric. For sensitivity closeness centrality close...
Wikipedia has been turned into an immensely popular crowd-sourced encyclopedia for information dissemination on numerous versatile topics in the form of subscription free content. It allows anyone to contribute so that articles remain comprehensive and updated. For enrichment content without compromising standards, community enumerates a detailed set guidelines, which should be followed. Based these, are categorized several quality classes by editors with increasing adherence guidelines....
In this paper we evaluate the effect of noise on community scoring and centrality-based parameters with respect to two different aspects network analysis: (i) sensitivity, that is how parameter value changes as edges are removed (ii) reliability in context message spreading, time taken broadcast a removed. Our experiments synthetic real-world networks three models demonstrate for both over all models, permanence qualifies most effective metric. For sensitivity closeness centrality close...
Abstract The evolution of Artificial Intelligence (AI)‐based systems and applications have pervaded everyday life to make decisions that a momentous impact on individuals society. With the staggering growth online data, often termed as infosphere , it has become paramount monitor ensure social good AI‐based are severely dependent. This survey aims provide comprehensive review some most important research areas related infosphere, focusing technical challenges potential solutions. also...