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Found 7 papers, 0 papers with code
NIT-Agartala-NLP-Team at SemEval-2020 Task 8: Building Multimodal Classifiers to tackle Internet Humor
The paper describes the systems submitted to SemEval-2020 Task 8: Memotion by the `NIT-Agartala-NLP-Team'.
Studying Generalisability across Abusive Language Detection Datasets
Work on Abusive Language Detection has tackled a wide range of subtasks and domains.
Validation of Facts Against Textual Sources
We propose a system which would verify a claim against a source and classify the claim to be true, false, out-of-context or an inappropriate claim with respect to the textual source provided to the system.
NIT\_Agartala\_NLP\_Team at SemEval-2019 Task 6: An Ensemble Approach to Identifying and Categorizing Offensive Language in Twitter Social Media Corpora
The paper describes the systems submitted to OffensEval (SemEval 2019, Task 6) on {`}Identifying and Categorizing Offensive Language in Social Media{'} by the {`}NIT{\_}Agartala{\_}NLP{\_}Team{'}.
A Societal Sentiment Analysis: Predicting the Values and Ethics of Individuals by Analysing Social Media Content
Several experiments were carried out on the corpora to classify the ethical values of users, incorporating Linguistic Inquiry Word Count analysis, n-grams, topic models, psycholinguistic lexica, speech-acts, and non-linguistic information, while applying a range of machine learners (Support Vector Machines, Logistic Regression, and Random Forests) to identify the best linguistic and non-linguistic features for automatic classification of values and ethics.
