Papers by Kartikey Pant

3 papers
SmokEng: Towards Fine-grained Classification of Tobacco-related Social Media Text (D19-55)

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Challenge: Contemporary datasets on tobacco consumption focus on one of two topics, public health mentions and disease surveillance, or sentiment analysis on topical tobacco products and services.
Approach: They propose to use a dataset of 3144 tweets to analyze slang related to smoking and then use it to create a binary and multi-class classification mechanism.
Outcome: The proposed method is able to identify a topic, a general mention or a more fine-grained classification based on the semantics of the tweets.
Towards Code-switched Classification Exploiting Constituent Language Resources (2020.aacl-srw)

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Challenge: Code-switching is a communicative phenomenon denoting a shift from one language to another within the same speech exchange.
Approach: They propose to convert code-switched data into its constituent high resource languages for use in both monolingual and cross-lingual settings.
Outcome: The proposed code-switching language can be used for multiple downstream tasks . the proposed language increases the F1 score by 22% and 42.5% compared to the state-of-the-art.
Towards Fine-grained Classification of Climate Change related Social Media Text (2022.acl-srw)

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Challenge: a new study examines the fine-grained classification and classification of climate change-related social media text.
Approach: They propose to use two datasets to analyze climate change-related social media text and propose a fine-grained classification based on the proposed dataset.
Outcome: The proposed datasets are compared with existing datasets and benchmarked using the best-performing model.

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