Sentiment analysis is used for knowing voice or response of crowd for products, services, organizations, individuals, movie reviews, issues, events, news etc... In this paper we are going to discuss about exitin
Deep Learning on NLP in Pytorch using a Greek dataset with tweets regarding the elections . - Makri-Panagoula/Tweet-Sentiment-Analysis
Twitter Sentiment Analysis is machine learning project using Python, which comprehends of training the model using logistic regression algorithm to analyze the tweets as positive and negative. The dataset is of size 1.6 million tweets with training and testing records classified internally,with an accur...
例如IMDB上有很多关于电影的评论，那么我们就可以通过Sentiment Analysis来评估某部电影的口碑，甚至还可以...
Dataset Card for tweet_eval Dataset Summary TweetEval consists of seven heterogenous tasks in Twitter, all framed as multi-class tweet classification. The tasks include - irony, hate, offensive, stance, emoji, emotion, and sentiment. All tasks have been unified into the same benchmark, with ...
and other critical scenarios. The model is executed over a publicly available dataset extended for credibility assessment. The model provides good results with 95.6% accuracy by XGBoost using platinum features. The performance of the proposed model is compared with state-of-the-art that produced much...
second step, it automatically labels the positive or negative sentiment tweets to generate a training dataset, avoiding another human labeling step. The training data sets are used to build the sentiment analysis model. The system uses unsupervised learning to learn classifiers using the lexical ...
training and checking was chosen on the basis of Root Mean Square Error (RMSE). The accuracy was measured by comparing the predicted and actual values. We set various factors like dataset sample, number of epochs, membership function type and number of inputs very carefully to achieve the ...
pandas: A powerful library for data manipulation and analysis, used to load, clean, and process the dataset. scikit-learn: A machine learning library for Python, used for training the Logistic Regression model, performing TF-IDF vectorization, and evaluating model performance. NLTK: A toolkit for...
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