Search Results for author: Siddharth Krishnan

Found 8 papers, 1 papers with code

Two-Stage Stance Labeling: User-Hashtag Heuristics with Graph Neural Networks

no code implementations16 Apr 2024 Joshua Melton, Shannon Reid, Gabriel Terejanu, Siddharth Krishnan

In this work, we develop a two stage stance labeling method that utilizes the user-hashtag bipartite graph and the user-user interaction graph.

Flurry: a Fast Framework for Reproducible Multi-layered Provenance Graph Representation Learning

no code implementations5 Mar 2022 Maya Kapoor, Joshua Melton, Michael Ridenhour, Mahalavanya Sriram, Thomas Moyer, Siddharth Krishnan

This lack of instrumentation severely inhibits scientific advancement in provenance graph machine learning by hindering reproducibility and limiting the availability of data that are critical for techniques like graph neural networks.

Anomaly Detection Graph Classification +2

Pay Attention to Relations: Multi-embeddings for Attributed Multiplex Networks

no code implementations3 Mar 2022 Joshua Melton, Michael Ridenhour, Siddharth Krishnan

In contrast to prior work, RAHMeN is a more expressive embedding framework that embraces the multi-faceted nature of nodes in such networks, producing a set of multi-embeddings that capture the varied and diverse contexts of nodes.

Community Detection Link Prediction +2

A Machine Learning Pipeline to Examine Political Bias with Congressional Speeches

no code implementations18 Sep 2021 Prasad hajare, Sadia Kamal, Siddharth Krishnan, Arunkumar Bagavathi

Computational methods to model political bias in social media involve several challenges due to heterogeneity, high-dimensional, multiple modalities, and the scale of the data.

BIG-bench Machine Learning

Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Models

no code implementations24 Jul 2020 Michael Ridenhour, Arunkumar Bagavathi, Elaheh Raisi, Siddharth Krishnan

We also analyze a multilayer network, constructed from two types of user interactions in Gab(quote and reply) and interaction scores from the weak supervision model as edge weights, to predict hateful users.

Network Embedding

ragamAI: A Network Based Recommender System to Arrange a Indian Classical Music Concert

no code implementations8 Dec 2019 Arunkumar Bagavathi, Siddharth Krishnan, Sanjay Subrahmanyan, S. L. Narasimhan

1) it will assist musicians to customize their performance with the necessary variety required to sustain the interest of the audience for the entirety of the concert 2) it will generate carefully curated lists of south Indian classical music so that the listener can discover the wide range of melody that the musical system can offer.

Recommendation Systems

Examining Untempered Social Media: Analyzing Cascades of Polarized Conversations

no code implementations10 Jun 2019 Arunkumar Bagavathi, Pedram Bashiri, Shannon Reid, Matthew Phillips, Siddharth Krishnan

Online social media, periodically serves as a platform for cascading polarizing topics of conversation.

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