Search Results for author: Sunil Gundapu

Found 8 papers, 1 papers with code

Transformer based Automatic COVID-19 Fake News Detection System

2 code implementations1 Jan 2021 Sunil Gundapu, Radhika Mamidi

For our analysis in this paper, we report a methodology to analyze the reliability of information shared on social media pertaining to the COVID-19 pandemic.

Fake News Detection Misinformation

gundapusunil at SemEval-2020 Task 8: Multimodal Memotion Analysis

no code implementations SEMEVAL 2020 Sunil Gundapu, Radhika Mamidi

Recent technological advancements in the Internet and Social media usage have resulted in the evolution of faster and efficient platforms of communication.

Sentiment Analysis

Word Level Language Identification in English Telugu Code Mixed Data

no code implementations PACLIC 2018 Sunil Gundapu, Radhika Mamidi

In a multilingual or sociolingual configuration Intra-sentential Code Switching (ICS) or Code Mixing (CM) is frequently observed nowadays.

Language Identification Machine Translation +2

Multichannel LSTM-CNN for Telugu Technical Domain Identification

no code implementations24 Feb 2021 Sunil Gundapu, Radhika Mamidi

With the instantaneous growth of text information, retrieving domain-oriented information from the text data has a broad range of applications in Information Retrieval and Natural language Processing.

Information Retrieval Machine Translation +5

Multichannel LSTM-CNN for Telugu Text Classification

no code implementations ICON 2020 Sunil Gundapu, Radhika Mamidi

With the instantaneous growth of text information, retrieving domain-oriented information from the text data has a broad range of applications in Information Retrieval and Natural language Processing.

Information Retrieval Machine Translation +7

Detection of Propaganda Techniques in Visuo-Lingual Metaphor in Memes

no code implementations3 May 2022 Sunil Gundapu, Radhika Mamidi

The exponential rise of social media networks has allowed the production, distribution, and consumption of data at a phenomenal rate.

Multimodal Deep Learning

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