CVIT's submissions to WAT-2019

no code implementations • WS 2019 • Jerin Philip, Shashank Siripragada, Upendra Kumar, Vinay Namboodiri, C. V. Jawahar

This paper describes the Neural Machine Translation systems used by IIIT Hyderabad (CVIT-MT) for the translation tasks part of WAT-2019.

Machine Translation Translation

A Societal Sentiment Analysis: Predicting the Values and Ethics of Individuals by Analysing Social Media Content

no code implementations • EACL 2017 • Tushar Maheshwari, Aishwarya N. Reganti, Samiksha Gupta, Anupam Jamatia, Upendra Kumar, Bj{\"o}rn Gamb{\"a}ck, Amitava Das

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.

Ethics General Classification +3

Cosmopolitan Mumbai, Orthodox Delhi, Techcity Bangalore:Understanding City Specific Societal Sentiment

no code implementations • WS 2016 • Aishwarya N. Reganti, Tushar Maheshwari, Upendra Kumar, Amitava Das

Emotion Recognition