Reading list for Awesome Sentiment Analysis papers

Natural Language Toolkit for Malaysian language, https://malaya.readthedocs.io/

Topic modelling and analysis of different UK newspapers, primarily using BERTopic

Code and data for EMNLP2021 paper: WIKIBIAS: Detecting Multi-Span Subjective Biases in Language

An Empirical Evaluation of Word Embedding Models for Subjectivity Analysis Tasks

Testbench for sentiment and factuality in texts.

Subjectivity removal and Polarity classification of movie reviews employing a shallow model (Multinomial Naive Bayes) and a deep model (Bidirectional LSTM with self-attention)

This Twitter Sentiment Analyzer helps detect the Positive and the Negative Tweets by classifying the data, analysing the sentiments of the words that are commonly used and labelling them as positive and negative words. The Bag of Words (BoW) was used to detect Racist/Hate Speech from a training dataset extracted from Twitter API

Multi-View Sentiment Corpus (EACL 2017): tweets labelled by three annotators with sentiment, emotion, irony, subjectivity and implicitness

This is the repository for the newly created Czech Subjectivity Dataset (Subj-CS) and our paper:

Analyzing subjectivity in social networks

Exploring the 2021 AAPI movement using Twitter and news data.